Shipborne or airborne maritime surveillance radars at scan mode work at a complex scene consisting of land, sea, and islands. Sea-land segmentation provides a two-class classification of sea clutter versus ground clutter to the surveillance scene as a precondition of adaptive target detection. It is a difficult problem because only a few coherent pulses are available at scan mode. Moreover, due to moving radar platforms and wide dynamic range of ground and sea clutter in power, average amplitude, Doppler offset, and initial phase of radar returns vector fail to distinguish sea clutter and ground clutter. In this paper, a similarity measure of two radar returns vectors, which is invariant to amplitude, Doppler offset, and initial phase, is constructed, which is closely relevant to the Doppler bandwidth of a returns vector. Based on the similarity measure, a K-nearest neighbor (KNN) classifier is proposed to yield a pixel-level sea-land segmentation of the scene. Further, the morphological filtering is operated on the pixel-level segmentation to obtain a region-level segmentation. Moreover, the discrete Fréchet distances of the main boundaries in successive scan periods are used to assess segmentation quality. The proposed method is verified by measured data from an airborne radar and an island -based radar. The results show that it behaves better than the methods using thresholding phase linearity degree of radar returns and the support vector machine (SVM), and back propagation neural network (BPNN) in a three-dimensional feature space.

Effectiveness verification of weapon equipment and the selection of stealth material are inseparable from target radar cross-section (RCS) measurement. For RCS characteristic analysis of sea surface small targets, a fishing vessel was measured using a shore-based ultra-high-frequency (UHF) band radar. In this article, a full program of RCS measurement and characteristic analysis is presented, and three strategies are adopted to guarantee its high precision. For this, a scheme was designed for RCS dynamic measurement, along with the construction of a two-stage median filter to improve target positioning precision, and an RCS estimation procedure with sea clutter removal is elaborated upon, which increases RCS accuracy. Note that the test range satisfies the far-field criterion, and the multipath effect is modified by external calibration in our data. The measurement results reveal that the RCS level of the sea surface small target is sensitive to the aspect angle and wave height at a low grazing angle, but the RCS fluctuation characteristic is not. Therefore, the aspect angle and wave condition must be considered for sea surface small target detection, classification, or identification.