Weibo Deng

Multi-carrier frequency MIMO HF radar using convex optimization beamforming

In order to enhance HF radar angle resolution, and overcome target RCS scintillations, we adopt the transmitting and receiving antennas sparse deployment under bistatic pattern, the element intervals far less than range from the target to transmitters and receiver, the transmitters emit multi-carrier frequencies. In this paper, we apply CVX theory to solve the optimal weights of each element at different frequency, take advantage of multi-carrier frequency signal phase changing offset the side lobe each other. The beampattern has better angle resolution, and achieves lower side lobe. In the end, we analyze that the different frequency echo amplitude and phase impact side lobe and direction errors

Knowledge-Based Generalized Side-Lobe Canceller for Ionospheric Clutter Suppression in HFSWR

High frequency surface wave radar (HFSWR) has been successfully developed for early warning and remote sensing. However, the ionospheric clutter is a difficult challenge that can make HFSWR system inefficient. The Generalized Side-lobe Canceller (GSC) has been proved to be an effective algorithm for clutter suppression in theory, but it suffers from the performance degradation for some non-ideal conditions in practice. The most intolerable shortcoming is the signal to noise ratio (SNR) loss caused by the residual signal in the secondary data. In this paper, a knowledge-based GSC (KB-GSC) method has been proposed via an adaptive single notch filter design to reject the residual signal for reducing the SNR loss. The feasibility and availability has been demonstrated by measured data.

A new adaptive anti-interference algorithm for HF signal processing based on uniform circular array

High-frequency signals are generally instable and susceptible to various external interferences in a complex electromagnetic environment. In order to solve this problem, this paper presents a new approach based on a uniform circular antenna array. With this approach we can maximize the SNR of the output signal and suppress the interferences to an acceptable level at the same time. Besides, this new approach can adaptively process the unknown signals and interferences received by the antenna array while not need any extra information about them in advance. Based on this approach, a new shortwave communication system is designed. Finally, both the simulation data and the real data from the communication system validate the effectiveness and practicality of this approach.

Main-Lobe Cancellation of the Space Spread Clutter for Target Detection in HFSWR

High-frequency surface wave radar (HFSWR) has been successfully developed for early warning, especially for monitoring the moving vessels. However, it can be blinded by space spread clutter (SSC) which can cover a wide looking directions, such as sea clutter and ionospheric clutter in HFSWR. A few methods have made great efforts for SSC cancellation, but these efforts make no sense for the clutter in main-lobe that is a long-standing problem. In this paper, a spread clutter estimated canceller (SCEC) based on single notch space filter has been developed for SSC cancellation to cancel the clutter in the main-lobe with the idea of estimating the SSC in the looking direction through the ones in side-lobes. The feasibility of the idea has been described and demonstrated by the results of simulations and measured data which make great significance for target detection and tracking.

Application of Compressive Sensing to anlge-Doppler processing without Knowledge-Aid

The Compressive Sensing (CS) is a mean to solve simultaneously detection and estimation problems. It has been applied mainly in source Direction of Arrival (DOA) estimation problems where the amount of data to be handled is reasonably small. This is not the case in Knowledge-Aid Space Time Adaptive Processing (KA-STAP) which is widely used for ground clutter suppression and targets detection in airborne radar for the extremely large amount of data. We develop an efficient algorithm which can provide two supervisors: one is that target can be separated from ground clutter in the condition of small amount of training data; the other one is that the number of sources is not necessary.

Modified Space-Time Adaptive Processing with first-order bragg lines kept in HFSWR

High Frequency Surface Wave Radar (HFSWR) can perform the functions of ocean environment monitoring, target detection, and target tracking over the horizon. However, its system performance is always limited by the severe ionospheric clutter environment. The ionospheric clutter generally can cover a few Doppler units and a few angle units. Consequently, Bragg lines masked by the ionospheric clutter are difficult to be recognized. In this paper, we exploit the Space-Time Adaptive Processing method to the HFSWR signal processing, and propose a strategy of choosing Protected Doppler Units to improve the Joint Domain Localised (JDL) algorithm. The results with measured data show that the modified JDL algorithm is effective and the Bragg lines masked by ionospheric can be recognized more easily.