Study On Clutter Estimation And Suppression Methods In Airborne Passive Bistatic Radar

The airborne passive bistatic radar system performs coherent processing by receiving the direct wave signal of the non-cooperative emission source and the echo signal of the monitoring area,so as to realize the functions of radar target detection,tracking,imaging and recognition.Because it has the advantages of both traditional passive bistatic radar and active airborne radar,the research on airborne passive bistatic radar has great application potential and practical significance.The clutter in the echo signal received by the airborne passive bistatic radar is no longer distributed near zero Doppler,but is coupled with the time series and receiving angle to form more complex ground clutter.Therefore,the traditional passive bistatic radar The clutter suppression algorithm will no longer apply.The SpaceTime Adaptive Processing(STAP)algorithm based on airborne platform can effectively solve the problem of Doppler broadening,especially the SR-STAP algorithm can realize accurate estimation of the clutter power spectrum under the condition of small samples,but it is still faced with the problem of applying to the airborne passive bistatic radar system.Some challenges mainly include: due to the multi-snapshot estimation amplitude mismatch caused by random signal segmentation,the clutter estimation is inaccurate;under the condition of the illuminators motion,the clutter estimation has the off-grid effects caused by the geometric complexity of the clutter;Under the condition that the reference signal is contaminated,the multipath signal in the reference channel is matched can cause the clutter spectrum broadened and increase the blind area of target detection;the demand of more equivalent pulse numbers leads to the failure of the sparse solution,and the dimension of the covariance matrix will be increased.Therefore,based on the system model and the analysis of clutter characteristics,the method of the clutter estimation and suppression which is suitable for airborne passive bistatic radar system is proposed in this paper.The detailed research work of the manuscript is arranged as follows.1.The clutter estimation and suppression technology of airborne passive bistatic radar under the condition of signal segmentation loss is studied.Since the signal of the airborne passive bistatic radar is the continuous wave signa,in order to adapt to the space-time adaptive processing,it is necessary to manually segment the signal into the equivalent pulses with a duty cycle of 100%,and this segmentation method with the inconsistency of amplitude will cause the influence of base mismatch in the multi-snapshot joint sparse estimation of the clutter spectrum,resulting in the decrease performance of the clutter power spectrum and affecting the clutter suppression performance of the range unit to be detected.In order to solve this problem,this paper proposes the STAP algorithm based on variational time-correlated sparse Bayesian.While estimating the sparse clutter power spectrum,this algorithm uses the compensation matrix to learn the time and amplitude structure characteristics of the multi-snapshot training unit of the data,smoothing the influence of the dictionary base mismatch,and at the same time in order to deal with the problems of large amount of data in the airborne passive bistatic radar system,the matrix inversion operation is transformed into the simple multiplication and addition operations.The simulation shows that this algorithm can still realize the clutter estimation through the multi-block signal when the amplitude of the continuous wave signal is serious,which has better performance advantages and robustness than the existing multi-shot sparse STAP method.2.The clutter estimation and suppression technology of airborne passive bistatic radar under the condition of impure reference signal is studied.When the reference antenna of the airborne passive bistatic radar receives the direct wave signal from the illuminators,it also receives the multipath signal reflected by the strong point on the ground,resulting in the contaminated reference signal.With the impure reference signal,when performing STAP processing on the airborne external radiation source radar,the multipath of the reference signal is matched with the space-time clutter in the echo,resulting in the space-time clutter expands,and the target self-cancellation phenomenon can increase the blind area of target detection.In order to solve this problem,this paper proposes the covariance-sparse Bayesian STAP method based on the sparsity of the location of the clutter spectrum in space.In this paper,the sparse model of clutter spectrum is analyzed firstly when the reference signal multipath exists,and then the Doppler dimensional slice data is extracted form range Doppler processing through multiple receiving units as the training samples,and then use covariance sparse Bayesian estimation to treat the training samples near the detection unit,solve the spatial position and quantity of multipath,and finally obtain the pure space-time clutter spectrum only by solving the multipath information in the multipath sparse model.The simulation shows that the algorithm can accurately estimate and suppress the space-time clutter when the reference signal is polluted by the multipath signals,and eliminates the influence of the detection blind area caused by the multipath signals.3.The clutter estimation and suppression technology of airborne passive bistatic radar under the condition of sparse off-grid is studied.When the transmitting source is in motion,the moving speed between the transmitting source and the receiving platform presents a new corresponding relationship,which will lead to a corresponding change in the coupling relationship of space-time clutter.On the spectrum of clutter,the space-time relationship of clutter is no longer distributed in a diagonal line,but appears as a more complex geometric relationship.The complex shape of the clutter spectrum increases the difficulty of clutter estimation and affects the clutter suppression performance of airborne passive bistatic radar by STAP.Furthermore,there is a strong distance dependence in this space-to-space geometry.This distance dependence is reflected in the change of the configuration geometric relationship of the range units to be detected other than a certain number of range units,resulting in the changing space-time coupling relationship of clutter.Therefore,the distance dependence brings two problems: the first one is that the number of independent and identically distributed training samples which can be used to estimate the distance unit to be detected is reduced,and the other is that the presence of singular value samples in the samples used for training will affect the correct clutter estimation.Therefore,the distance dependence of this configuration further increases the difficulty of clutter suppression for airborne passive bistatic radar.In order to solve this problem,this paper proposes the clutter estimation algorithm based on rootfinding off-grid sparse Bayesian.This algorithm establishes the space-time clutter dictionary base as a dynamically adjustable dictionary base,solves the iterative optimization polynomial through the EM algorithm,realizes the optimization of the atom position of the dictionary base at the position where the clutter is off-grid,and then uses the optimized dictionary,thereby realizing off-grid clutter estimation.The experimental simulations show that this algorithm can complete clutter spectrum estimation based on a dictionary with a larger grid width,and the performance of off-grid clutter suppression is higher than that of existing algorithms.At the same time,in order to further optimize the performance of the algorithm,this paper proposes a sample selection algorithm by adding artificial pseudo-random noise,which overcomes the influence of errors on clutter estimation under the condition of singular value samples.4.A structured dimensionality reduction STAP algorithm suitable for airborne passive bistatic radar is studied.When the airborne passive bistatic radar needs to divide more equivalent pulses,the number of independent and identically distributed samples is also limited.At the same time,the dimension will increase when using SR-STAP for clutter suppression under this condition The estimation error and convergence caused by the increase of the dictionary base dimension,the increase in the amount of computation caused by the inversion of the clutter covariance matrix,and the problem of easy introduction of interference signal segments,this paper proposes an array element-pulse selection method based on tabu search dimensionality reduction STAP algorithm.This algorithm takes the spatiotemporal spectral correlation sparsity of the distance unit to be detected as the cost function,and realizes data dimensionality reduction processing through the tabu search algorithm to optimize the array element-pulse.This algorithm not only reduces the inversion of the airborne passive bistatic radar clutter suppression matrix dimension,which improves the real-time performance in actual engineering;at the same time,the optimization of array element-pulse pairs can also realize the shielding of pulse signal segments with strong interference in each array element,which improves the anti-interference ability of the clutter suppression algorithm.The simulation results show that this algorithm can achieve better array element-pulse pair selection ability than the existing algorithm,and at the same time improve the shielding ability of the interference signal segment.