超声差分Zadoff-Chu码运动目标距离估计
Range Estimation of a Moving Target Using Ultrasound Differential Zadoff-Chu Codes
摘要：
高精度距离估计是许多现代应用和技术中所需的基本工具。然而，运动目标的连续距离估计是一项具有挑战性的任务，特别是在多普勒效应下。本文提出了一种新的信号设计，我们称之为差分Zadoff-Chu（DZC）。在多普勒效应下，与使用常规ZC序列时的性能相比，DZC序列改善了基于最大似然（ML）的距离估计的性能。此外，一个降低复杂度的测距算法，提出了利用DZC序列，并显示出优于常规的ZCML为基础的距离估计。建议的系统进行评估，在一个典型的室内环境中，使用低成本的超声硬件。在低信噪比（-10 dB SNR）下，运动距离为$0.2$ m ~ 2.2 m，最大速度为0.5 m/s，90%以上的距离估计误差小于1.6 mm。对于相同的移动范围，该系统提供的距离估计值在高SNR情况下（10 dB）的均方根误差（RMSE）小于0.76 mm，在低SNR情况下（-10 dB）的MSE小于0.85 mm。对于一个更大的运动范围从1.8米到4.2米的最大速度为1.91米/秒，所提出的系统提供的距离估计与RMSE小于7.70毫米在10分贝信噪比。
英文摘要：
High accuracy range estimation is an essential tool required in many modern applications and technologies. However, continuous range estimation of a moving target is a challenging task, especially under Doppler effects. This paper presents a novel signal design, which we name differential Zadoff-Chu (DZC). Under Doppler effects, DZC sequences improve the performance of the maximum likelihood (ML)-based range estimation compared to its performance when using regular ZC sequences. Moreover, a reduced-complexity ranging algorithm is proposed utilizing DZC sequences and is shown to outperform the regular ZC ML-based range estimation. The proposed system is evaluated in a typical indoor environment, using low-cost ultrasound hardware. Under a low signal to noise ratio (-10 dB SNR), more than 90% of the range estimates are in less than 1.6 mm error, with a movement range from $0.2$ m to 2.2 m and a maximum velocity of 0.5 m/s. For the same movement range, the system provides range estimates with a root mean square error (RMSE) less than 0.76 mm in a high SNR scenario (10 dB), and an MSE less than 0.85 mm in a low SNR scenario (-10 dB). For a larger movement range from 1.8 m to 4.2 m with a maximum velocity of 1.91 m/s, the proposed system provides range estimates with RMSE less than 7.70 mm at 10 dB SNR.
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