Abstract: Compact high-frequency surface wave radar (HFSWR) exhibits low measurement accuracy for target parameters. Traditional plot-to-track association methods solely rely on inaccurate instantaneous kinematic parameters, which are prone to erroneous associations when tracking closely spaced targets. To address this issue, this paper proposes a plot-to-track association method based on multi-frame Range-Doppler (R-D) spectrum echo amplitude distribution, which employs the joint matching of kinematic parameters and echo amplitude distribution to improve association accuracy. First, for each established track, the Sobel operator is used to calculate the gradient amplitudes of target echoes in each frame of the R-D spectrum, constructing a gradient amplitude sequence. After smoothing processing, kernel density estimation (KDE) is applied to establish the continuous probability density function (PDF) of the track’s gradient amplitude sequence. Next, an association gate is established centered on the predicted state of the target. The gradient amplitudes of candidate plots within the association gate at the current time step are computed, and the instantaneous PDF for each candidate plot is derived using the kernel density estimation method. Finally, the Kullback-Leibler (KL) divergence is utilized to measure the similarity between the instantaneous PDF of candidate plots and the continuous PDF of the current track. The candidate plot with the minimum KL divergence is selected for track update. Experimental verification of plot-to-track association was carried out by utilizing the measured maritime target data obtained from Compact HFSWR. The results indicate that, in comparison with the nearest neighbor data association method, the target tracking time achieved by this method has increased by 28.2%, with an average extension of 14.3 minutes, which improves the continuity of target tracking.