A Coherent TBD Algorithm for Remote Sensing of Weak Targets Using GNSS Reflected Signals

Global navigation satellite system (GNSS)reflected signals have been widely used in remote sensing applications. To overcome the low-power budget of GNSS reflected signals, traditional detection strategies involve extending the coherent processing interval (CPI) of a single frame or employing the multiframe detection (MFD) method in which the noncoherent integration is used to accumulate echo energy. In this article, a novel coherent dynamic-programming-based track-before-detect (C-DP-TBD) algorithm is proposed to search and compensate for the interframe phase shift to improve the performance of weak target detection using GNSS reflected signals. The proposed algorithm is included in the two-stage MFD and follows a range-Doppler (RD) map generator. The RD map generator extracts the RD map candidate list for a specific data frame, which contains all of its variants based on the potential phase value and location shifts of the target peak in the RD domain relative to a designated reference frame. Subsequently, the C-DP-TBD processor coherently integrates each variant in this list with the reference frame, removes implausible variants, and selects the most reliable one by comparing all resulting peak signal-to-noise ratios with a preset threshold. The confirmation of the target track in the RD domain is finally achieved by extracting the position of the target peak from every available frame. Compared with traditional motion target detection methods with long CPI and DP-TBD methods, the performance superiority of the proposed algorithm is demonstrated by both simulation and experimental results in which a ferry was employed as a moving target.