The traditional particle filter-track before detection (PF-TBD) algorithm with fixed number of particles suffers from the large-scale and complex environment of high frequency surface wave radar (HFSWR). To solve this problem, an integrated method of target detection and tracking based on PF-TBD algorithm with adaptive particle filter is proposed. In the proposed method, combined with the target broadening characteristics in HFSWR spectrum, the particle adaptive sampling strategy is set by using the information contained in the particle weight of surface distributive target. Through the target tracking results of the measured data and the comparison with the synchronous automatic identification system (AIS) information, it shows that the proposed method can improve the overall tracking performance of multiple targets in complex environments such as low signal to noise ratio (SNR) and fast maneuvering targets.