Singular FIOs in SAR Imaging, II: Transmitter and Receiver at Different Speeds
Gaik Ambartsoumian, Raluca Felea, Clifford J. Nolan, Venkateswaran P., Krishnan, and Eric Todd Quinto

TL;DR
This paper analyzes the mathematical properties of SAR imaging operators with moving transmitter and receiver at different speeds, revealing artifact behaviors and bifurcations in image quality.
Contribution
It classifies the forward operator as a Fourier integral operator with singularities and characterizes the normal operator's structure in different motion scenarios.
Findings
Artifacts are as strong as the true image in both cases.
Normal operator belongs to specific classes of Fourier integral operators.
A bifurcation in artifact types occurs when source and receiver move in opposite directions.
Abstract
In this article, we consider two bistatic cases arising in synthetic aperture radar imaging: when the transmitter and receiver are both moving with different speeds along a single line parallel to the ground in the same direction or in the opposite directions. In both cases, we classify the forward operator as a Fourier integral operator with fold/blowdown singularities. Next we analyze the normal operator in both cases (where is the -adjoint of ). When the transmitter and receiver move in the same direction, we prove that belongs to a class of operators associated to two cleanly intersecting Lagrangians, . When they move in opposite directions, is a sum of such operators. In both cases artifacts appear and we show that they are, in general, as strong as the bona-fide part of the image. Moreover, we…
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Singular FIOs in SAR ImagingAmbartsoumian, Felea, Krishnan, Nolan, and Quinto
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Singular FIOs in SAR Imaging, II: Transmitter and
Receiver at Different Speeds††thanks: Submitted to the editors DATE.
G. Ambartsoumian Department of Mathematics, University of Texas at Arlington, TX, USA () [email protected]
R. Felea (Corresponding Author) School of Mathematical Sciences, Rochester Institute of Technology, NY, USA () [email protected]
V. P. Krishnan TIFR Centre for Applicable Mathematics, Bangalore, Karnataka, India () [email protected]
C. J. Nolan Department of Mathematics and Statistics, University of Limerick, Ireland () [email protected]
E. T. Quinto Department of Mathematics, Tufts University, Medford, MA, USA ()
Abstract
In this article, we consider two bistatic cases arising in synthetic aperture radar imaging: when the transmitter and receiver are both moving with different speeds along a single line parallel to the ground in the same direction or in the opposite directions. In both cases, we classify the forward operator as a Fourier integral operator with fold/blowdown singularities. Next we analyze the normal operator in both cases (where is the -adjoint of ). When the transmitter and receiver move in the same direction, we prove that belongs to a class of operators associated to two cleanly intersecting Lagrangians, . When they move in opposite directions, is a sum of such operators. In both cases artifacts appear and we show that they are, in general, as strong as the bona-fide part of the image. Moreover, we demonstrate that as soon as the source and receiver start to move in opposite directions, there is an interesting bifurcation in the type of artifact that appears in the image.
keywords:
Singular Fourier integral operators; Elliptical Radon transforms; Synthetic Aperture Radar; Fold and Blowdown singularities
{AMS}
Primary 35S30, 35R30; Secondary 50J40
1 Introduction
Synthetic Aperture Radar (SAR) is a high-resolution imaging technology that uses antennas on moving platforms to send electromagnetic waves to objects of interest and measures the scattered echoes. These are then processed to form an image of the objects. For a good overview of SAR imaging, especially from a mathematical point of view, we refer the reader to [6, 7]. In monostatic SAR imaging, the moving transmitter also acts as a receiver, whereas in bistatic SAR imaging, the transmitter and receiver are located on different platforms.
Our focus in this article is on a bistatic SAR imaging setup, where the transmitter and receiver move along a straight line parallel to the ground, in the same direction or in the opposite directions, and with different speeds (see (2.1)). Here and in the rest of the article we assume that the ground is represented by a plane. The SAR imaging task is then mathematically equivalent to recovering the ground reflectivity function from the measured data for a certain period of time along each point of the receiver trajectory. Since exact reconstruction of from is an extremely difficult task, a reasonable compromise (acceptable in practice for most applications) is to find the singularities of from . In particular, this will allow to see the edges (and hence shapes) of the objects on the ground. Unfortunately even that simpler task may not be completely accomplishable, since in certain setups may not have enough information for correct recovery of singularities of . In these cases, the best possible reconstruction of may miss certain parts of the original singularities, or have added “fake” singularities, called artifacts.
In this article, the reconstructed images, including artifacts, are analyzed using the calculus of singular Fourier integral operators (FIOs). The forward operator which maps singularities in the scene to those in the data is an FIO. It is conventional to reconstruct the image of an object by using the backprojection operator, applied to the data . We study the normal operator and the artifacts which appear by using this method.
The current article is a continuation of our prior work [2], where, motivated by certain multiple scattering scenarios, we considered the case when the transmitter and receiver move at equal speeds away from a common midpoint along a straight line. The main result of that article made precise the added singularities and their strengths (in comparison to the true singularities) when reconstruction is done using the backprojection method mentioned above. We showed that the backprojection method introduces three additional singularities for each true singularity with potentially no way of avoiding them if the transmitter and receiver are assumed omnidirectional. One of our main motivations in studying the case of different speeds for the transmitter and receiver was to remove some of these artifacts. However, when the transmitter and receiver move away from each other, the backprojection method still introduces additional artifacts, which in the limiting case (when the speeds are equal) gives the artifacts considered in [2].
