A Novel Hybrid TDMA–DDMA Approach for Imaging Automotive Radar Systems

IF 2.2 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Deniz Kumlu;Timothee Vincon;Muhammad Arsalan;Ernesto Horne
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引用次数: 0

Abstract

In this letter, we propose a novel hybrid time-division multiple access (TDMA) and Doppler-division multiple access (DDMA) model for cascaded radar systems, targeting high-resolution automotive radar applications. By leveraging the Texas instruments AWR2243 radar sensor, configured in a cascaded multiple-input multiple-output arrangement, we demonstrate the advantages of combining TDMA and DDMA for enhanced performance in both velocity resolution and range accuracy. Conventional TDMA and DDMA approaches suffer from inherent tradeoffs between maximum unambiguous velocity, Doppler resolution, and frame rate. Our hybrid method dynamically toggle between TDMA and DDMA activation patterns, achieving a balance between these metrics. Through theoretical analysis and experimental validation, we show that our model improves Doppler resolution while maintaining a competitive frame rate and range resolution. The proposed hybrid solution is particularly advantageous for scenarios where both high velocity measurements and high angular resolution are critical, such as in advanced driver-assistance systems and autonomous driving. This approach provides a flexible and efficient means of optimizing radar performance without compromising key system parameters, as supported by our experimental results and theoretical calculations.
一种新型TDMA-DDMA混合成像汽车雷达系统方法
在这封信中,我们提出了一种新的混合时分多址(TDMA)和多普勒多址(DDMA)模型,用于级联雷达系统,目标是高分辨率汽车雷达应用。通过采用级联多输入多输出配置的德州仪器AWR2243雷达传感器,我们展示了TDMA和DDMA相结合的优势,提高了速度分辨率和距离精度。传统的TDMA和DDMA方法在最大明确速度、多普勒分辨率和帧速率之间存在固有的权衡。我们的混合方法在TDMA和DDMA激活模式之间动态切换,实现了这些指标之间的平衡。通过理论分析和实验验证,我们的模型提高了多普勒分辨率,同时保持了具有竞争力的帧速率和距离分辨率。该混合解决方案尤其适用于高速测量和高角度分辨率至关重要的场景,例如高级驾驶员辅助系统和自动驾驶。这种方法提供了一种灵活有效的优化雷达性能的方法,而不会影响关键系统参数,正如我们的实验结果和理论计算所支持的那样。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Sensors Letters
IEEE Sensors Letters Engineering-Electrical and Electronic Engineering
CiteScore
3.50
自引率
7.10%
发文量
194
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