An Approximate Maximum Likelihood Algorithm for Target Localization in Multistatic Passive Radar

This paper addresses the problem of target localization using Bistatic range (BR) measurements in a distributed multistatic passive radar system. The range based positioning technique employs multiple transmitter receiver pairs, which provide separate BR measurements. Based on the Maximum likelihood (ML) function, an efficient algebraic Approximate maximum likelihood (AML) algorithm for single target localization is proposed. The closed-form AML solution has neither initial condition requirements nor convergence difficulty. Simulations are included to compare its performance to that of the Cramer-Rao lower bound (CRLB) and the Two-step Weighted least squares (TS-WLS) algorithm. The proposed method is shown to be able to achieve the CRLB accuracy under Gaussian measurement noise. It is more robust to noise than the TS-WLS method, and presents relative insensitivity to target-sensor geometry.