The microlocal analysis of the normal operator in the study of generalized Radon transforms and in imaging problems has a long history. Guillemin and Sternberg were the first to study integral geometry problems from the FIO and microlocal analysis point of view, and made fundamental contributions [21, 20]. Later, paired Lagrangian calculus introduced by Melrose-Uhlmann [27] and Guillemin-Uhlmann [22], and also studied in Antoniano-Uhlmann [4] was used by Greenleaf-Uhlmann in several of their highly influential works on the study of generalized Radon transforms [17, 18]. Microlocal techniques have also been very useful in the context of seismic imaging [5, 31, 38, 29, 37, 8, 12]), in sonar imaging see [11, 13, 33]), in X-ray Tomography; in addition to works mentioned above also see [32, 24, 15, 14, 16]), and in tensor tomography [34, 35, 39].
The microlocal analysis of linearized SAR imaging operators (both monostatic and bistatic) was done in [30, 40, 10, 2, 36]. Bistatic SAR imaging problems, due to the fact that the transmitter and receiver are spatially separated, naturally lead to the study of elliptical Radon transforms, which are also of independent interest. These have been studied in the literature as well [3, 1, 28].
The article is organized as follows: In Section 2 we state the main facts and results: the positions of the transmitter and receiver that we consider (2.1), the forward operator (2.2), the canonical relation of and the properties of the projections from its canonical relation ( and ) (Theorems 2.1 and 2.4). Then, we describe the composition calculus results (Theorems 2.2 and 2.6).
In Section 3 we recall briefly the definition of the fold/blowdown singularities and the properties of the classes we need in this article, and Section 4 briefly summarizes the main result of [2].
In Section 5 we consider the case when the transmitter and receiver are moving in the same direction along a line parallel to the ground. We show that the normal operator has a distribution kernel belonging to the paired Lagrangian distribution class where is the diagonal relation and is the graph of a simple reflection map about the -axis. This result is valid even if the transmitter is stationary, for example, when the transmitter is a fixed radio tower and the receiver is a drone.
In Section 6 we consider the case when the transmitter and receiver move in opposite directions along the line, and the analysis becomes considerably more complicated. To distinguish this case from the case in Section 5, we denote the forward operator by . First of all, the projections drop rank by one along two smooth disjoint hypersurfaces . Then, Theorem 2.6 shows that the backprojection adds two sets of artifacts and the normal operator is a sum of operators belonging to classes: , where causes the same artifact which appears for in Section 5 and is a two-sided fold (Def. 3.2). Finally, in section 6.4 we consider spotlighting, in which certain portions of the ground are selectively illuminated. In this case, we show that the normal operator belongs to where is a two-sided fold canonical relation (see Theorem 6.15).
In Appendix A, we prove Theorem 2.2 using the iterated regularity method and in Appendix B, we give a geometric explanation of the points we cannot image in the case considered in Section 6.
In all these situations, we show that additional artifacts (coming from and ) could be just as strong as the bona-fide part of the image, in other words, singularities related to . In this article, for , the strength of the artifact () means the order of on . We find the order of on both and and, if they are the same, then we conclude that in general, the artifact is as strong (see Remarks 2.3 and 2.7).
An obvious but perhaps important observation that follows from the results of this paper is that if one has a choice of having the source and receiver platforms moving in the same or opposite directions along the same straight line, then it is highly preferable to have them move in the same direction in order to avoid additional set of artifacts, other than the usual left-right ambiguities.
2 Statements of the main results
2.1 The linearized scattering model
For simplicity, we assume that both the transmitter and receiver are at the same height above the ground at all times and that the transmitter and receiver move at constant but different speeds along a line parallel to the axis. Let
[TABLE]
for be the trajectories of the transmitter and receiver respectively.
The case corresponds to the common midpoint problem, which was fully analyzed in [2]. Therefore we will assume . We also assume , since corresponds to the monostatic case (where the same device serves as both a transmitter and a receiver) and has also been fully analyzed in earlier works [30, 10].
We are aware that there are other cases for the transmitter and receiver to be considered, like moving along parallel lines at different heights or along skew lines at different speeds or along intersecting lines in a plane parallel to the ground. At this point we can only say that in those cases the left-right ambiguity which appears in the case considered in this article will, in general, be lost. However, we will limit the analysis of and only to the case mentioned in (2.1) since it is already leads to interesting analysis. We point out that, in practice, the flight paths can be more complicated because of turbulence and other factors.
The linearized model for the scattered signal we will use in this article is
[TABLE]
for , where is the function modeling the object on the ground, and
[TABLE]
is the bistatic distance–the sum of the distance from the transmitter to the scatterer and from the scatterer to the receiver, is the speed of electromagnetic wave in free-space and the amplitude term is given by
[TABLE]
This function includes terms that take into account the transmitted waveform and geometric spreading factors.
From now on, we denote the space by and the space by .
For simplicity, we will assume that . Because the ellipsoidal wavefronts do not meet the ground for
[TABLE]
there is no signal for such . As we will see, our method cannot image the point on the ground directly “between” the transmitter and receiver (see the proof of Theorem 2.1 in Section 5). Given transmitter and receiver positions and respectively, such a point on the ground has coordinates . Note that this point on the -axis corresponds to . For these two reasons, we multiply by a cutoff function that is zero in a neighborhood of
[TABLE]
In addition, to be able to compose our forward operator and its adjoint, we further assume that is compactly supported and equal to in a neighborhood of a suitably large compact subset of
[TABLE]
We let , and this gives us the data
[TABLE]
We require additional cutoffs for our analysis to work for the case of (see Remarks 2.5 and 6.6).
