Backward Projection Positioning for Airborne Moving Targets Using a Distributed Passive Radar System

In modern electronic reconnaissance, passive localization plays a crucial role in target positioning and tracking in complex electromagnetic environments due to its inherent concealment capability. However, conventional multistation localization methods often suffer from large estimation errors and limited robustness in dynamic scenarios because of their reliance on multi-snapshot measurements. To address these limitations, this paper extends the backward projection positioning (BPP) method to distributed radar systems for airborne target localization and tracking. By performing backward projection on spatial-domain Doppler history, a cost function involving azimuth angle, elevation angle, and slant range is constructed to generate high-resolution localization images. The distributed radar system forms a physical aperture, enabling high-precision and robust tracking performance. To reduce ambiguities caused by sparse deployment, an optimization strategy based on a genetic algorithm is proposed for radar node placement. The performance of the proposed method is further evaluated using a linear distributed configuration. Simulation results demonstrate that the proposed approach achieves approximately an order-of-magnitude improvement in localization accuracy compared with conventional DOA-based methods.