Research On Adaptive Sea Clutter Suppression Algorithm For Sky-Wave Radar

The carrier wave of sky-wave over-the-horizon radar(OTHR) is a high frequency(HF) wave and the ionosphere can reflect the HF electromagnetic wave. As a result, the beam of OTHR is turned back to detect targets by looking down. It has a distant and wide detectiong range, can effectively detect distant targets, low-altitude targets and stealth targets. OTHR has an important military application for remote warning. The unique detection way of the OTHR brings it many advantages, but also makes it faces a large of challenges, one of which is the suppression of sea clutter. The first-order sea clutter produced by resonance between the high-frequency electromagnetic wave and the ocean surface wave and the high-order sea clutter caused by instability of the ionosphere and disturbance of the ocean sueface currents can mask the targets which have a low Doppler frequency, resulting in low speed target detection difficulty.By using the OTHR measured data, this dissertation studies the adaptive sea clutter suppression algorithm. The main work is as follows.1、Firstly, a variety of sea clutter suppression algorithms are studied. First of all, the sea clutter suppression algorithm based on ESN is studied. This adaptive algorithm is one of the methods based on neural network. The methods based on neural network are typical representatives of which model the sea clutter as a chaotic signal. And then the algorithm is validated and analyzed by processing the measured data. Finally, this dissertation puts forward an adaptive sea clutter suppression method based on optimal filter for practical engineering application. The fast Fourier transform(FFT) is firstly applied on the radar data in slow time domain so as to form multiple frequency cells, then an optimal filter is designed to keep the signal in the frequency cell under test invariant while minimizing the signals in other frequency cells. Compared with the method based on ESN, the measured data processing results show that the proposed algorithm can detect the slow speed target of which the SCNR is lower.2、Secondly, in view of the possible existence of the high order matrix inverse for the optimal filter, this dissertation proposes an adaptive and iterative sea clutter suppression algorithm based on RLS so as to reduce computational complexity and enhance the stability. The measured data processing results demonstrate that the algorithm can suppress the sea clutter effectively. In addition, through theoretical derivation, the optimal filter can be modeled as a dynamic system described by a state transfer equation and a measurement equation, then an adaptive and iterative sea clutter suppression algorithm based on EKF is put forward. By processing the measured data the validity of the algorithm is verified and the detection performance for the slow target whose SCNR is low is tested.3、Thirdly, this dissertation proposes an adaptive sea clutter suppression algorithm based on APES for the situation that the reference range cell is little or no. The validity of the algorithm is verified by processing the measured data. Additionally, this dissertation combines the APES method to above mentioned algorithms to further enhance the detection performance.