Throughout the article we use the following notation
[TABLE]
and we define the ellipse
[TABLE]
We assume that the amplitude function , that is, it satisfies the following estimate: For every compact and for every non-negative integer and for every -index and , there is a constant such that
[TABLE]
This assumption is satisfied if the transmitted waveform from the antenna is approximately a Dirac delta distribution. The qualitative features predicted by the approach based on microlocal analysis are consistent with practical reconstructions, including for example, the well-known right-left ambiguity artifact in low-frequency SAR images [7].
2.2 Transmitter and receiver moving in the same direction:
The case corresponds to the situation when the transmitter and receiver are traveling in the same direction along a line parallel to the ground or when the transmitter is stationary () on that line. For , we refer to the forward operator by . We show that for the case , the operator in (2.2) is a FIO of order and study the properties of the natural projection maps from the canonical relation of . We have the following results.
Theorem 2.1**.**
Let be the operator in (2.2) for .
* is an FIO of order .* 2. 2.
The canonical relation associated to is given by
[TABLE]
where and are defined in (2.3). Furthermore, is a global parameterization of . 3. 3.
Denote the left and right projections from to and by and respectively. Then and drop rank simply by one on the set
[TABLE] 4. 4.
* has a fold singularity along and has a blowdown singularity along (see Def. 3.1).*
We next analyze the imaging operator .
Theorem 2.2**.**
Let be as in Theorem 2.1. Then , where
[TABLE]
*which is the graph of . *
Remark 2.3**.**
*Since , using the properties of the classes [22], we have that microlocally away from , is in and microlocally away from , . This means that has the same order on both and which implies that the artifacts caused by will, in general, have the same order as the reconstruction of the singularities in that cause them (see the comments below Def. 3.7). However, more complicated behavior can occur including smoothing or cancellation of artifacts. *
2.3 Transmitter and receiver moving in opposite directions:
When , the transmitter and receiver travel away from each other, and we refer to the forward operator by .
2.3.1 Further preliminary modifications of the scattered
data
In the case when , we further modify the operator considered in Section 2.1.
Our method cannot image a neighborhood of two points on the ground for a given transmitter and receiver positions in addition to the points muted by the cutoff function in Section 2.1. Therefore we modify or pre-process the receiver data further such that the contribution to it from a neighborhood of these two points is [math]. The two points on the -axis that we would like to avoid are of the form , where
[TABLE]
as explained in Remark 2.5. We define a smooth mute function that is identically [math] if the ellipse is near one of the points ; for each , the corresponding values of are
[TABLE]
where and are given by (2.3). The points are given explicitly in Appendix B.
With the function , we modify in (2.2) by replacing by and call it again. Throughout this section, corresponding to the case , we will designate the operator as . That is, we have
[TABLE]
where takes into account the cutoff functions in Section 2.1 and the function defined in the last paragraph.
Theorem 2.4**.**
Let be the operator given in (2.12) for . Then
* is an FIO of order * 2. 2.
The canonical relation associated to is given by (2.6) with global parameterization . 3. 3.
The left and right projections and respectively from drop rank simply by one on the set where is given by (2.7) and
[TABLE] 4. 4.
* has a fold singularity along (see Def. 3.1).* 5. 5.
* has a blowdown singularity along and a fold singularity along (see Def. 3.1).*
For convenience, we denote, for each , the projection of the part of above to (the projection to the base of \pi_{R}\left({{\Sigma_{2}}{\big{|}_{s}}}\right)) by , and this is the circle described in (2.14) and in Appendix B. It can be written
[TABLE]
Remark 2.5**.**
From Equation (2.14) we have that is a circle of radius and centered at .
*Now we can explain why we need to cutoff the data for ellipses near the two points given by (2.9)-(2.10). Since intersects above these two points, drops rank by two above these points. So, we mute data near given by (2.11). We will precisely describe this mute, in Remark 6.6. *
We now analyze the imaging operator . Unlike the case , this case is more complicated and we consider several restricted transforms.
Theorem 2.6**.**
Let and . Let be the operator in (2.12) and let
[TABLE]
Then the following hold:
Let and and let be a smooth cutoff function that is compactly supported in . Consider the operator defined in (2.12) with the amplitude function replaced by . Then where is defined in (2.8). 2. 2.
Let and where is defined in (2.11). Let be a smooth cutoff function and compactly supported in . Consider the operator defined in (2.12) with the amplitude function replaced by . Then where is a two-sided fold given by (6.1). 3. 3.
Let and or with defined in (2.11). Let be a smooth cutoff function compactly supported in . Consider the operator defined in (2.12) with the amplitude function replaced by . Then .
Remark 2.7**.**
Using the properties of the classes for case 2 of the theorem,
[TABLE]
*implies that artifacts in the reconstruction could show up because of (reflection in the axis) and because of (a 2-sided fold). Furthermore, from the discussion below Definition 3.8, we have that , and and thus these artifacts could be, in general, as strong as the bona-fide part of the image (corresponding to ). *
3 Preliminaries: Singularities and
classes
Here we introduce the classes of distributions and singular FIO we will use to analyze the forward operators and and the normal operators and .
