Array Self-Calibration For Gain-Phase Error

It is obvious that the array radar has great advantages over traditional phased array in target detection,parameter estimation,interference cancellation and low probability of interception.As array radar utilizes more active devices in the transmitter and receiver,of which the gain and phase may change significantly due to machining error,working environment and service time.However,most array radar signal processing algorithms require the knowledge of array manifold.In the case where gain-phase error exists,the gain-phase error will alter the array manifold leading to great degradation in algorithm performances.Therefore research in array gain-phase error calibration is of both theoretical and practical value.According to the usage of active calibration sources,the gain-phase error calibration methods are divided into two categories,one is pilot calibration and the other is self-calibration.Pilot calibration requires the knowledge of calibration sources with known directions,thus this method is restricted in its usage.In the self-calibration algorithm,the typical RARE(rank-reduction)algorithm is suitable for the accurate calibration of certain array elements,but it has some major defects: 1)The original RARE algorithm requires peak search.With small interval,frequent searches are required that can lead to heavy computing burden.While the interval is getting larger,the estimation precision will be poorer;2)The 2-dimensional grid in original RARE algorithm can hardly be applied to the 2-dimensional target angle estimation due to its high density as well as the high computational complexity.To get around these problems,this paper proposes two improved RARE algorithms:Firstly,a new root-RARE algorithm is proposed according to the peak search,the large calculation and low estimation accuracy in the RARE algorithm.Which can substitute the polynomial root finding for the spectral peak search.This algorithm can effectively solve the heavy computational burden in RARE algorithm.Compared with the existing algorithm,the proposed method verifies and analyses the performance estimation as well as cpu time of DOA and DOD in the case of low SNR.The simulation results show that the algorithm can greatly reduce the amount of calculation and effectively improve the estimation performance of DOA.Secondly,for the dense 2-dimensional grid and heavy computation.An algorithm based on RARE algorithm is proposed which estimates the DOA and DOD in the 2-dimensional angular radar,and self-calibrate the gin-phase coefficients.The proposed algorithm realizes the data separation of DOD and DOA by rearranging the received data in the two-dimensional angle radar.Compared with the existing algorithms,the algorithm effectively avoids the most error interference between DOD and DOA of the current two-dimensional angle estimation algorithms.Besides,the algorithm significantly improves the estimation performance of DOD and DOA,and reduces computational complexity.In addition,the algorithm also improves the accuracy of DOD and DOA estimation as well as calibrates the gain-phase error better.Thus,the estimated DOD and DOA can be automatically matched.The simulation example demonstrates the effectiveness of the algorithm.