An Improved Track-Before-Detect Algorithm for GNSS-Based Bistatic Radar Target Detection

This paper studies the global navigation satellite system (GNSS) based passive bistatic radar (PBR) object detection. Passive detection using GNSS as an illuminator has many unique advantages, such as covert operations, global coverage and low power consumption. However, the low ground power density of GNSS signals is an important factor limiting its development. Therefore, long-time energy accumulation is required to improve the signal-to-noise ratio of the target. However, long-term integration is affected by Range Migration (RM) and Doppler Spread (DS) due to target motion. In this paper, we propose a new Moving Target Detect (MTD) algorithm based on the detection of weak targets, which propose an improved Dynamic Programming-Tracking Before Detection (DP-TBD) algorithm by processing the results of the pulse-segmented Radon-Fourier transform (SRFT). This algorithm is named SRFT-DP-TBD. The algorithm is named SRFT-DP-TBD, which realizes the detection and tracking of high maneuvering moving targets with low SNR. SRFT-DP-TBD processes the echo pulse in multiple segments, jointly searches for distance and velocity and accumulates them with intra-segment, then analyzes the intra-segment signal output results and performs phase compensation during inter-segment TBD to achieve coherent accumulation. In this way, intra-segment and inter-segment coherent accumulation is realized, which significantly improves the signal-to-noise ratio of the echo signal. Finally, an experiment using GPS L5 signal as an illumination source is carried out, and a moving car is successfully detected and the track of the car is obtained by the proposed algorithm.