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CLC number: TB52

On-line Access: 2014-01-27

Received: 2013-08-07

Revision Accepted: 2013-11-20

Crosschecked: 2014-01-14

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Journal of Zhejiang University SCIENCE A 2014 Vol.15 No.2 P.130-137

http://doi.org/10.1631/jzus.A1300263


Target localization based on joint measurement of amplitude and frequency in a LOFAR field*


Author(s):  Lin-wei Tao, Ying-min Wang

Affiliation(s):  . School of Marine Science and Technology, Northwestern Polytechnical University, Xian 710072, China

Corresponding email(s):   tlwlyn@nwpu.edu.cn

Key Words:  Low frequency analyzing and recording (LOFAR), Closest point of approach (CPA), Doppler frequency shift, Transmission loss


Lin-wei Tao, Ying-min Wang. Target localization based on joint measurement of amplitude and frequency in a LOFAR field[J]. Journal of Zhejiang University Science A, 2014, 15(2): 130-137.

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T1 - Target localization based on joint measurement of amplitude and frequency in a LOFAR field
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DOI - 10.1631/jzus.A1300263


Abstract: 
To estimate the motion parameters of a moving target before its passing by the closest point of approach (CPA) point in a low frequency analyzing and recording (LOFAR) field, an error-free theoretical method based on the joint measurement of target radiated noise’s amplitude and frequency was presented. First, the error-free theoretical equations for target characteristic frequency, absolute velocity, the CPA, and amplitude of the radiation noise were derived by three equal interval measured values of the target amplitude and frequency. Then, the method to improve the calculation accuracy was given. Finally, the simulation and experiments were conducted in the air and showed the correctness of this method. By using one single piece of LOFAR, this method can calculate four target parameters and the relative error of each estimated parameter is less than 10%.

低频分析和记录场合基于幅度和频率联合测量的目标定位方法

研究目的:针对低频分析和记录(LOFAR)使用场合,利用目标的幅度和频率信息来解算目标运动要素。
创新要点:利用目标幅度和频率信息,推出无误差的目标特征频率、绝对速度、最接近点距离、辐射幅度等四个参量理论公式,并得到解算目标运动要素的优化方法。
研究方法:1.用计算机进行无误差的理论验证仿真,并在有噪声的影响下,验证算法的正确性;2.在空气中,使用汽车模拟目标的运动,用麦克风采集汽车运动的多普勒信号(见图2),验证算法的工程有效性和正确性。
重要结论:1.使用三次等间隔采样的目标幅度和频率信息,即可无误差地解算出目标特征频率、绝对速度、最接近点距离、辐射幅度等四个参量;2.使用优化后的算法,经实际空气实验验证,使用单个LOFAR传感器即可解算出目标的四个参量,且四个参量的估计相对误差小于10%。

关键词:低频分析和记录(LOFAR);最接近点;多普勒频移;传播损失

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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