Research On Classification And Suppression Of Ionospheric Clutter For High Frequency Surface-wave Radar

High Frequency Surface Wave Radar(HFSWR)is the important part of the coastal defense early warning system.The maintenance of the country’s territorial sea security and the real-time monitoring of the ocean sea state have been realized with the wide-area detection performance and full-time working characteristics of HFSWR.The echo signal is received by the radar after being modulated and reflected by the earth’s ionosphere owing to the high frequency working band of radar.The ionospheric clutter formed will lead to the increase of the missing alarm probability and false alarm probability of the target detection algorithm,which seriously restricts the detection performance of the high frequency surface wave radar.Therefore,effectively suppressing ionospheric clutter becomes the key technology of highfrequency radar.The time-varying,non-stationary and non-Gaussian characteristics of ionospheric clutter make it difficult to complete the overall suppression for a single spatial and space-time clutter suppression method.In addition,the traditional clutter suppression technology uses a generalized clutter model that lacks pertinence to the characteristics of ionospheric clutter,and the suppression performance of the algorithm is limited,resulting in ionospheric clutter on of the most difficult radar clutter to solve.To overcome the problem of ionospheric clutter suppression,the research on intelligent classification processing and suppression of ionospheric clutter is carried out.This thesis firstly introduces the cause and structure of ionospheric clutter and the action mechanism of ionosphere on high-frequency electromagnetic waves was illustrated,theoretically analyzing the complexity of ionospheric clutter.To further study the characteristics of ionospheric clutter,four methods for ionospheric clutter feature extraction are proposed,and the ionospheric clutter characteristics are analyzed from four aspects including directionality,spatial distribution homogeneity,space-time stationarity and wavelet domain characteristics,respectively.Combined with the experimental data,the characteristics of ionospheric clutter of different causes are summarized.This work pointed out the irrationality of ionospheric clutter classification based on the causes of ionospheric clutter or the morphology of ionospheric clutter in Range-Doppler spectrum in previous study.We also provide a theoretical basis for the subsequent research on the classification of ionospheric clutter types and the research on multi-type ionospheric clutter suppression methods.Based on the multi-dimensional feature analysis of ionospheric clutter and the statistical results of the measured data,a feature-based classification of ionospheric clutter types is carried out.According to the principle of maximizing sample density,five types of ionospheric clutter with typical characteristics are proposed and the causes and multi-dimensional characteristics of each clutter are analyzed and summarized.Taking these five typical ionospheric clutter types as supervised samples,a semi-supervised clustering-based ionospheric clutter classification method is proposed,which solves the problems of low classification accuracy of the current supervised classification method caused by difficulty of obtaining supervised samples,insufficient number of samples,and difficulty in selecting classification criteria.This method effectively reduces the dependence on the number of supervised samples,however,the spatial distribution of the classification results is prone to discretized.Aiming at this problem,by introducing the neighborhood space constraint,an ionospheric clutter classification method based on improved Fuzzy C-Means clustering is proposed,which can obtain classification results with practically physical significance and higher classification accuracy without reducing the classification performance.By which a new solution is provided to solve the ionospheric clutter classification problem.According to the classified five typical ionospheric clutter,different suppression methods for clutter characteristics are proposed.For the spatial characteristics of target-like clutter,energy-concentrated strong directional clutter and homogeneous spatial clutter,a single-notch auxiliary channel cancellation algorithm based on sample screening,an adaptive beamforming algorithm based on sparse reconstruction,and a generalized sidelobe cancellation algorithm based on clutter classification are proposed.The effectiveness and robustness of the algorithm is verified by simulation and measured data.For range-domain correlated clutter and comb-like ionospheric clutter,related literatures have given the Joint Domain Localized Processing based on Range Analyzed algorithm and the Wavelet Oblique Projection Filtering algorithm,respectively.The performance of the aforementioned algorithms is not the key point of this research,hence was not introduced in details.On the basis of ionospheric clutter classification and suppression methods of multi-type ionospheric clutter,an intelligent ionospheric clutter processing and suppression method that combines the two approaches was raised in this work.A smart matching between clutter types and algorithms for clutter suppression is designed and completed using greedy strategy.The method solves the over-reliance of clutter suppression capability on the operator’s experience in conventional classification processing and realizes the intelligent suppression of radar clutter by adaptively matching the ionospheric clutter type and the suppression algorithm.The effectiveness of the method is verified using the measured data,and the target tracking processing is realized by using multiple batches of clutter samples with accumulation periods.In this work,the concept of intelligent classification and suppression of ionospheric clutter is introduced.The ionospheric clutter is classified by the multidimensional features of clutter and different clutter suppression algorithms are proposed for different characteristics of ionospheric clutter.Finally,appropriate clutter suppression algorithms are matched with different types of ionospheric clutter to achieve their intelligent classification and suppression,effectively suppressing ionospheric clutter,improving target detection probability,which contains strong practicability.