Definition 3.1**.**
[19]** Let and be manifolds of dimension and let be . Define .
* drops rank by one simply on if for each , *
rank and . 2. 2.
* has a Whitney fold along if is a local diffeomorphism away from and drops rank by one simply on , so that is a smooth hypersurface and for every .* 3. 3.
* is a blowdown along if is a local diffeomorphism away from and drops rank by one simply on , so that is a smooth hypersurface and for every .*
Definition 3.2** ([26]).**
*A smooth canonical relation for which both projections and have only (Whitney) fold singularities, is called a two-sided fold or a folding canonical relation. *
This notion was first introduced by Melrose and Taylor [26], who showed the existence of a normal form in .
Theorem 3.3** ([26]).**
*If dim dim and is a two-sided fold, then microlocally there are homogeneous canonical transformations, and , such that near where, . *
We now define classes. They were first introduced by Melrose and Uhlmann [27], Guillemin and Uhlmann [22] and Greenleaf and Uhlmann [18] and they have been used in the study of SAR imaging [30, 10, 25, 2].
Definition 3.4**.**
*Two submanifolds and intersect cleanly if is a smooth submanifold and . *
Consider two spaces and and let and and and be Lagrangian submanifolds of the product space . If they intersect cleanly, and are equivalent in the sense that there is, microlocally, a canonical transformation which maps into and . This leads us to the following model case.
Example 3.5**.**
*Let be the diagonal in and let . Then, intersects cleanly in codimension . *
Now we define the class of product-type symbols .
Definition 3.6**.**
* is the set of all functions such that for every and every there is such that*
[TABLE]
*for all . *
Since any two sets of cleanly intersecting Lagrangians are equivalent, we first define classes for the case in Example 3.5.
Definition 3.7** ([22]).**
Let be the set of all distributions such that with and
[TABLE]
*with where and . *
This allows us to define the class for any two cleanly intersecting Lagrangians in codimension using the microlocal equivalence with the case in Example 3.5.
Definition 3.8**.**
[22*]** Let be the set of all distributions such that where , , the sum is locally finite and where is a zero order FIO associated to , the canonical transformation from above, and . *
This class of distributions is invariant under FIOs associated to canonical transformations which map the pair to itself, whilst also preserving the intersection. By definition, if its Schwartz kernel belongs to . If then and [22]. Here by , we mean that the Schwartz kernel of belongs to microlocally away from .
To show that a distribution belongs to class we use the iterated regularity property:
Theorem 3.9** ([18, Proposition 1.35]).**
*If then if there is an such that for all first order pseudodifferential operators with principal symbols vanishing on , we have . *
In section 6, we will use the following theorem.
Theorem 3.10** ([10, 29]).**
*If is a FIO of order m whose canonical relation is a two-sided fold then where is another two-sided fold. *
4 Summary of the main result for the case
Recall that in the statement of Theorem 2.6, we assumed that . In fact, as already mentioned in the introduction, the case when in the context of Theorem 2.6 was analyzed in our earlier paper [2], and the results obtained in this work can be considered as a bifurcation of the singularities that appear for the case when , as . With this is mind, we state the main result obtained in [2], and briefly explain how our earlier result fits into the framework of the current article.
Let denote the operator
[TABLE]
where
[TABLE]
Theorem 4.1**.**
[2]** Let be the operator in (4.1). Then the normal operator can be decomposed as a sum:
[TABLE]
Here and denote the additional singularities (artifacts) caused due to reflection about the axis, reflection about the axis and rotation by about the origin, respectively. In other words, is the same as the one defined in (2.8) and and are defined as:
[TABLE]
and
[TABLE]
The theorem above is a limiting case of the result in Theorem 2.6, and in the limit, there is a bifurcation of the singularities, due to the presence of Lagrangians in the result above compared to in Theorem 2.6. From (2.13), we see that when , the circle given by the equation
[TABLE]
becomes the straight line regardless of the value , and as noted in Remark 2.3 of [2], the canonical relation associated to the operator is a 4-1 relation due to the symmetries with respect to both the and axes. When , the additional symmetry (about the axis) in the canonical relation of is broken. This was one of our main motivations for the results in this paper.
5 Analysis of the operator and the imaging operator
for
In this section, we prove Theorems 2.1 and 2.2.
Proof 5.1** (Proof of Theorem 2.1).**
We first prove that
[TABLE]
is a non-degenerate phase function. We have that is a phase function in the sense of Hörmander [23] because at points where the amplitude of the operator is elliptic. The differential vanishes at a point on the ground directly “between” the source and receiver and this point is given by . However, in a neighborhood of such points the amplitude vanishes due to the cutoff function in the definition of given in (2.2). Also we have that is nowhere [math] since . The same reason that is non-vanishing at points where the amplitude is elliptic also gives that is non-degenerate. Since satisfies an amplitude estimate, is an FIO [9]. Finally since is of order , the order of the FIO is [9, Definition 3.2.2]. By definition [23, Equation (3.1.2)]
[TABLE]
This establishes (2.6). Furthermore, it is easy to see that is a global parametrization of .
Now we prove the claims about the canonical left and right projections from , the final parts of Theorem 2.1. In the parameterization of , we have
[TABLE]
and the derivative is
[TABLE]
Then
[TABLE]
The third term would be zero when the unit vectors and point in opposite directions, but this cannot happen since the transmitter and receiver are above the plane of the Earth. Also since , . Hence, this determinant vanishes to first order when . This corresponds to given in (2.7).
