| Vertically polarized high-frequency electromagnetic waves enable diffraction propagation along ocean surface,and have the characteristics of lower propagation attenuation and propagation along the curved earth surface.At the same time,the HF band is just in the resonance zone of the aircraft and the ship,and the wavelength of tens of meters will completely disable the existing stealth coating,which makes the HFSWR have a unique advantage of anti-stealth,anti-low-altitude penetration and over-the-horizon detection,etc.In the existing shore-based HF surface wave radar,the radar systems mostly use large array structures for target detection.As the ocean occupies an increasingly important status in the national economy,the large-scale occupation of scarce coastal resources has been the main factor limiting the development of surface wave radar.Hence,there is an urgent need to develop a small-aperture array HFSWR system used for target detection.Although the small-aperture HFSWR greatly reduces the footprint,it also poses a huge challenge for signal processing methods.This is because the system not only has the inherent problems of high-frequency radar such as fewer channel samples and coherent sources,but also the smaller array aperture can limit space resolution and estimation accuracy of the radar,reduce array freedom significantly.Hence,this paper focuses on the above-mentioned key technical issues and studies,and establishes the corresponding mathematical models to provide theoretical support for the research of signal processing methods of HFSWR.The main achievements of this paper are as follows: 1.Firstly,the signal processing flows of small-aperture HFSWR,such as distance processing,Doppler processing and azimuth processing are analyzed and deduced.The commonly used azimuth estimation methods in this system mainly include a digital beamforming method,a multiple signal classification method,and a rotation invariant subspace method.Then,under condition of small-aperture array,the space resolution and constraint factors of the above three methods are studied in depth.Finally,give a definition and model of the small-aperture HFSWR,derive the spatial distribution characteristics of the array itself,and the correctness of the result is verified by the simulation and measured data containing the radio,sea clutter and ionospheric clutter.2.When azimuth estimation is performed by small-aperture HFSWR,it is often affected by the problems of few array elements,insufficient space snapshots and coherent signals,which greatly limits the space resolution and estimation accuracy of the system to the targets.The paper proposed a DOA estimation method based on CS and polarization interpolation,through studying the problems of signal sparse representation,sensing matrix design and signal reconstruction in compressed sensing theory.The method firstly uses the orthogonal matching pursuit algorithm to estimate the number of sources and corresponding azimuth,which can solve the problem of few snapshots and coherence signal.Then,in order to reduce the estimated deviation when the targets are not on the grid,an off-grid optimization model based on continuous basis pursuit is established to obtain the accurate results of arbitrary azimuth targets.At last,in order to further improve the algorithm performance,a minimum mean square error function is deduced to correct the CBP estimation value.Simulation and measured results verify this method not only has high DOA estimation accuracy,but is robust to coherent signals and few snapshots.3.Since the mainlobe sidelobe ratio of the small-aperture array is relatively low,a strong interference on the sidelobe will severely limit the detection performance of the radar in the direction of the mainlobe.The robust adaptive beamforming(RAB)method can solve this question better,but the traditional RAB method is affected by the problem that coherent sources,random steering vector error and the sampling covariance matrix containing the desired signal.So that,its output performance is often far from the optimal value.To effectively deal with the above problem,a robust adaptive beamforming method based on joint estimation of interference-noise covariance matrix and array steering vector is proposed.This method first establishes a quadratic constraint model,which can make the interference-noise covariance matrix be as close as possible to the ideal covariance matrix.Then,for reducing the computational complexity,the analytical solution of the optimization problem is derived according to the CS and total least squares methods.Finally,based on the vector space projections approach,the accurate array steering vector estimation value can be acquired.The experimental results show that the output performance of the proposed algorithm approximates the optimal value,and can effectively suppress the measured radio interference.4.Radio and clutter that cover a certain number of range-Doppler-angle cells,have the major impacts on the detection performance of HFSWR system.Especially for a small-aperture array,the angle spectrums of radio and clutter suffer from severe broadening so that the targets more easily submerged in the broadened radio and clutter can be hardly detected.To tackle this issue,this paper proposes an algorithm for radio and clutter suppression to enable detection of the submerged targets,based on the spatial multi-beam and optimal sample selection.In this paper,based on the conclusion obtained in Chapter 2,a training sample acquisition method with auxiliary beam is proposed.And then,the criterions of the auxiliary beam and statistical sample are provided by analyzing the distance and Doppler correlation of the radio and clutter in the measured data.Finally,the radio and clutter can be suppressed by eliminating their energy.The simulation and measured results prove that the proposed method significantly increases the detection probability of the submerged targets,and has very strong robustness of the amplitude-phase error and pointing error. |
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