Exploiting Target Location Distribution in MIMO Radar: PCRB vs. PSBP for Transmit Beampattern Design

TL;DR

This paper explores how prior knowledge of target location distribution can improve MIMO radar transmit beampattern design by comparing PCRB-based and PSBP-based methods through theoretical analysis and simulations.

Contribution

It introduces two novel methods for exploiting target location priors in MIMO radar, including a PCRB-based approach and a PSBP-based approach, with algorithms for their design.

Findings

PCRB-based method provides a lower bound on DoA estimation error.

PSBP-based method enhances beampattern focusing using prior distribution.

Numerical results show the proposed methods outperform traditional designs.

Abstract

This paper investigates the issue of how to exploit prior target location distribution for multiple input multiple output (MIMO) radar transmit beampattern design. We consider a MIMO radar aiming to estimate the random angular location parameters of a point target, whose prior distribution information can be exploited by the radar. First, we establish the models of the MIMO radar system and the target location distribution. Based on the considered models, we propose the first category of target location distribution exploitation methods by analyzing the radar direction-of-angle (DoA) estimation performance and deriving a general form of posterior Cramer-Rao bound (PCRB) as the lower bound of the mean square error of DoA estimation. Following this, to investigate the potential of leveraging prior information from two distinct perspectives, thereby providing deeper insights into the estimation process, we proposed the second category of target location distribution exploitation methods by introducing a novel radar metric, probability scaled beampattern (PSBP), from the perspective of radar beampattern. To compare the two methods, we formulate the PCRB and PSBP oriented radar transmit beampattern design problems and propose corresponding low complexity and convergence-guaranteed algorithms to tackle them. Finally, numerical simulations are conducted in different scenarios to provide a comprehensive evaluation and comparison of the radar performance.