Maritime Moving Target Detection Using Multiframe Recursion Association in GNSS-Based Passive Radar

Given the global coverage provided by the global navigation satellite system (GNSS) signals, the GNSS-based passive radar shows potential in maritime moving target detection. However, the limited power budget of the navigation satellite seriously obstructs the detection performance. To address the problem, this article puts forward a target detection method based on multiframe recursion association (MFRA), which resorts to increasing the signal-to-noise ratio (SNR) by integrating the target returns over successive signal frames. A scoring function with target state as the variable is utilized to gauge the integration performance. As a new signal frame is passed in, the state relation between the two adjacent frames is determined by associating the new frame with the previous scoring function, followed by the scoring function updating according to the associated data. The processing is recursively performed, so that the multiframe integration can be achieved based on the estimated state trajectory, and the target detection is accomplished on the final scoring function. This method is applicable to targets with complex motion, as well as small targets that require a very long dwell time. Compared with the existing methods, the proposed method is more effective and can provide a better target detection performance. The effectiveness and superiority of this method are verified against the maritime experimental data of BeiDou and Galileo satellites as opportunistic transmitters.