| Satellite navigation system can provide full-time,all-weather and high-precision navigation,positioning and timing services,is an important national infrastructure.But in the process of its operation,the receiving device is very vulnerable to some external environmental interference or human interference,and suppression interference has been a serious threat to the reliability of satellite navigation system in practical applications due to its low cost and easy access characteristics.At this time,it is very beneficial to maintain a safe and orderly electromagnetic environment of satellite navigation system if we can accurately estimate the direction of the incoming wave of interference source and then use anti-interference means to block the source of interference damage,or even direct directional investigation of the source of interference.Therefore,it is important to study the interference source estimation methods under suppressed interference of satellite navigation systems.The interference source monitoring device is very vulnerable to the incoming signal with multiple harmonics or multipath interference in the complex urban environment,such as urban building canyons,elevated forest,complex terrain,etc.These coherent interference sources easily lead to inaccurate measurement information,large errors,resulting in poor decisionmaking,the inability to effectively carry out the location of the interference source,which is a waste of human and material resources.Therefore,it is important to study a signal DOA sensing algorithm with robustness,low complexity and good performance to cope with the harsh communication environment and intentional and unintentional interference.For the above these issues,this paper conducts research in the following areas:(1)A study for the classical DOA estimation algorithm is carried out.First,several array models are briefly introduced,including the uniform array model and the sparse array model;then specific simulations are conducted for two classical DOA estimation methods: the MUSIC algorithm and the ESPRIT algorithm.Based on the uniform linear array,the estimation accuracy of the two algorithms is discussed and compared,and it is concluded that the estimated RMSE value of MUSIC algorithm is smaller.Further,several control groups are set up to investigate the estimation performance of the MUSIC algorithm under different conditions,and the effects of the corresponding parameters on the estimation accuracy are derived.(2)The estimation algorithm of coherent interference sources is studied.After the theoretical analysis of the coherent signal characteristics and the classical decoherence methods,the simulation of the FSS and the FBSS algorithms is carried out to analyze and compare the decoherence performance and estimation accuracy of the two algorithms,and also to verify the maximum number of interference sources that can be estimated by the two algorithms.It is concluded that the RMSE value of the forward-backward spatial smoothing algorithm is smaller,and the forward-backward spatial smoothing algorithm can reduce the array aperture loss and have higher array freedom compared with the forward spatial smoothing algorithm.(3)Research on decoherence algorithms based on sparse arrays is carried out.By comparing and analyzing two sparse array research methods,namely,defuzzification and virtual arrays,it is concluded that virtual arrays can make full use of the advantages of large aperture of sparse arrays,and the localization resolution and estimation accuracy are higher.The estimation of incoherent and coherent interference sources is carried out using the augmented coprime array and nested array respectively,and finally the conclusion is summed up that the estimated RMSE value of sparse array is smaller than that of uniform line array,among which the estimated RMSE value of augmented coprime array is the smallest,there is no error spectral peak,and the spectral peak is sharp enough to ensure that the estimated angle is closer to the real target position. |
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