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Numerical Simulation and Laboratory Testing of Time-Frequency MUSIC Beamforming for Identifying Continuous and Impulsive Ground Targets from a Mobile Aerial Platform

机译:时频MUSIC波束成形的数值模拟和实验室测试,用于识别移动式空中平台的连续和脉冲地面目标

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摘要

When a microphone array is mounted on a mobile aerial platform, such as an unmanned aerial vehicle (UAV), most existing beamforming methods cannot be used to adequately identify continuous and impulsive ground. Here, numerical simulation results and laboratory experiments are presented that validate a proposed time-frequency beamforming method based on the Multiple Signal Classification (MUSIC) algorithm to detect these acoustic sources from a mobile aerial platform.In the numerical simulations three parameters were varied to test the proposed algorithm?s location estimation performance: 1) the acoustic excitation types; 2) the moving receiver?s simulated flight conditions; and 3) the number of acoustic sources. Also, a distance and angle error analysis was done to quantify the proposed algorithm?s source location estimation accuracy when considering microphone positioning uncertainty. For experimental validation, three laboratory experiments were conducted. Source location estimations were done for: a 600 Hz sine source, a banded white noise source between 700-800 Hz, and a composite source combined simultaneously with both the sine and banded white noise sources.The proposed algorithm accurately estimates the simulated monopole?s location coordinates no matter the excitation type or simulated trajectory. When considering simultaneously-excited, multiple monopoles at high altitudes, e.g. 50 m, the proposed algorithm had no error when estimating the source?s locations. Finally, a distance and angle error analysis exposed how relatively small microphone location error, e.g. 1 cm maximum error, can propagate into large averaged distance error of about 10 m in the far-field for all monopole excitation types. For all simulations, however, the averaged absolute angle error remained small, e.g. less than 4 degrees, even when considering a 5 cm maximum microphone location error.For the laboratory experiments, the sine source had averaged distance and absolute angle errors of 0.9 m and 14.07 degrees from the source?s true location, respectively. Similarly, the banded white noise source?s averaged distance and absolute angle errors were 1.9 m and 47.14 degrees; and lastly, the averaged distance and absolute angle errors of 0.78 m and 8.14 degrees resulted when both the sources were simultaneously excited.
机译:当将麦克风阵列安装在诸如无人机(UAV)的移动式空中平台上时,大多数现有的波束成形方法无法用于充分识别连续和冲动的地面。在此,给出了数值模拟结果和实验室实验,这些结果验证了一种基于多信号分类(MUSIC)算法的时频波束形成方法可以从移动航空平台检测这些声源的方法。在数值模拟中,对三个参数进行了测试该算法的位置估计性能:1)声激励类型; 2)移动接收机的模拟飞行状况; 3)声源的数量。此外,在考虑麦克风定位不确定性时,进行了距离和角度误差分析,以量化该算法的信号源位置估计精度。为了进行实验验证,进行了三个实验室实验。进行了源位置估计:600 Hz正弦源,700-800 Hz之间的带状白噪声源以及正弦和带状白噪声源同时组合的复合源。所提出的算法可准确估计模拟的单极子。位置坐标无论是激励类型还是模拟轨迹。当考虑同时激发时,在高海拔,例如50 m时,该算法在估计源位置时没有错误。最后,距离和角度误差分析揭示了相对较小的麦克风位置误差,例如对于所有单极激发类型,最大误差为1 cm,可传播到远场中约10 m的较大平均距离误差中。但是,对于所有模拟,平均绝对角度误差仍然很小,例如,即使考虑最大5 cm的麦克风位置误差,其误差也小于4度。对于实验室实验,正弦源与源的真实位置的平均距离和绝对角度误差分别为0.9 m和14.07度。同样,带状白噪声源的平均距离和绝对角度误差分别为1.9 m和47.14度。最后,当两个源同时被激发时,平均距离和绝对角度误差分别为0.78 m和8.14度。

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    Silva Ramon Alejandro;

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  • 年度 2013
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  • 原文格式 PDF
  • 正文语种 en
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