A Hybrid Integration and Parameter Estimation Algorithm Based on KTSMF for Sea-Surface Moving Targets Using Space-Based Bistatic Passive Radar

A space-based bistatic passive radar system, typically utilizing a satellite as the illuminator of opportunity and ground or aerial platforms as receivers, offers significant advantages for wide-area maritime surveillance, robust anti-jamming performance, and superior survivability. However, due to the limited transmit power and significant path loss over long-range propagation, the signal-to-noise ratio (SNR) of sea-surface targets is extremely low. To achieve effective detection and estimation, long-time integration is required, which can unfortunately induce severe range cell migration (RCM) and Doppler frequency migration (DFM) effects, resulting in integration gain loss and degraded detection performance. This article proposes a hybrid integration and parameter estimation algorithm based on the keystone transform and segmented matched filtering (KTSMF), which partitions the echoes into multiple frames and combines the keystone transform with segmented matched filters for integration. It not only effectively eliminates RCM and DFM effects in both intra-frame and inter-frame processing but also addresses Doppler ambiguity and Doppler aliasing effects, which enables a generalized processing capability for slow-moving, fast-moving, and highly maneuverable targets. Simulation results and analysis demonstrate that the proposed method achieves superior detection performance and parameter estimation accuracy compared to existing algorithms.