On the kernel of is spanned by . So has a fold singularity along .
Similarly, we have,
[TABLE]
Then
[TABLE]
has the same determinant as .Therefore drops rank simply by one on . On , the kernel of is spanned by and which are tangent to . Thus has a blowdown singularity along .
Next we analyze the imaging operator . We have the following integral representation for :
[TABLE]
where
[TABLE]
After an application of the method of stationary phase in and , the Schwartz kernel of this operator becomes
[TABLE]
where
[TABLE]
Note that since we have assumed that .
Proposition 5.2**.**
Let . The wavefront relation of the kernel of satisfies
[TABLE]
*where is the diagonal in , and is given by (2.8). We have that and intersect cleanly in codimension 2 in or . *
Proof 5.3**.**
Let . Then we have
[TABLE]
and implies
[TABLE]
From the first two relations in (5.4) and (5.3), we have
[TABLE]
and
[TABLE]
We will use prolate spheroidal coordinates with foci and to solve for and . We let
[TABLE]
with and positive, and in the interval and and in . In this case and we use it to solve for . Hence
[TABLE]
and
[TABLE]
Noting that and , the first relation given by (5.6) in these coordinates becomes
[TABLE]
from which we get
[TABLE]
The second relation, given by (5.7), becomes
[TABLE]
After simplification we get
[TABLE]
which implies either that
[TABLE]
(since we can assume for points on the ground) or that
[TABLE]
where and are defined as in (2.3) but evaluated at and the third term in the equality is equivalent to the first term.
We consider Conditions (5.13) and (5.14) separately. First, assume Condition (5.13) holds. Then we have . In this case,
[TABLE]
and note that implies that . We also remark that it is enough to consider as no additional relations are introduced by considering over the relations we now address. Now we go back to and coordinates. If then for . In this case, the composition, . If then . For these points the composition, is a subset of in (2.8). Note that (5.14) has no solutions for . The statements about clean intersection are the same as the one given in [2]. This concludes the proof of Proposition 5.2.
Proof 5.4** (Proof of Theorem 2.2).**
We will use the iterated regularity method (Theorem 3.9) to show that the kernel of . We consider the generators of the ideal of functions that vanish on [10]. These are given by
[TABLE]
We show in Appendix A that each can be expressed as sums of products of and with smooth functions. Let , for , where are homogeneous of degree in , and are homogeneous of degree [math] in and is homogeneous of degree in . Let be pseudodifferential operators with principal symbols for . The and arguments using iterated regularity are similar to those used in [10, Thm. 1.6] and in [25, Thm. 4.3].
*We use the same arguments as in [2] to show that the orders from are and . *
6 Analysis of the forward operator and the imaging operator
for
In this section, we analyze the operator in (2.12). In [2] we analyzed the case . For the case with , we make another simplification:
[TABLE]
If , then we can reduce it to the case by using the diffeomorphisms and .
We first prove Theorem 2.4.
Proof 6.1** (Proof of Theorem 2.4).**
In the proof of this theorem, most of the statements are already proved in Theorem 2.1. We just prove the statements regarding the properties of the projection maps and . Recall from the proof of Theorem 2.1 that
[TABLE]
and
[TABLE]
Clearly this determinant drops rank when the first term, . This corresponds to given by (2.7).
The determinant also drops rank when the second term is zero, which can occur when ; this corresponds to given by (2.13). Note that drops rank by 2 at the intersection points of and (where ) but we exclude them using the cutoff function described preceding (2.11).
On , using the first, second, and fourth row of , the kernel is which applied to gives us . We have that and . If then using we get which is a contradiction. Thus which implies that has a fold singularity along .
Similarly,
[TABLE]
*has the same determinant up to sign and so drops rank by one on . On , using the last row of , the kernel is which applied to gives . If then from we obtain which is a contradiction. Hence which implies that has a fold singularity along as well. This completes the proof of Theorem 2.4. *
Proposition 6.2**.**
For , the wavefront relation of the kernel of satisfies,
[TABLE]
where is the diagonal in , is given by (2.8) and is defined as
[TABLE]
*where and , and and is given by (2.4). Furthermore, and intersect cleanly in codimension 2, and intersect cleanly in codimension 1, and intersect cleanly in codimension 1, and . *
Proof 6.3**.**
In fact, this proposition is already proved in Proposition 5.2. Here, unlike the situation in Proposition 5.2, there is a nontrivial contribution to the wavefront of the composition from (5.14). Hence for , we have that
[TABLE]
To show that no point in has , one uses (5.14) and that in (5.11). Finally, note that since we exclude the points of intersection of and due to the cutoff function defined in Section 2.3. One can show that is an immersed conic Lagrangian manifold that is a two-sided fold using Definition 3.2 and the proof of Theorem 6.13 part (b)).
Using Def. 3.4 and the calculations above, one can also show that these manifolds intersect in the following ways:
- (a)
* intersects cleanly in codimension 2,*
[TABLE]
This is part of Proposition 5.1 in **[2]**. 2. (b)
* intersects cleanly in codimension 1,*
[TABLE]
Note that the condition that in implies and so the condition does not increase the codimension of the intersection. Using **[26]**, one can show the intersection is clean. 3. (c)
* intersects cleanly in codimension 1,*
[TABLE]
Using **[26]**, one can show the intersection is clean. 4. (d)
* since we exclude the points of intersection of and .*
*This completes the proof of the proposition. *
For the rest of the proof, we focus on . Let , then . Let . then, by (6.1) there is an such that and are both in and
[TABLE]
where are given below (6.1). Therefore, if then
[TABLE]
A calculation shows that if then
[TABLE]
If , then is the equation of a vertical line with intercept .
