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首页> 外文期刊>Aerospace and Electronic Systems, IEEE Transactions on >Source Localization and Sensing: A Nonparametric Iterative Adaptive Approach Based on Weighted Least Squares
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Source Localization and Sensing: A Nonparametric Iterative Adaptive Approach Based on Weighted Least Squares

机译：源定位和传感：基于加权最小二乘的非参数迭代自适应方法

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摘要

Array processing is widely used in sensing applications for estimating the locations and waveforms of the sources in a given field. In the absence of a large number of snapshots, which is the case in numerous practical applications, such as underwater array processing, it becomes challenging to estimate the source parameters accurately. This paper presents a nonparametric and hyperparameter, free-weighted, least squares-based iterative adaptive approach for amplitude and phase estimation (IAA-APES) in array processing. IAA-APES can work well with few snapshots (even one), uncorrelated, partially correlated, and coherent sources, and arbitrary array geometries. IAA-APES is extended to give sparse results via a model-order selection tool, the Bayesian information criterion (BIC). Moreover, it is shown that further improvements in resolution and accuracy can be achieved by applying the parametric relaxation-based cyclic approach (RELAX) to refine the IAA-APES&BIC estimates if desired. IAA-APES can also be applied to active sensing applications, including single-input single-output (SISO) radar/sonar range-Doppler imaging and multi-input single-output (MISO) channel estimation for communications. Simulation results are presented to evaluate the performance of IAA-APES for all of these applications, and IAA-APES is shown to outperform a number of existing approaches.
机译：阵列处理广泛用于传感应用中，以估计给定字段中源的位置和波形。在没有大量快照的情况下（例如在水下阵列处理等许多实际应用中就是这种情况），准确估算源参数变得具有挑战性。本文提出了一种非参数和超参数的，基于自由加权，最小二乘的迭代自适应方法，用于阵列处理中的幅度和相位估计（IAA-APES）。 IAA-APES可以很好地与少量快照（甚至一个快照），不相关，部分相关和相干的源以及任意阵列几何一起使用。 IAA-APES扩展为通过模型顺序选择工具贝叶斯信息标准（BIC）提供稀疏结果。此外，已表明，如果需要，可以通过应用基于参数松弛的循环方法（RELAX）来完善IAA-APES＆BIC估算，从而实现分辨率和精度的进一步提高。 IAA-APES还可以应用于有源传感应用，包括单输入单输出（SISO）雷达/声纳距离多普勒成像和通信的多输入单输出（MISO）信道估计。给出了仿真结果，以评估IAA-APES在所有这些应用中的性能，并且IAA-APES的性能优于许多现有方法。

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