Xu Rongqing

Robust Adaptive Beamforming Based on Generalized Sidelobe Cancellation

If the desired signal is present in training snapshots, conventional adaptive beamformer is quite sensitive even to slight mismatches between the presumed and actual signal steering vectors (spatial signatures). Such mismatches can occur as a result of environmental nonstationarities, look direction errors, imperfect array calibration, distorted antenna shape, as well as distortions caused by near-far mismatch, source spreading, and local scattering. It induces signal cancellation in the traditional adaptive beamforming and severely degrades the beamforming performance. In this paper, we develop a new approach to robust GSC (generalized sidelobe cancellation)-based adaptive beamforming in the presence of an arbitrary unknown signal steering vector mismatch. The proposed method involves two steps: the first step is to use a nulling broadened blocking matrix to exclude the desired signal component from the auxiliary channels, and the second step is to obtain optimal weight by sidelobe cancellation method. Finally, simulation results demonstrate that the proposed structure can considerably enhance the overall performance. It has greatly improved robustness as compared with existing adaptive beamforming-algorithms, and enjoys simple implementation

Robust interference cancellation method of high frequency surface wave radar

High frequency interference typically exhibits a time-varying or non-stationary spatial structure for the propagation of ionospheric. Adaptive interference cancellation methods are known to degrade in this case. In this paper, a new robust interference cancellation method is proposed to confront the non-stationary radio frequency (RF) interference in high frequency surface wave radar (HFSWR) circumstance. By modifying receiving matrix in the permissible range to get the optimization signal to interference-plus-noise ratio in the worst-case, we involve minimization to a quadratic constraint. Reformulate the problem as a standard second-order cone program, and get the coefficient of adaptive beamforming. The good performance of the new method was confirmed by the simulation and experimental data of experimental high frequency surface wave radar.

A novel array calibration method based on spatial correlation matrix for HFSWR

This paper addresses a new method based on spatial correlation matrix to calibrate uniform linear array for HF Surface Wave Radar (HFSWR). Strong point echoes, such as target, clutter, transponder and so on, which are highly spatial correlated, can be used to structure spatial correlation matrix. And the matrix contains angles of echoes and phase errors information. In this paper, we use two-dimension FFT to estimate angle of strong point echo, and then obtain the corrections. Computer simulations and experimental results are conducted to show the validity of the new method.

Ionospheric clutter mitigation with knowledge aided pre-whiten in High Frequency Surface Wave Radar

Ionospheric clutter has proven to be the greatest impediment in high frequency surface wave radar (HFSWR). It influences most range bins, all Doppler bins and beams. Knowledge-aided ionospheric clutter mitigation using multiple coherent processing interval (CPI) data was described. The approach is based on estimation of the near vertical incidence clutter by past CPI data to provide improved knowledge of clutter statistics. Knowledge aided pre-whitening filter was used to cancel both near vertical incidence clutter and the range wrap clutter. Experimental results demonstrate that the algorithm is able to suppress the ionospheric clutter whilst preserving the desired characteristics of the target echoes.

Robust least squares method for interference cancellation in high frequency surface wave radar

External skywave interference from natural or man-made sources typically masks the entire range-Doppler search space in high frequency surface wave radar (HFSWR), a robust least squares interference cancellation algorithm based on the dual-polar receiver was proposed in this paper. We modify the sample of horizontal auxiliary channel, and get the best performance of interference cancellation in the worst case error circumstance under the limit of maximum error bound while not decreasing the angular response of the target signal. Converting the convex optimization question to simple one dimension search, we get the effective method to settle the optimal weight coefficient. The experimental result shows that the proposed method is very effective.

Ionosphere interference suppression for HFSWR using L-shape array

In this paper, using L-shape array for ionosphere interference suppression for high frequency surface wave radar is proposed. The linear receive array, which is used by conventional HFSWR systems, is replaced by an L-shape array, which is effectively a combination of two linear arrays arranged perpendicular to each other. This gives the radar additional resolving power in elevation angles, which is not available in conventional HFSWR systems with one-dimensional linear arrays, so the ionosphere interferences with high elevation angles can be better suppressed. Measured data from real HFSWR is used in experiments to compare the ionosphere interference suppression performance of conventional linear array and the L-shape array. The result shows great performance improvement by using the L-shape array.

Linearly Constrained Coherent Sidelobe Canceller for Ionosphere Interference Suppression for HFSWR

In this paper, a linearly constrained coherent sidelobe canceller for high frequency surface wave radar is presented to improve the interference cancellation performance. To overcome the target-canceling problem of traditional coherent sidelobe cancellation algorithm, a linear constrain is applied to the adaptive weight vector of auxiliary array in order to keep this adaptive weight vector within a subspace that is orthogonal to the main beam, so the target echoes in the main beam are well preserved. Measured data from real high frequency surface wave radar system is used to compare the performance of the new algorithm and the traditional one, and the results show that the new algorithm is clearly superior to the traditional algorithm.

Robust Least Squares Method for Sporadic E Ionospheric Clutter Mitigation in High Frequency Surface Wave Radar

The unwanted ionospheric clutter has proved to be the greatest impediment to achieving consistently good performance for high-frequency surface wave radar (HFSWR), A robust least squares algorithm based on the dual-polar receiver was proposed in this paper for sporadic E ionospheric clutter mitigation. The horizontal auxiliary channel was modified to get the best performance of clutter mitigation in the worst case error circumstance under the limit of maximum error bound. The optimal weight coefficient was solved efficiently by converting the min-max problem into a minimization problem. The experimental result shows the effectiveness of the proposed method

Array pattern synthesis for optimum directivity with constrained array efficiency and specified sidelobe level

In order to optimize the directivity with the controlled array efficiency and desired sidelobe level, a new pattern synthesis method is presented in this paper. This method can be applied to arbitrary array geometries. The array efficiency is restricted to be higher than a given value by incorporating a quadratic inequality constraint on the weight vector, and the desired sidelobe level is achieved by implementing linear constraints through iteration. By optimizing the array directivity subject to array efficiency and sidelobe constraints, the highest possible directivity with controlled array efficiency and desired sidelobe level can be achieved. The simulation results of different arrays show that the proposed method is very effective and flexible.

Adaptive interference cancellation synthesized SMI and eigenspace-based method for HF surface wave radar

High frequency (HF) interference typically exhibits a time-varying or non-stationary spatial structure for the propagation through ionosphere. Adaptive interference cancellation methods are known to degrade in this case. In this paper, a new approach that effectively suppresses the non-stationary interference without degrading target visibility is presented for high frequency surface wave radar (HFSWR) circumstance. The proposed method synthesizes the sample matrix inverse (SM) and eigenspace-based beamformer, which maintains the beam pattern to keep the target response as well as cancels the interference mostly. A computationally efficient algorithm based on Lagrange multiplier methodology is proposed to compute the beamformer weights. Its excellent performance was confirmed by the experiment data of a real system.