Automotive radar sensors are widely used in vehicles so as to allow the "advanced driver assistance systems (ADAS)" to work. As far as we are concerned, no mandatory regulations were established so far for i...
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Automotive radar sensors are widely used in vehicles so as to allow the "advanced driver assistance systems (ADAS)" to work. As far as we are concerned, no mandatory regulations were established so far for interference control in the cases where multiple vehicles equipped with automotive radars exist in close proximity. Consequently, those inter-vehicle cross-interference easily result in the radar performance degradation, e.g. incapability of target detection and identification. In this paper, an interference suppression algorithm is proposed which utilizes two Recursive-Least-Square (rls) adaptive filters to estimate, the interference signals caused by the "aggressor" radar and the echo signals from the "ego" radar. The algorithm operates in the iterative mode with its initial input being the originally received beat signals involving interference. In each iteration, the estimates of the interference signals and of the clean signals are calculated sequentially by the two rls filters, and the beat signal is updated with parts of the fragments substituted with their interference-mitigated counterparts. Such iterative operations stop when the convergence criterion, e.g. none of the fragments in the beat signals are considered being interfered, is achieved or the iteration number reaches the limit predefined due to the practical constraints. Simulation and measurement results demonstrate that the proposed dual-rls-based algorithm outperforms the existing methods in terms of lower interference-to-signal ratio resultant and superior capability of retrieving the original range-Doppler profile.
In this paper, we propose an ordered selection technique to improve the performance of the decision-directed rlsadaptive channel tracking algorithm in 2x2 spatial-multiplexing MIMO-OFDM systems under high mobility. T...
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ISBN:
(纸本)9781424448562
In this paper, we propose an ordered selection technique to improve the performance of the decision-directed rlsadaptive channel tracking algorithm in 2x2 spatial-multiplexing MIMO-OFDM systems under high mobility. The proposed technique uses the decision of high reliability order during MIMO signal detection and then selectively activates the rls adaptation only when less interference and error will be generated if a wrong decision is still made. Simulation results show that the channel tracking accuracy of the proposed approach outperforms the 2D-rlsalgorithm and the conventional linear interpolation algorithm. Moreover, we also show that both ordering and selection are effective and necessary to greatly suppress the error propagation and coefficient misadjustment. With the proposed technique, the system performance has obvious SNR improvements.
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