DOA Estimation Of Coherent Source And Array Calibration For Airborne

Array signal processing applications cover many fields such as communications,radar,medicine,positioning and aerospace,and are an important research content in the field of signal processing.The classic spatial spectrum estimation methods are all based on the ideal array structure.However,in the actual installation environment,especially under the airborne platform,the array will have various errors,such as amplitude and phase errors and mutual coupling errors.In the case of correction,the performance of the traditional spatial spectrum estimation method will be seriously deteriorated.Limited by the limited location space under the airborne platform,the array is small in scale and other equipment is installed around it,which will cause the array to work in a complex environment and have to consider multipath caused by reflection and external co-frequency interference signals.At the same time,because the airborne platform is in constant motion,it is also necessary to consider the conversion of coordinate positions,which adds difficulty to the array error correction.This article first introduces the basic mathematical model of the array signal,analyzes several of the most commonly used spatial spectrum estimation algorithms in engineering practice,and then compares the estimation performance of the two algorithms through simulation;for incident signals in complex environments In the case of coherent signal sources,the reason why the performance of eigen decomposition algorithms deteriorate in the presence of coherent sources is theoretically analyzed,and the influence of the presence of coherent sources on the performance of spatial spectrum estimation is discussed.Finally,Two classic decoherence algorithms are presented,and the performance of different decoherence methods is compared through simulation analysis.Secondly,in view of the spatial spectrum estimation problem under the error of the array structure,the mathematical model of the array error is established first,the influence of the array error on the spatial spectrum estimation result is studied,and then the classic singleradiator correction and Weiss-Friedander(WF)Self-correcting two array error correction methods.Aiming at the problem that the WF self-correction algorithm fails under the uniform linear array structure,a self-correction method based on least squares is introduced and improved.The improved self-correction algorithm can avoid the influence between the phase error and the source azimuth through the construction The cost function only needs to search and traverse the fuzzy coefficients in a small range to find the coefficient that minimizes the cost function,which can effectively reduce the array phase inconsistency error and the ambiguity between the angle estimation under the uniform linear array structure,and finally through simulation,Verify the effectiveness of the improved least squares selfcorrection algorithm.Finally,the implementation of the array error correction project in the airborne environment is introduced.First,the overall block diagram of the error correction is given,the key modules in the airborne hardware platform are introduced,and then the main software design process of the DSP is introduced..Through the use of interpolation and coordinate transformation,the measured data was corrected and analyzed by external radiation sources.Finally,an improved least squares self-calibration algorithm is used to analyze the measured data,and the performance close to the calibration result of the external radiation source is obtained.This means that the improved self-calibration algorithm can greatly reduce the engineering amount of the array error correction under the airborne platform.Has a certain engineering application value.