M. E. Shevchenko, V. N. Malyshev, A. V. Gorovoy, A. S. Cherepanov
{"title":"Spatial Filtering of Signals under Imprecise Calibration of Antenna Arrays","authors":"M. E. Shevchenko, V. N. Malyshev, A. V. Gorovoy, A. S. Cherepanov","doi":"10.32603/1993-8985-2023-26-6-27-40","DOIUrl":null,"url":null,"abstract":"Introduction. Spatial filtering of signals is performed for the selection the signals of interest when the signals spectra overlap. The quality of spatial filtering depends on the accuracy of antenna array (AA) calibration, which allows estimation of the amplitude-phase distribution (APD) at all possible directions of arrival, thus ensuring the identity of reception paths. A mismatch between the actual and measured APD values leads to quality degradation in all spatial filtering methods.Aim. To develop a method for improving the quality of signal spatial filtering based on the estimates of the desired and interfering signal arrival directions formed by the MUSIC and ESPRIT algorithms under a priori uncertainty and imprecise AA calibration.Materials and methods. The quality of spatial filtering is improved by rejecting the interfering signals unsuppressed due to imprecisely measured APD of an AA. Statistical simulation modeling was carried out in the MATLAB environment; the data obtained experimentally were analyzed.Results. A method for spatial filtering based on MUSIC and ESPRIT completed with an additional rejection of unsuppressed interfering signals due to imprecise AA calibration is developed. An algorithm for basis construction for rejection under of a priori uncertainty of the signal-interference environment is substantiated. The results of statistical simulation modeling and experimental data processing have shown the feasibility of additional rejection applied to the selected signals by spatial filtering.Conclusion. The developed method for spatial filtering under the conditions of a priori uncertainty of the signal-interference situation and imprecise calibration of AA and reception paths ensures high quality characteristics across a wide dynamic range of desired and interfering signals. Whereas the Capon's method, which requires a priori knowledge of the arrival direction of the desired signal or its estimation, is capable of selecting only weak signals and suppressing strong ones under the conditions of imprecise APD.","PeriodicalId":217555,"journal":{"name":"Journal of the Russian Universities. Radioelectronics","volume":"35 9","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Russian Universities. Radioelectronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32603/1993-8985-2023-26-6-27-40","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Introduction. Spatial filtering of signals is performed for the selection the signals of interest when the signals spectra overlap. The quality of spatial filtering depends on the accuracy of antenna array (AA) calibration, which allows estimation of the amplitude-phase distribution (APD) at all possible directions of arrival, thus ensuring the identity of reception paths. A mismatch between the actual and measured APD values leads to quality degradation in all spatial filtering methods.Aim. To develop a method for improving the quality of signal spatial filtering based on the estimates of the desired and interfering signal arrival directions formed by the MUSIC and ESPRIT algorithms under a priori uncertainty and imprecise AA calibration.Materials and methods. The quality of spatial filtering is improved by rejecting the interfering signals unsuppressed due to imprecisely measured APD of an AA. Statistical simulation modeling was carried out in the MATLAB environment; the data obtained experimentally were analyzed.Results. A method for spatial filtering based on MUSIC and ESPRIT completed with an additional rejection of unsuppressed interfering signals due to imprecise AA calibration is developed. An algorithm for basis construction for rejection under of a priori uncertainty of the signal-interference environment is substantiated. The results of statistical simulation modeling and experimental data processing have shown the feasibility of additional rejection applied to the selected signals by spatial filtering.Conclusion. The developed method for spatial filtering under the conditions of a priori uncertainty of the signal-interference situation and imprecise calibration of AA and reception paths ensures high quality characteristics across a wide dynamic range of desired and interfering signals. Whereas the Capon's method, which requires a priori knowledge of the arrival direction of the desired signal or its estimation, is capable of selecting only weak signals and suppressing strong ones under the conditions of imprecise APD.
简介对信号进行空间滤波是为了在信号频谱重叠时选择感兴趣的信号。空间滤波的质量取决于天线阵列(AA)校准的准确性,通过校准可以估算所有可能到达方向的幅相分布(APD),从而确保接收路径的一致性。实际和测量的 APD 值不匹配会导致所有空间滤波方法的质量下降。根据 MUSIC 和 ESPRIT 算法在先验不确定性和不精确 AA 校准情况下形成的期望信号和干扰信号到达方向估计值,开发一种提高信号空间滤波质量的方法。空间滤波的质量是通过剔除由于不精确测量 AA 的 APD 而未被抑制的干扰信号来提高的。在 MATLAB 环境中进行了统计仿真建模,并对实验获得的数据进行了分析。开发了一种基于 MUSIC 和 ESPRIT 的空间滤波方法,该方法还能额外抑制因 AA 校准不精确而导致的未抑制干扰信号。在信号干扰环境的先验不确定性条件下,为剔除干扰信号而构建基础的算法得到了证实。统计仿真建模和实验数据处理的结果表明,通过空间滤波对选定信号进行额外剔除是可行的。在信号干扰情况先验不确定以及 AA 和接收路径校准不精确的条件下,所开发的空间滤波方法可确保在所需信号和干扰信号的宽动态范围内具有高质量特性。而卡彭方法需要先验地了解所需信号的到达方向或对其进行估计,在 APD 不精确的条件下,只能选择弱信号,抑制强信号。