We first use this characterization of to prove Statements (1) and (3) of Theorem 2.6. As already mentioned, the diagonal relation and given by (2.8) intersect cleanly in codimension 2 on either submanifold. Hence there is a well-defined class associated to and .
6.1 Proof of Theorem 2.6**,**
Statement (1)
Recall from statement (1) of this theorem that the function is a cutoff function compactly supported in
[TABLE]
where (see (2.16)) can be written in terms of as
[TABLE]
We show that for , there are no and satisfying (6.2). Therefore, where is the Schwartz kernel of .
So, assume for some (6.2) holds. Then, the right-hand side of (6.3) can be estimated by
[TABLE]
Since , if , this calculation and (6.3) shows that has no solution. Therefore there are no solutions to (6.2) if . Now assume for some , , then for (6.2) to have a solution that means that there must be a point with . However, this is impossible since . This shows that for , there is no solution to (6.2).
Now following the proof of Theorem 2.2, we achieve the result of Statement (1).
6.2 Proof of Theorem 2.6**,**
Statement (3)
Recall that the cutoff function is compactly supported in
[TABLE]
where is defined in (2.11). The operator we analyze in this part of the proof is .
We define the following set
[TABLE]
Note that , is the vertical line , and if is small enough, . By (6.3), when and then is the circle centered at and of radius
[TABLE]
Let . If there were a solution to (6.2) for some , then (as on ) and . If then the ellipse encloses by a calculation. Therefore, by the final statement of Lemma 6.4, meets no circle for and so there is no solution to (6.2). Now, if then the ellipse is enclosed by and, by the final statement of Lemma 6.4, meets no for and so there is no solution to (6.2) in this case, too. Therefore, where is the Schwartz kernel of . Now proceeding as in the proof of Theorem 2.2, we complete the proof of Statement (3) of Theorem 2.6.
The rest of this section is devoted to the proof of Statement (2) of Theorem 2.6.
6.3 Proof of Theorem 2.6,
Statement (2)
The reconstruction operator we consider in statement (2) of Theorem 2.6 is where the mute has compact support in
[TABLE]
where is defined in (2.11) and where is defined by (6.5).
Recall that the canonical relation of drops rank on the union of two sets, and . Accordingly, we decompose into components such that the canonical relation of each component is either supported near a subset of the union of these two sets, one of these two sets or away from both these sets. To do this, we define several cutoff functions.
6.3.1 The primary cutoff functions and
The cutoff will be equal to near the -axis and zero away from it, and will be equal to one near and equal to zero away from it as in Figure 1.
To define these functions precisely, we need to set up some preliminary relations. Because the mute function is zero near and has compact support, there is an such that is zero for and all . Because the radius and the function is continuous, there is a such that . Since (see (6.8)) is an increasing function in and separately, we can choose such that
[TABLE]
Without loss of generality, we can assume
[TABLE]
Now, let be an infinitely differentiable function defined as follows:
[TABLE]
and we extend this function smoothly between [math] and .
For , let be defined by
[TABLE]
Note that can be explicitly calculated using (6.8). So, if , is a nontrivial circle. Finally, note that if , then ; this is true because for such .
To define we first prove a lemma about the circles .
Lemma 6.4**.**
Let .
If then is to the left of the vertical line which is to the left of for any . 2. 2.
If then is contained inside , and these circles do not intersect. 3. 3.
For any ,
[TABLE]
is an open set containing .
Proof 6.5**.**
Statement (1) of the lemma is a straightforward calculation.
Now, fix . Let , then the endpoints of on the -axis are
[TABLE]
Clearly the functions and are smooth for . It is straightforward to see that is a strictly increasing smooth function for .
We prove that the function is strictly decreasing by showing is always negative. A somewhat tedious calculation shows that
[TABLE]
By replacing the square root in this expression by the upper bound , we see that
[TABLE]
and the right-hand side of this expression is clearly negative.
The circles are symmetric about the -axis, so if and are points in with , since , the circle is strictly inside the circle . This proves (2).
*By the choice of in (6.11), and . Because and are smooth strictly monotonic functions with nonzero derivatives, is a foliation of an open, connected region containing , and this proves (3). *
We define
[TABLE]
and we extend smoothly between (which is possible by Lemma 6.4, statement (3)). By the lemma, is equal to on an open neighborhood of and zero away from .
We assume, without loss of generality, that and are symmetric about the -axis.
Remark 6.6**.**
We now can define the function in Remark 2.5. We let
[TABLE]
The set is represented by the shaded set in Figure 2 that is near and the -axis. Let be a smooth function of that is zero if the ellipse given in (2.4) intersects and is equal to if does not meet .
6.3.2 Properties of and end of proof
We now write where are given in terms of their kernels
[TABLE]
where is the phase function of . The supports of the are given in Figure 3.
Now we consider , which using the decomposition of as above can be written as
The theorem now follows from Lemmas 6.7-6.11, and Theorem 6.13, which we now state and prove. In the lemmas, we analyze the compositions above.
