@inproceedings{7e8c44e3faf94159a049760a1056b728,
title = "Bayesian Cramer-Rao Bound for multiple targets tracking in MIMO radar",
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.",
keywords = "BCRB, MIMO radar, Multiple targets tracking",
author = "Phuoc Vu and Haimovich, {Alexander M.} and Braham Himed",
year = "2017",
month = jun,
day = "7",
doi = "10.1109/RADAR.2017.7944338",
language = "English (US)",
series = "2017 IEEE Radar Conference, RadarConf 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "938--942",
booktitle = "2017 IEEE Radar Conference, RadarConf 2017",
address = "United States",
note = "2017 IEEE Radar Conference, RadarConf 2017 ; Conference date: 08-05-2017 Through 12-05-2017",
}