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.