Ship detection at the sea surface is important for improving human marine activities. Most existing ship detection methods for high-frequency surface wave radar (HFSWR) are based on peak and constant false alarm rate (CFAR) detection and require a coherent integration time (CIT) of several minutes. However, in such a long period, the target may not be stationary. To account for the nonstationary property, a time-frequency analysis (TFA)-based ship detection and direction finding (DF) method is proposed for HFSWR. Target ridges on the TF representation (TFR) of the echo data are detected first. Next, array snapshots are formed by sampling the extracted ridges and are used to estimate the direction of arrival (DOA). The processing results of the radar data collected at Dongshan, Fujian Province, China, show that the proposed method outperforms the CFAR method with both increased detection rates and decreased DF errors, especially under relatively low signal-to-noise ratio (SNR) scenarios.

In this paper, the application of ultra-high frequency (UHF) radar for ship target detection over river is investigated for the first time. Due to the wide beam width of antenna, the ship detection of the UHF radar suffers from the broaden river clutters scattering from water waves. In addition, due to the high resolution, the ship echoes are seriously extended in both range and Doppler dimensions, which is different from the traditional point target signal. Extended target detection in strong river clutter is applied in this paper. Conventional constant false alarm rate (CFAR) detector is limited in this situation, which is applicable to the point target detection in clutter free background. An improved cell-averaging (CA)-CFAR method is proposed based on a joint estimation of threshold in range, Doppler and time serials of range-Doppler (R-D) spectra. Based on the time stationarity of clutter, this three-dimensional (3D) CA-CFAR combines several R-D spectra collected in continuous time to estimate the clutter threshold. The effectiveness of this improved method is validated using both simulated and field data.

Detecting and tracking small drones is significant for security requirements, but is challenging since small drones typically have a low radar cross section (RCS), small size and hovering ability. Polarimetric analysis of returned radio wave is of great significance in detection and track of small drones. In this letter, the polarimetric analysis based on RCS and micro- Doppler signature of small drone rotor blade is firstly studied in VHF/UHF band. Both the simulated and measured RCS results confirm that the Horizontal-Horizontal (H-H) polarization is preferred for drone detection in low altitude angles at this frequency band. Moreover, the Method of Moments (MoM), a rigorous numerical method based on integral equation, is implemented to simulate the micro-Doppler signature generated by the rotating blade in VHF/UHF band. The results show that it is feasible to obtain the rotating speed from the micro-Doppler measurement, which is also verified by the experiment.

Crossed-loop/monopole antenna has been widely used in high frequency ground-wave radar for ocean surface remote sensing owing to its compact size. The multiple signal classification (MUSIC) algorithm is commonly adopted to achieve a favorable angular resolution for this broad beam antenna. However, the direction of arrival (DOA) estimation is always troubled by the frequently occurring distortion of antenna pattern. Previous studies are mainly focused on the calibration by using the actual pattern or other assistant algorithms. In this paper, theoretical analysis is made to illustrate the reason for pattern distortion, which draws a conclusion that the distortion is essentially due to the different influence of environmental obstacles upon the electric field part and magnetic field part. This also implies that there is nearly no distortion between the two loops, which is validated by three different experiments. Based on this conclusion, the DOA estimation performance of MUSIC algorithm is studied by creating a numerical relationship associating the estimation error with distortion level. Furthermore, a new method using ideal pattern is proposed to improve the estimation performance by removing the amplitude information of monopole and relying on the crossed-loop processing. Both simulation and experimental results are given to prove its validity.

High-frequency (HF) radars are routinely used for remotely sensing ocean surface currents. However, the performance of the most widely used direction-finding HF radar is degraded due to the effect of the inevitable deviations of actual antenna pattern on the direction of arrival (DOA) estimation. In this paper, we quantify the DOA estimation error resulting from the deviation of the actual antenna pattern from the ideal one. Theoretical analysis and field experiment results suggest that the ratio of the deviations for the two loops dominates the DOA estimation error. Thus, eliminating the effect of the antenna pattern deviations on DOA estimation error is transformed into eliminating the effect of this ratio. From this, a calibration method based on the time-averaged local spatial coverage rate (TLSCR) is proposed to reduce the effect of the antenna pattern deviations on current extraction, which uses the ideal antenna pattern to estimate the DOA of the echoes. To validate this proposed calibration method, we assess the radar-derived radial velocities by comparing with in situ observations. The comparison results indicate that the proposed TLSCR calibration method can effectively reduce the DOA estimation error and improve the performance of the direction-finding HF radar in current observation.

High-frequency (HF) ground wave radar is an important tool for sea state measurement and low-altitude target detection. Dense radio frequency interference (RFI) in the HF band inhibits the extraction of sea state parameters and degrades the performance of radar. Though many interference suppression methods based on large arrays have been proposed, most of them are weak to deal with the interference in small-aperture radar. In this letter, a spatial subspace method is proposed to suppress RFI, which uses two crossed-loop/monopole antennas to construct interference subspace at the reserved range bins and projects the echoes onto its orthogonal subspace at the interested range bins. The processed results of measured data from OSMAR-SD verify the high performance of this algorithm for dense RFI suppression. Apart from that, the data utilization ratio and the accuracy of estimating wave height are both improved significantly after the RFI suppression.