Bayesian Cramer-Rao Bound for multiple targets tracking in MIMO radar
Document Type
Conference Proceeding
Publication Date
6-7-2017
Abstract
Theoretical performance bounds are developed for tracking multiple targets in multiple-input multiple-output (MIMO) radar systems with widely distributed antennas. In previous work, we proposed a direct tracker, which eliminates the need for explicit association of observations to tracks, thus improving tracking performance compared to conventional trackers that estimate time delays and Doppler. In this paper, we develop the Bayesian Cramer Rao Bound (BCRB) for the performance of direct tracking of multiple targets in a distributed MIMO radar. A first-order approximation linearizes the observations with respect to the targets state vector. The BCRB is developed for Swerling Type 1 targets. The theoretical performance bounds are applied to demonstrate the performance of direct trackers versus conventional trackers.
Identifier
85021430295 (Scopus)
ISBN
[9781467388238]
Publication Title
2017 IEEE Radar Conference Radarconf 2017
External Full Text Location
https://doi.org/10.1109/RADAR.2017.7944338
First Page
0938
Last Page
0942
Recommended Citation
Vu, Phuoc; Haimovich, Alexander M.; and Himed, Braham, "Bayesian Cramer-Rao Bound for multiple targets tracking in MIMO radar" (2017). Faculty Publications. 9525.
https://digitalcommons.njit.edu/fac_pubs/9525
