CAJ | 학술논문

提出了一种基于矩阵重构和多重假设检验相结合的方法.采用特殊定义的变换-对消矩阵,抵消了非平稳噪声的影响;采用多次重构的显著性函数结果与显著性水平比较来判断信源数,避免了假设检验对先验知识的要求.将单序列假设检验扩展为多个序列联合检验后,即使在低信噪比和低快拍数时也可以获得较好的估计性能;同时显著性水平的确定与阵列数据无关,基本不需要先验信息,约束条件较少.仿真结果验证了该方法的有效性.
제출료일충기우구진중구화다중가설검험상결합적방법.채용특수정의적변환-대소구진,저소료비평은조성적영향;채용다차중구적현저성함수결과여현저성수평비교래판단신원수,피면료가설검험대선험지식적요구.장단서렬가설검험확전위다개서렬연합검험후,즉사재저신조비화저쾌박수시야가이획득교호적고계성능;동시현저성수평적학정여진렬수거무관,기본불수요선험신식,약속조건교소.방진결과험증료해방법적유효성.
Based on the reconstructed matrix and the multiple hypothesis testing, this paper presents a scheme for estimating the signal number in spatial nonstationary noise fields. A special transform-differencing matrix is constructed to cancel the nonstationary noise. Then, the result of multiple reconstructed hypothesis tests is used to estimate the signal number compared with the significant level, thus avoiding the requirement for prior knowledge of hypotheses. The scheme has a superior performance even in the case of low SNR and short snapshots. Furthermore, the significant level has no a relation to the receiving data of the array, so it does not need any priori knowledge. Simulation results prove the improved performance of the method.