Automotive Radar Online Channel Imbalance Estimation via NLMS

Fuente: arXiv
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Main Authors: Ghafi, Esmaeil Kavousi, Lang, Oliver, Wagner, Matthias, Melzer, Alexander, Huemer, Mario
Format: Preprint
Published: 2025
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author Ghafi, Esmaeil Kavousi
Lang, Oliver
Wagner, Matthias
Melzer, Alexander
Huemer, Mario
author_facet Ghafi, Esmaeil Kavousi
Lang, Oliver
Wagner, Matthias
Melzer, Alexander
Huemer, Mario
contents Automotive radars are one of the essential enablers of advanced driver assistance systems (ADASs). Continuous monitoring of the functional safety and reliability of automotive radars is a crucial requirement to prevent accidents and increase road safety. One of the most critical aspects to monitor in this context is radar channel imbalances, as they are a key parameter regarding the reliability of the radar. These imbalances may originate from several parameter variations or hardware fatigues, e.g., a solder ball break (SBB), and may affect some radar processing steps, such as the angle of arrival estimation. In this work, a novel method for online estimation of automotive radar channel imbalances is proposed. The proposed method exploits a normalized least mean squares (NLMS) algorithm as a block in the processing chain of the radar to estimate the channel imbalances. The input of this block is the detected targets in the range-Doppler map of the radar on the road without any prior knowledge on the angular parameters of the targets. This property in combination with low computational complexity of the NLMS, makes the proposed method suitable for online channel imbalance estimation, in parallel to the normal operation of the radar. Furthermore, it features reduced dependency on specific targets of interest and faster update rates of the channel imbalance estimation compared to the majority of state-of-the-art methods. This improvement is achieved by allowing for multiple targets in the angular spectrum, whereas most other methods are restricted to only single targets in the angular spectrum. The performance of the proposed method is validated using various simulation scenarios and is supported by measurement results.
format Preprint
id arxiv_https___arxiv_org_abs_2506_10841
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Automotive Radar Online Channel Imbalance Estimation via NLMS
Ghafi, Esmaeil Kavousi
Lang, Oliver
Wagner, Matthias
Melzer, Alexander
Huemer, Mario
Signal Processing
Automotive radars are one of the essential enablers of advanced driver assistance systems (ADASs). Continuous monitoring of the functional safety and reliability of automotive radars is a crucial requirement to prevent accidents and increase road safety. One of the most critical aspects to monitor in this context is radar channel imbalances, as they are a key parameter regarding the reliability of the radar. These imbalances may originate from several parameter variations or hardware fatigues, e.g., a solder ball break (SBB), and may affect some radar processing steps, such as the angle of arrival estimation. In this work, a novel method for online estimation of automotive radar channel imbalances is proposed. The proposed method exploits a normalized least mean squares (NLMS) algorithm as a block in the processing chain of the radar to estimate the channel imbalances. The input of this block is the detected targets in the range-Doppler map of the radar on the road without any prior knowledge on the angular parameters of the targets. This property in combination with low computational complexity of the NLMS, makes the proposed method suitable for online channel imbalance estimation, in parallel to the normal operation of the radar. Furthermore, it features reduced dependency on specific targets of interest and faster update rates of the channel imbalance estimation compared to the majority of state-of-the-art methods. This improvement is achieved by allowing for multiple targets in the angular spectrum, whereas most other methods are restricted to only single targets in the angular spectrum. The performance of the proposed method is validated using various simulation scenarios and is supported by measurement results.
title Automotive Radar Online Channel Imbalance Estimation via NLMS
topic Signal Processing
url https://arxiv.org/abs/2506.10841