Recall that and are operators defined as follows:
[TABLE]
and
[TABLE]
Lemma 6.7**.**
*The operators and are smoothing. *
Proof 6.8**.**
We show that is smoothing. The proof for the case of is similar.
We have
[TABLE]
where and are defined in (6.12) and (6.14) respectively. The Schwartz kernel of is
[TABLE]
where has the following products of cutoff functions as an additional factor:
[TABLE]
Here is determined from and as the value for which . For this reason, in trying to understand the propagation of singularities, we need only to restrict ourselves, for each fixed , to those base points and for which
[TABLE]
We use this setup to show is smoothing by showing its symbol is zero for covectors in (note that our argument shows that the symbol of the operator is zero in a neighborhood in of ). Let . Then, there is an such that and . For the rest of the proof, we fix this . (If there are other values of associated to the composition, we repeat this proof for those values of .)
Because , we consider three cases separately.
- I.
Covectors :* In this case, and is in . By the choice of the function in Remark 6.6, the symbol of is zero above such .* 2. II.
Covectors :* In this case, and the argument in case I shows that the symbol of is zero for such and * 3. III.
Covectors :* If , then for some above, there is a , such that*
[TABLE]
Using (6.17), the fact that , we see that and . Now, using the restriction on in (6.18) and the fact that , we see . Putting this together shows that
[TABLE]
Since , this shows that . Therefore and by Remark 6.6. Therefore, the symbol of is zero near so is smoothing near .
*This finishes the proof that is smoothing. *
Lemma 6.9**.**
*The operator is smoothing. *
Proof 6.10**.**
Recall that the Schwartz kernel of is
[TABLE]
*For each fixed , the support of is inside and by the choice of the function in Remark 6.6, the symbol of is zero above such . *
Lemma 6.11**.**
*The operators , and can be decomposed as a sum of operators belonging to the space . *
Proof 6.12**.**
Each of these compositions is covered by the transverse intersection calculus.
We decompose , , and into a sum of operators on which the compositions will be easier to analyze. This is represented in Figure 4.
For , note that divides in three regions since by (6.10). Let be the part of to the left of and let be the part inside and the part to the right of . Define our partitioned operators as follows where
[TABLE]
for . Note that the symbols are all smooth because
[TABLE]
is a smooth cutoff function in since the support of is inside and the support of does not meet .
We decompose into two operators in a similar way. Let be the open upper half plane and let be the open lower half plane. Define
[TABLE]
for Because the functions are supported away from the axis, these symbols are smooth.
We decompose into four operators in a similar way using Figure 4: divides into four regions , the unbounded region above the -axis, , it’s mirror image in the -axis, the bounded region inside and above the -axis, and its mirror image, . We define
[TABLE]
for , and because of the cutoffs used, these are all FIO with smooth symbols.
To find the canonical relation of , we consider and let such that and . In any case, has canonical relation a subset of . To find which subset, we consider the restriction that the supports of the put on and . We use the fact that and are on plus the following rules to understand the canonical relations of these operators:
If the supports exclude and from being equal, then the canonical relation () of the composed operator does not include . 2.
if the supports exclude and from being reflections in the axis then the canonical relation of the composed operator does not include . 3.
If the supports exclude from being outside and being inside or vice versa, then the canonical relation of the composed operator does not include .
We first consider . To do this, we partition further. Let be a smooth cutoff function supported in and equal to one on and let , , and where the characteristic functions and are functions of . Note that, for each fixed and functions of , , , . All these functions are smooth and . This allows us to divide up each ( into the sum of three operators where has symbol equal to the symbol of but multiplied by , has symbol equal to the symbol of but multiplied by , and has symbol equal to the symbol of but multiplied by . Note that .
We now analyze the composition using this partition of . Consider the composition . Because both operators are supported in above the axis, the canonical relation of this composition cannot intersect (see (ii)). Because they are both supported outside , it cannot intersect (since associates points inside only with points outside and vice versa by (iii)). So this shows .
Note that we use the transverse intersection calculus to show and each of the other operators in this lemma are regular FIO.
Now, we consider . Note that is supported in in and is supported in . Therefore, the canonical relation of the composition can include neither nor by (i), (ii). Furthermore, because they are both supported outside , it does not contain by (iii). Therefore, is smoothing.
Next, we consider . The argument is similar to the case , but this canonical relation is contained in .
This shows that is a sum of operators in .
The proof that follows using the same arguments but the roles of and are switched because has support in below the -axis and below .
Now we consider . Because the support in of is to the left of and the support of is inside, the canonical relation of cannot intersect (since there are no points in that canonical relation by the support condition and (i) and it cannot intersect for a similar reason by (ii). So .
A similar argument using symmetry of support of and in the axis shows that .
Putting these together, we see that .
The proof that is similar but here we use the partition of : , and . In a similar way, .
Thus, .
Now we consider . Here we partition , into three operators with smooth symbols as we did for :
- •
* will have support in for fixed in the union of circles *
* (outside of ),*
- •
* will have support in for fixed in the union of circles (surrounding ) and be equal to the symbol of in *
, and
- •
* will have support in for fixed in the union of circles *
* (inside ).*
The proof follows similar arguments as for and it shows .
Finally, we consider . By symmetry of the conditions (i), (ii), (iii), we justify and are in . So, the only composition to consider is , and by analyzing all combinations, we see . This finishes the proof.
