Direct Localization With Direct-Path Interference for Reference Channel-Free Distributed Passive Radars

The unknown signals from non-cooperative illuminators of opportunity (IOs) and direct-path interference (DPI) make it challenging to achieve high-precision target localization for passive radars. Traditional dual-channel solutions heavily depend on high-quality reference channel (RC) observations, leading to increased hardware cost, computational overhead, and strict operational requirements. In this paper, a cost-effective signal model is proposed, which captures both noise and DPI-contaminated target echoes in an RC-free setting. Based on this model, a high-dimensional coupled parameter estimation problem is formulated, and a direct position estimator using an iterative optimization strategy with coordinate descent is developed to reduce computational complexity. The estimator iteratively subtracts the estimated DPI from the received signals and then updates the target position estimate. We also derive the Cramér–Rao lower bound (CRLB) to provide an accurate theoretical benchmark for the estimation accuracy. Numerical analysis is conducted to validate the effectiveness and robustness of the proposed estimator. The results demonstrate that the proposed estimator achieves a localization accuracy close to the CRLB and reveal that, although excessive DPI will result in performance degradation for target localization, moderate DPI can, in fact, allow to improve parameter estimation.