Extension of the Geometric Mean Constant False Alarm Rate Detector to Multiple Pulses
Graham V. Weinberg

TL;DR
This paper extends the geometric mean CFAR detector to handle multiple pulses, providing a method to maintain a constant false alarm rate in clutter modeled by Pareto distributions.
Contribution
It introduces a novel approach to achieve full CFAR detection with multiple pulses using gamma distribution properties, advancing radar detection techniques.
Findings
Derived false alarm probability for multiple pulses
Extended to full CFAR detector case
Applicable to Pareto-distributed clutter
Abstract
The development of sliding window detection processes, based upon a single cell under test, and operating in clutter modelled by a Pareto distribution, has been examined extensively. This includes the construction of decision rules with the complete constant false alarm rate property. However, the case where there are multiple pulses available has only been examined in the partial constant false alarm rate scenario. This paper outlines in the latter case how the probability of false alarm can be produced, for a geometric mean detector, using properties of gamma distributions. The extension of this result, to the full constant false alarm rate detector case, is then presented.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsRadar Systems and Signal Processing · Distributed Sensor Networks and Detection Algorithms · Cognitive Radio Networks and Spectrum Sensing
