Target Localization Accuracy Gain in MIMO Radar Based Systems

TL;DR

This paper analyzes target localization accuracy in MIMO radar systems, deriving bounds and estimators, and demonstrating how sensor placement and system parameters influence localization precision.

Contribution

It develops the CRLB for MIMO radar localization, compares coherent and non-coherent processing, and introduces the BLUE for improved target position estimation.

Findings

CRLB inversely proportional to bandwidth (non-coherent)

CRLB inversely proportional to carrier frequency (coherent)

Sensor placement optimization reduces localization error

Abstract

This paper presents an analysis of target localization accuracy, attainable by the use of MIMO (Multiple-Input Multiple-Output) radar systems, configured with multiple transmit and receive sensors, widely distributed over a given area. The Cramer-Rao lower bound (CRLB) for target localization accuracy is developed for both coherent and non-coherent processing. Coherent processing requires a common phase reference for all transmit and receive sensors. The CRLB is shown to be inversely proportional to the signal effective bandwidth in the non-coherent case, but is approximately inversely proportional to the carrier frequency in the coherent case. We further prove that optimization over the sensors' positions lowers the CRLB by a factor equal to the product of the number of transmitting and receiving sensors. The best linear unbiased estimator (BLUE) is derived for the MIMO target localization problem. The BLUE's utility is in providing a closed form localization estimate that facilitates the analysis of the relations between sensors locations, target location, and localization accuracy. Geometric dilution of precision (GDOP) contours are used to map the relative performance accuracy for a given layout of radars over a given geographic area.