We are left with the analysis of the compositions and . This is the content of the next theorem:
Theorem 6.13**.**
Let and be as above. Then
- (a)
. 2. (b)
.
Proof 6.14**.**
Consider the intersections of . We have that intersects cleanly in codimension ; intersects cleanly in codimension and intersects cleanly in codimension .
For part (a) we decompose . Now, we consider the compositions that for . Using (i), (ii), and (iii), we have that . Then, using a proof similar to the one for Theorem 2.2, we see that .
Arguments using (i), (ii), and (iii) show that the cross terms , , , and are in and and are smoothing.
Now, we consider part (b) and the operator .
We recall that and are disjoint, thus is a two sided fold. Next we use [26] to get that , and that is a two sided fold.
We use the decomposition (6.19) where is supported in the upper part of and is supported in the lower part of . Note that the support in of and are disjoint.
Then using Theorem 3.10 we have that
[TABLE]
Consider the operator defined as follows:
[TABLE]
This is a Fourier integral operator of order [math] and it is easy to check its canonical relation is . Let . We have . Note that , and (as well as ) intersects transversally. Using [22, Proposition 4.1], this implies that . Since and we have
Similarly, we show that
[TABLE]
This concludes the proof of Statement (2) of Theorem 2.6.
6.4 Spotlighting
This is equivalent to assuming the scatterer has support in either the open half-plane or . In this case, does not appear in the analysis.
Theorem 6.15**.**
Let be as in (2.2) of order . Assume the amplitude of is nonzero only on a subset of either the upper half-plane or the lower half plane and bounded away from the axis. Then , where is given by (6.1).
Proof 6.16**.**
*We assume (the other case is similar), is empty and and have fold singularities along as proved in Proposition 6.2. Thus where is a two-sided fold. Using the results in Felea [10] and Nolan [29], we have that . *
In this case, does contribute to the added singularities and this is discussed in Remark 2.7.
7 Acknowledgements
All authors thank The American Institute of Mathematics (AIM) for the SQuaREs (Structured Quartet Research Ensembles) award, which enabled their research collaboration, and for the hospitality during the authors’ visits to AIM in 2011, 2012, and 2013. Most of the results in this paper were obtained during the last two visits. Support by the Institut Mittag-Leffler (Djursholm, Sweden) is gratefully acknowledged by Krishnan, Nolan, and Quinto.
The authors thank the referees for their thorough, thoughtful, and insightful comments that made the article clearer.
Ambartsoumian was supported in part by NSF grants DMS 1109417 and DMS 1616564, and by Simons Foundation grant 360357.
Felea was supported in part by Simons Foundation grant 209850.
Krishnan was supported in part by NSF grants DMS 1109417 and DMS 1616564. He also benefited from the support of Airbus Corporate Foundation Chair grant titled “Mathematics of Complex Systems” established at TIFR CAM and TIFR ICTS, Bangalore, India.
Quinto was partially supported by NSF grants DMS 1311558 and DMS 1712207, and a fellowship from the Otto Mønsteds Fond during fall 2016 at the Danish Technical University as well from the Tufts University Faculty Research Awards Committee.
Appendix A Proofs of iterated regularity for ()
In this section, we prove that each of the given in (5.15) is a sum of products of derivatives of and smooth functions. This will finish the proof that .
A.1 Expression for
We will use the same prolate spheroidal coordinates (5.11) with foci and to solve for and . We have
[TABLE]
We have
[TABLE]
Therefore in (A.1), it is enough to express in terms of and . We obtain:
[TABLE]
Combining the first and the third term, and second and the fourth term above and then simplifying, we get
[TABLE]
where indicates multiplication with the expression in the previous line. Now denote
[TABLE]
Note that since , . Therefore we have
[TABLE]
Now using this expression for the difference of cosines in (A.1), we are done.
A.2 Expression for
We have
[TABLE]
Since , we have that the last term in (A.2) is [math].
Now we can write
Since and can be expressed in terms of and as above, we are done.
A.3 Expression for
We have
[TABLE]
In prolate spheroidal coordinates, we have
[TABLE]
As before we get the terms and which can be expressed in terms of and .
A.4 Expression for
We have
and
Thus
[TABLE]
Now
[TABLE]
Next we use again the expressions for and as before and for we use (A.2).
A.5 Expression for
We have
[TABLE]
Now we are in a similar situation as in the previous case.
A.6 Expression for
We have
[TABLE]
This part is complete as well.
Appendix B Expressions for and
Recall that is defined in (2.13) as
[TABLE]
Recall that is defined by (6.5) and for is nonempty and not trivial.
We assume in this section that the cutoff function in Section 2 is chosen so it is zero for .
The radius and the -coordinate of the center of circle are
[TABLE]
Let denote the -coordinate of the center of ellipses in the plane. Then the distance between and can be written as
[TABLE]
For a fixed let and denote correspondingly the smallest and the largest values of , for which the ellipsoid intersects . Notice, that since the normal to an ellipse at a point bisects the angle from the to the foci, the condition implies that our ellipses on the ground can not intersect the circle at more than two points. Here denotes the right focus of the ellipse on the ground. Figure 5 shows the setup for , where the ellipsoid passes through , the closest to point of . The setup for is similar, with the ellipsoid passing through , which is the farthest from point of .
A straightforward computation shows that
[TABLE]
where .
The reference list from the paper itself. Each links out to its DOI / PubMed record.
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