Research On Clutter Suppression And Target Detection Of Sky-wave Over-the-horizon Radar

Sky-wave over-the-horizon(OTH)radar uses the ionosphere to reflect high-frequency electromagnetic waves,so that it can detect the targets out of sight.As an early warning radar with special system,it has an important strategic and tactical position in military.After years of development,sky-wave OTH radar has been equipped with considerable detection capability and is widely used.However,the complex electromagnetic propagation environment and detection background still make the radar face many challenges in application.This dissertation conducts research focusing on some technical problems that restrict the sky-wave OTH radar in practical engineering,including the improvement of efficiency for multi-target detection,the suppression of radio frequency interference(RFI)and sea clutter,and etc.Several feasible solutions are proposed for those typical problems,trying to overcome the existing shortcomings and improving the detection performance of sky-wave OTH radar.The main contributions and innovations of this dissertation are concluded as follows.(1)Simultaneous detection of air and sea targets in different directions based on signal recoveryThe current sky-wave OTH radar is equipped with phased array and therefore needs to alternately illuminate and detect targets in different directions.The long-term coherent accumulation of sea targets in one direction will greatly increase the time interval of air target detection in the other direction,which is not conducive to continuous tracking the high-speed air targets.In response to this problem,this dissertation proposes a timeinterpolated scheme for simultaneously detecting air and sea targets in different directions,which inserts multiple air target detections within the beam dwell time of the sea target,with a data recovery algorithm developed to complete the missing sea surface echo.The proposed scheme can develop a stable trajectory for air targets,while ensuring the effective detection of sea targets.(2)The RFI suppression in spatial-domain combining image texture featuresThe texture features in the field of image analysis are introduced into radar signal processing.More specifically,the Tamura coarseness is considered as an index to evaluate the strength(or suppression degree)of RFI.The coarseness evaluates the intensity of RFI based on the gray scale of the Range-Doppler graph,without relying on prior knowledge or interference characteristic estimation.With the guidance of coarseness,a method to determine the optimal diagonal loading factor for beamforming is proposed,which improves the suppression performance of RFI existing in the spatial sidelobes.(3)The RFI suppression time-domain with distance sidelobe constraintTo suppress the RFI exists in the spatial mainlobe,this dissertation respectively considers transmitting waveform design and receiving filter design.The proposed waveform design problem,which assumes that the receiving filter is the optimal interference suppression filter,attempts to controls the theoretical output signal to interference plus noise ratio(SINR),as well as the cross-correlation sidelobes between the designed waveform and the receiving filter.And an iterative algorithm within the framework of alternating direction method of multipliers(ADMM)is developed to address the proposed waveform design problem.Besides,two filter design problems are proposed,which maximize the theoretical output SINR,but respectively control the integrated sidelobes level and peak sidelobes level between the designed filter and the transmitting waveform.The proposed filter design problems can be transformed into standard second order cone programming(SCOP)and therefore can be solved efficiently.(4)The sea clutter suppression based on spectrum cognitionSea clutter is the main obstacle for sky-wave OTH radar to detect low-speed sea targets.In a real environment,the sea clutter spectrum is rich in variation and has a certain degree of non-uniformity.This makes it difficult to accurately estimate clutter characteristics with finite reference samples,which further affects the performance of clutter suppression methods.This dissertation attempts to improve the estimation accuracy of clutter characteristics with clutter spectrum cognition technology,thereby improving the sea clutter suppression performance with the framework of optimal filter.Firstly,a sea clutter suppression method combining the prior knowledge and clutter spectrum model is studied.Next,a clutter suppression method based on sparse dictionary learning is proposed,which performs long-term offline learning on radar echo data to establish a clutter dictionary and then use it to estimate sea clutter characteristics.The above two methods can improve the estimation accuracy of the clutter covariance matrix,therefore effectively improve the clutter suppression performance and target detection capability of OTH radar in the background of non-ideal sea clutter.(5)Modeling and suppression of multi-hop sea clutterMulti-hop propagation can make the clutter spectrum superimpose,expanding the spectral range of the sea clutter and increasing the impact of sea clutter on target detection.Based on the principle of propagation and superposition of multi-hop clutter,this dissertation proposes a models for multi-hop clutter,and attempts to suppress it by transmitting special waveforms The two multi-hop clutter suppression schemes introduced in this article are based on the sequential orthogonal waveforms and the discontinuous waveforms,respectively.The proposed schemes can effectively separate or suppress multi-hop clutter while retaining the main signal component in regular one-hop echo.The above mentioned schemes are proposed based on the actual engineering requirements of sky-wave OTH radar,and are compatible with the hardware equipment of current radar.Their effectiveness and availability for tackling the engineering issues have been verified by actual data or simulation experiments.