Ionospheric Clutter Mitigation Research Articles

Fast‐time STAP based on BSS for heterogeneous ionospheric clutter mitigation in HFSWR

High-frequency surface-wave radar (HFSWR) is widely used in vessel and aircraft detection, sea-state sensing and wind-field mapping. Target detection suffers from the ionospheric clutter, which is reflected by the ionosphere. Adaptive beamforming (ABF) has been used for ionospheric clutter mitigation. However, the performance of ABF is limited by the heterogeneous ionospheric clutter and degrees of freedom (DOF) of the antennas array. In order to improve the performance, here, the one-dimensional ABF is expanded to two-dimensional fast-time space–time adaptive processing (STAP), which combines beam and range domains to obtain more DOFs than that in the ABF. In addition, the blind sources separation (BSS) method is also used to improve the spatial covariance matrix estimation accuracy of STAP in the heterogeneous ionospheric clutter background. The simulation and real data results demonstrate the effectiveness of the proposed BSS-STAP method in HFSWR.

A Two-Step Method for Ionospheric Clutter Mitigation for HFSWR With Two-Dimensional Dual-Polarized Received Array

For high-frequency surface wave radar (HFSWR), the unwanted radio wave originated from the ionosphere is commonly called ionospheric clutter. Its presence seriously affects the performance of the HFSWR and extremely degrades the radar capability to detect target over long distances. To solve this problem, this paper proposes a two-step method for ionospheric clutter mitigation with two-dimensional dual-polarized received array. The proposed method first performs parameter estimation of the clutter, and then gives a polarimetric-adaptive-based oblique projection filter (PAB-OPF) to suppress the clutter. In the first step, due to the fact that vertically and horizontally polarized antennas are at different array elements for reducing mutual coupling and hardware cost, 2-D DOAs are estimated to give phase compensation for polarization phase delay estimation. In the second step, the PAB-OPF is proposed to eliminate phase inconsistency by matching different polarization phase delays for different vertically polarized antennas, and then to suppress the clutter efficiently in space-polarization domain. Error analysis and computational complexity of the proposed method are derived. Experimental results are shown to illustrate the superiority of the proposed method for ionospheric clutter suppression.

New BSS‐based ABF for heterogeneous ionospheric clutter mitigation in HFSWR

Ionospheric clutter is detrimental to target detection in high-frequency surface-wave radar (HFSWR). Adaptive beamforming (ABF) has been adopted to suppress the ionospheric clutter in recent years. Unfortunately, the performance of ABF degrades due to the heterogeneity of the ionospheric clutter. In this study, a new approach is proposed to suppress the ionospheric clutter. A novel heterogeneous ionospheric clutter model based on the mixture of mutually independent ionospheric clutter sources is established. The blind source separation (BSS) approach is used to separate the clutter sources first. Then the separated components are exploited to estimate the spatial covariance matrix (SCM) of the cell under test. The SCM estimation based on BSS is more accurate than the classical sample matrix inversion method under the heterogeneous ionospheric clutter. Therefore, the ABF performance improves due to the better SCM estimation. The simulation and real data results demonstrated the effectiveness of the new BSS-based ABF method in HFSWR. The signal-to-clutter-plus-noise ratio of the new method improved compared with the traditional ABF based on the SMI method. The new method can help to detect targets under the heterogeneous ionospheric clutter. It may also be a promising methodology in other ABF applications.

Modeling and Simulation Challenges in Wide Ocean Area Surveillance

Wide ocean area surveillance using high frequency surface wave radar(s) is discussed in this paper. Theoretical and practical issues and problems are reviewed. Modeling and simulation challenges such as ionospheric clutter mitigation, ocean clutter, surface wave propagation over multi-mixed paths, EM scattering and RCS characteristics of surface and air targets, and signal detection and tracking are presented.

Ionospheric clutter mitigation for high-frequency surface-wave radar using two-dimensional array and beam space processing

Ionospheric clutter mitigation for high-frequency surface-wave radar using a two-dimensional array and beam space processing is presented here. The new antenna system with both azimuth and elevation angle resolving power is capable of exploiting the difference in both azimuth and elevation angles between wanted target echoes and unwanted ionospheric clutters, giving it an advantage over conventional one-dimensional linear arrays. In addition, the beam space processing can effectively preserve target echo energy during interference cancellation. Measured data from a real high-frequency surface-wave radar system is used to evaluate the performance of the new method.

Ionospheric clutter mitigation using one-dimensional or two-dimensional wavelet processing

Ionospheric clutter mitigation is an important issue for high-frequency surface wave radar (HFSWR) signal processing. Clutter results from a sky wave propagation mode, which is backscattered by ionospheric ionisation irregularities. The random behaviour and the high strength of clutter signals can strongly limit the HFSWR detection capabilities. Here, an ionospheric clutter mitigation processing using wavelets is described. This new approach is founded on the ability of wavelets to separate signals having different variation scales or different directions of variations. The results obtained on real clutter signals with simulated targets are reported. Using the proposed method, one can expect, at mid-latitude, an improvement of the target-to-clutter ratio of 20-30-dB.

Robust ionospheric clutter mitigation method for high frequency surface wave radar

This paper analyzes the characteristics of ionospheric clutter, which has proven to be the greatest impediment in high frequency surface wave radar (HFSWR). Ionospheric clutter influences most range bins, all Doppler bins and beams, and exhibits a high directivity. A robust adaptive side-lobe cancellation algorithm based on orthogonal auxiliary beams, which use the difference beams to estimate the ionospheric clutter information, is introduced to suppress the ionospheric clutter. Training data was selected by excluding the sea clutter and probable target unit; and diagonal loading was added to enhance the robustness of the algorithm. Experimental results demonstrate that the algorithm is able to suppress the ionospheric clutter whilst preserving the desired characteristics of the target echoes and is suitable for practical implementation.