| With the advantages of over-the-horizon detection,all-day,all-weather,and anti-stealth,high-frequency surface wave radar(HFSWR)plays a vital role in maritime economic development and national defense.Conventional HFSWR arrays are large in scale.Their lengths generally range from hundreds of meters to more than a kilometer,requiring many scarce shoreline resources.Therefore,miniaturization of radar systems has become an important development direction for HFSWR.Small efficient receiving array and signal processing technology is one of the most widely used miniaturization methods.In this paper,the system is called small array high frequency ground wave radar(SAHFSWR).SA-HFSWR is generally about one hundred meters in size;hence,it can save a large amount of land area and construction costs while improving mobility simultaneously.SA-HFSWR systems have many benefits,but they also pose significant challenges in the research on signal processing methods.The high-frequency(HF)band electromagnetic environment is highly complex,including various interferences and clutters.Among them,ionospheric clutter is extremely common and complex,seriously affecting the performance of HF band radar systems.Ionospheric clutter is formed by the signals reflected through the atmospheric ionosphere.It has strong energy,nonstationary,and various types.The ionospheric clutter entering the radar system will seriously impact the target signal and intensify the difficulty of target detection.Therefore,ionospheric clutter suppression has always been crucial in signal processing.For SA-HFSWR,however,owing to the reduced size of the array,the spatial beams of the array are severely broadened,and the angular resolution is reduced by several times,making it difficult to separate the target and clutter components.Moreover,the increased correlation of the spatial response of the array will significantly affect the accuracy of the clutter information selection in the space domain in clutter suppression,resulting in a severe reduction in the performance of commonly used clutter suppression methods.Therefore,this paper analyzes and investigates the problem of ionospheric clutter suppression in small-array HFSWR systems,and the main work and achievements are as follows.1.In order to fully understand the properties of ionospheric clutter in small array,common ionospheric clutter is divided into sheet,mass,block and bar ionospheric clutter according to space-time characteristics.Based on a characteristic subspace space-time characteristic analysis method,measured data are used to analyze the space-time characteristics of targets and four kinds of ionospheric clutter in conventional and small arrays.According to their space-time characteristics,the sheet,mass and block ionospheric clutter with more distance units but less correlation is classified as nonstationary clutter.The bar ionospheric clutter that is stationary in certain distance but has very few samples to choose from is classified as small sample ionospheric clutter.On this basis,through theoretical derivation and simulation experiments,it is proved that the smaller the array aperture is,the stronger the correlation of the array spatial response is,and the correlation is much higher than that of ionospheric clutter,which leads to the serious degradation of the performance of general clutter training sample selection suppression methods in the spatial domain.2.Aiming at the problems of nonstationary ionospheric clutter in SAHFSWR,such as low sample correlation and high spatial response correlation,which lead to inaccurate clutter information extraction,this paper proposes a space-time adaptive clutter suppression(HBF-JDL)algorithm based on hyperbeamforming.It is verified that HBF-JDL can improve the distance correlation of nonstationary clutter and improve the accuracy of sample information,which can make up for the problem of beam broadening caused by small array.The clutter suppression results of measured data show that HBF-JDL can effectively suppress nonstationary ionospheric clutter under the condition of small array.3.A sparse representation space-time adaptive clutter suppression(DMSRSTAP)algorithm based on clutter model is proposed to solve the problems of low resolution,beam broadening and few snapshots of small array ionospheric clutter in SA-HFSWR.Compared with other sparse representation methods,DMSR-STAP does not require sparsity as a prior knowledge,and can improve resolution to make clutter component estimation more accurate.Moreover,it can be used in the condition of a single training sample.The clutter suppression results of measured data show that DMSR-STAP can suppress small sample ionospheric clutter under the condition of small array.4.On the basis of two proposed methods of space-time clutter suppression,it is analyzed that space-time adaptive processing(STAP)can affect the observation of the angle and Doppler information.In addition,the beam of SAHFSWR is too wide,which makes this problem more serious.To solve the problem that STAP can affect the target information,a space-time response correction algorithm based on two-dimensional beam-reshaping(BR)is proposed in this paper.BR algorithm can suppress the clutter component and ensure the integrity of the main-lobe,so as to protect the angle and Doppler frequency information of the target from being affected.The effectiveness of BR algorithm is verified by simulation and measured data.In this paper,HBF-JDL and DMSR-STAP algorithms are proposed respectively on the basis of the nonstationary and small sample characteristics of ionospheric clutter in small array.All the proposed methods have been verified by the measured data,which can suppress the ionospheric clutter in nonstationary and small sample effectively,and greatly improve the signal-toclutter ratio.On this basis,the influence of STAP on target information is analyzed,and BR algorithm is proposed to protect target angle and Doppler information,so as to improve the accuracy of target information after clutter suppression. |
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