Study On Multi-mode Propagation And Clutter Suppression Of Mimo-oth Radar

The ionosphere is the primary transmission medium of the over-the-horizon radar(OTHR). And it has a hierarchical structure and the non-stationary characteristics. The hierarchical structure can lead to the generation of multi-mode propagation. Nonstationary characteristics will produce disturbance to the radar return signal, significant broadening of the spectrum of sea clutter. This extension makes that the Doppler spectrum of slow target is generally close to or overlaps with the sea clutter, causing difficulties to OTHR in detection on slow ship target. While multi-mode propagation makes the clutter extension more serious, making the slow ship detection more difficult.The OTHR which uses the multiple-input multiple-output(MIMO) technique(MIMO-OTH radar) could achieve non-causal adaptive transmitter beamforming. In the MIMO-OTH radar system, using spatial information, multi-mode clutter could be effectively suppressed. For multi-mode clutter suppression in MIMO-OTH radar, this paper focuses the research on the feasibility and effectiveness of the multi-mode clutter suppression algorithms based on blind source separation(BSS) and sparse reconstruction, the main research conclusions and results are as follows:(1) Based on analyzing the characteristics and properties of the ionosphere, the MIMO-OTH radar signal model in multi-mode propagation is derived. The signal model shows the feasibility of the multi-mode clutter suppression algorithm based on BSS. And the signal model provides theoretical support for using the sparse reconstruction method to suppress multi-mode clutter.(2) The second-order blind identification(SOBI) algorithm, the joint approximate diagonalisation of eigen-matrices(JADE) algorithm and the fast fixed point independent component analysis(Fast-ICA) algorithm in BSS are used for separating the received radar array signals. Simulation results verify the effectiveness of BSS in radar array signal processing. But the three blind separation algorithms cannot separate the correlated sources. For this case, the improved SOBI algorithm using spatial smoothing technique(SS-SOBI) is proposed. Simulation results show that the SS-SOBI algorithm can fully separate the correlated source signals and uncorrelated source signals. All the correlation coefficients between separated signals and source signals are more than 0.98. The SS-SOBI algorithm has good separation performance. That achieving multi-mode clutter suppression by separating the mixed signals using the BSS algorithms is an idea of clutter suppression in this paper. The excellent separation characteristics provide some guidance for proposing the multi-mode clutter suppression algorithm based on BSS.(3) The multi-mode clutter suppression algorithm based on SOBI is proposed. This algorithm does not need prior information of the target direction and does not need specific information about the target echo waveform. And it can effectively suppress the multi-mode clutter, retaining the information of clutter. In the MIMO system, SOBI is improved by the overall spatial smoothing method(SS-SOBI). Compared with the improvement in the phased array system, this improvement applies the same spatial smoothing technique, using the different smooth manner. And the multi-mode clutter suppression algorithm based on SS-SOBI is proposed. Compared with the algorithm based on SOBI, the algorithm based on SS-SOBI has better multi-mode clutter suppression performance, making signal-to-clutter ratio(SCR) been greatly improved, which is more conducive to target detection. In simulation, SCR is increased about 10 dB. In the multi-mode scenario that double targets with the same radial velocity, i.e., sources spectra have similarities, the algorithm based on SS-SOBI can separate all source signals. This further illustrates the effectiveness and robustness of the algorithm in multi-mode clutter suppression. Simulation results show that the algorithm still has good multi-mode clutter suppression performance in low signal-to-noise ratio(SNR). In addition, when multi-mode propagation and strong phase contamination coexist, this paper presents a new approach that separating the signals of the various propagation paths by BSS, firstly, and then correcting the ionospheric contamination for the signal which contains the target. Related simulations verify the correctness of the method.(4) In the MIMO-OTH radar system, the multi-mode clutter suppression algorithm based on the sparse signal reconstruction technique is proposed. And the principle of the algorithm is analyzed and a specific flow of this algorithm is given. The proposed algorithm transforms two-dimensional angle sparse search to one-dimensional angle search, reducing the computational complexity. The estimated DOD and DOA can be automatically paired. Simulation results show that the algorithm can accurately achieve the target location and the ideal multi-mode clutter suppression effect is obtained.