Abstract
Recently, nonlinear blind compensation technique has attracted growing attention in array signal processing application. However, due to the nonlinear distortion stemming from array receiver which consists of multi-channel radio frequency (RF) front-ends, it is too difficult to estimate the parameters of array signal accurately. A novel nonlinear blind compensation algorithm aims at the nonlinearity mitigation of array receiver and its spurious-free dynamic range (SFDR) improvement, which will be more precise to estimate the parameters of target signals such as their two-dimensional directions of arrival (2-D DOAs). Herein, the suggested method is designed as follows: the nonlinear model parameters of any channel of RF front-end are extracted to synchronously compensate the nonlinear distortion of the entire receiver. Furthermore, a verification experiment on the array signal from a uniform circular array (UCA) is adopted to testify the validity of our approach. The real-world experimental results show that the SFDR of the receiver is enhanced, leading to a significant improvement of the 2-D DOAs estimation performance for weak target signals. And these results demonstrate that our nonlinear blind compensation algorithm is effective to estimate the parameters of weak array signal in concomitance with strong jammers.
Highlights
During the past few decades, array signal processing (ASP) has been a world-wide hot spot of research [1,2], with discoveries as diverse in application as wireless communications, multiple-input multiple-output (MIMO) radar and sonar [3,4,5,6]
ASP is concerned with the problem of extracting high dimensional information of interest which is received from an array of spatially distributed sensors and transmitted to a multi-channel array receiver
Estimation is the hottest topic and most of the published literature focuses on parametric algorithms to deal with it [9,10,11]. These methods are proven to perform well in source direction finding under ideal settings, which ignore the negative effect of the nonlinear distortion components of an array signal processing system on source localization accuracy
Summary
During the past few decades, array signal processing (ASP) has been a world-wide hot spot of research [1,2], with discoveries as diverse in application as wireless communications, multiple-input multiple-output (MIMO) radar and sonar [3,4,5,6]. Estimation is the hottest topic and most of the published literature focuses on parametric algorithms to deal with it [9,10,11] These methods are proven to perform well in source direction finding under ideal settings, which ignore the negative effect of the nonlinear distortion components of an array signal processing system on source localization accuracy. In References [18,20,21,22,23], the nonlinear behavior model parameters are identified and extracted in the frequency domain, resulting in heavy computational costs To solve these identification problems, separating large signals (strong array signals) and small signals (nonlinear distortion components and weak array signals) in time domain according to the power level is appropriate.
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