Researches On Key Technologies Of Skywave Over-the-horizon Radar Ship Target Detection

The skywave over-the-horizon radar uses the skywave propagation mechanism to achieve over-the-horizon detection,with a detection range of 1,000 to 4,000 kilometers.In addition to the long detection distance,compared with the traditional system radar,the skywave over-the-horizon radar also has the characteristics of wide monitoring range,costeffective detection,good anti-stealth performance,strong anti-damage ability,and little influence by weather factors.With the rise of social and economic strength,the country’s demands for marine interests are also increasing day by day.How to protect the safety of people’s lives and property at sea,and maintain the integrity of national sovereignty over territorial sea,territory and airspace,has become the top priority.Because of its many advantages,the skywave over-the-horizon radar is receiving more and more attention and support from the country.Among the many tasks of skywave over-the-horizon radar,the task of sea surveillance is particularly prominent.And ship target detection is the focus and difficulty of skywave over-the-horizon radar’s sea surveillance mission.There are three main challenges in ship target detection by skywave over-the-horizon radar: first,the strong sea clutter that always exists will submerge the ship target signal;second,the nonstationary ionosphere will cause multi-mode and multi-path effects and phase pollution;third,external disturbance signals such as transient disturbance will raise the detection background noise level.This thesis focuses on how to improve the ship target detection performance of skywave over-the-horizon radar.Firstly,this thesis reviews the foundation of skywave over-the-horizon radar ship target detection,mainly including three parts: target signal processing and detection flow,external disturbance signals,and skywave propagation mechanism.On the basis of the ship target echo signal model,this thesis expounds the classical target detection process:pulse compression,beam forming,Doppler processing and threshold detection,and points out that the classical target signal processing and detection flow can be regarded as the optimal processing for target which assumes obeying the Swerling I model distribution and is only affected by white Gaussian noise.In the part of external disturbance signals,this thesis analyzes the impact of sea clutter,meteor clutter,lightning impulsive noise and radio frequency interference on ship target detection.In the part of skywave propagation mechanism,this thesis introduces the formation and structure of the ionosphere,and quantitatively analyzes the principle of multi-path effect through a simple ionosphere model.At the same time,combined with the measured data,the principle of multi-mode and phase pollution and its influence on ship target detection are qualitatively explained.Through the introduction and analysis of the above three parts,it lays a foundation for the subsequent chapters to propose corresponding solutions to specific problems.For the common transient interference suppression problem in skywave over-thehorizon radar,this thesis converts it into a slow-time domain impulsive noise suppression problem,and studies from known and unknown transient interference positions.When the transient interference locations are known,the interference suppression problem can be transformed into a missing data recovery problem.The traditional auto-regressive method cannot deal with the arbitrary position of missing data.This thesis proposes a solution from the perspective of maximum a posteriori estimation combined with the expectation-maximization algorithm.Considering the problem of computational complexity,this thesis further proposes a method based on least squares estimation and its modified method.The simulation results show that the improved method based on least squares estimation has better performance than the other two methods in terms of recovery performance and computational complexity.Furthermore,the measured data processing results show that the improved method has better recovery performance than the other types of missing data recovery methods at any position.When the transient disturbance location is unknown,this thesis proposes a solution from the perspective of robust smoothing,combined with the assumptions of the auto-regressive model for the useful signal.The method realizes the extraction of useful signals in a robust and smooth way,and on this basis,the position of transient interference can be determined,and the polluted data can be replaced by the estimated useful signal to complete the suppression of transient interference.The simulation results show that the proposed method is more accurate in estimating the transient interference position than the traditional method,and the measured data processing results show that the proposed method has better suppression effect than the other types of transient interference suppression methods.For the problem of ionospheric Doppler frequency shift correction,and array gain and phase error correction,this thesis firstly compares them mathematically,and finds that they are related but completely same in mathematical expression.Aiming at ionospheric Doppler shift correction,this thesis firstly uses the parametric spectrum estimation method to estimate the power spectrum of the slow-time data from different resolution units,and then detects the local peak points as the candidate first-order Bragg peaks.According to the Bragg resonance theorem,the first-order Bragg peak pair is determined from the candidate first-order Bragg peaks.Considering that the parametric spectrum estimation method has a certain error in the determination of the position of the first-order Bragg peak,and the target signal may also be mistakenly selected as the first-order Bragg peak,this thesis adopts the robust local weighted polynomial regression method to smooth the first-order Bragg peak pairs of different resolution units.When the center frequency of the first-order Bragg peak pair is estimated,the ionospheric Doppler shift correction can be realized.The experimental results show that the method proposed in this thesis has a more robust correction effect.Aiming at array gain and phase error correction,this thesis uses multiple groups of meteor trail clutter in different azimuths as the correction sources,and proposes the self-correction methods from the perspectives of the received signal covariance matrix Toeplitz structure and the covariance matrix eigen subspace.The simulation results show that when the gain and phase errors are small,the Toeplitz method has better correction effect,while when the gain and phase errors are large,the eigen subspace method is more robust.For the problem of robust sliding window constant false alarm ratio detection in the clutter region,this thesis first reviews the sliding window constant false alarm ratio(CFAR)detection principle,and points out that the traditional sliding window CFAR detection can be regarded as the combination of the estimation of the detection background disturbance level and the normalization of current detection unit data.At the same time,the study of invariance theory lays a theoretical foundation for the subsequent proof of the CFAR characteristics of the sliding window detector.Then,this thesis analyzes the reference window design,clutter area division and detection background distribution in the clutter area of skywave over-the-horizon radar,and discusses the peak detection preprocessing.Finally,according to the Weibull background,this thesis studies the design of sliding window CFAR detector from two perspectives: known and unknown shape parameters.For the situation where the shape parameters are known,this thesis proposes a weighted likelihood detector from the perspective of weighted likelihood estimation.Compared with the traditional detector,this detector has less computation under the same robustness,which is conducive to saving computer resources.However,it is not practical to assume that the shape parameters are known.And then this thesis proposes a robust explicit detector from the perspective of robust explicit parameter estimation.The detector has CFAR characteristics in the Weibull distribution background,which meets the actual engineering needs,and the simulation analysis shows that the detector has certain advantages compared with the traditional sliding window CFAR detector.Finally,the measured data processing results verify the reliability of the proposed detector.The research results of this thesis will help to improve the detection performance of skywave over-the-horizon radar ships,improve the working ability of skywave overthe-horizon radar in complex and non-stationary environments,and provide a feasible solution for the further development of the signal processing framework of skywave over-the-horizon radar.