邢萌,
刘星,,
曾琦
四川大学电气工程学院 成都 610065
基金项目:国家自然科学基金(61901288)
详细信息
作者简介:钟俊：男，1972年生，博士，副教授，研究方向为信号与信息处理、嵌入式系统等
邢萌：女，1997年生，硕士生，研究方向为信号与信息处理、雷达信号处理等
刘星：男，1986年生，博士，助理研究员，研究方向为序列设计及编码理论等
曾琦：男，1982年生，博士，副教授，研究方向为无线通信系统、信号检测与处理等
通讯作者:刘星 liuxing4@126.com
中图分类号:TN957.51计量
文章访问数:310
HTML全文浏览量:118
PDF下载量:34
被引次数:0
出版历程
收稿日期:2020-12-14
修回日期:2021-03-12
网络出版日期:2021-03-24
刊出日期:2021-11-23
An Automatic Decision Algorithm for Foreign Objects Debris Based on Duffing Oscillator
Jun ZHONG,Meng XING,
Xing LIU,,
Qi ZENG
College of Electrical Engineering, Sichuan University, Chengdu 610065, China
Funds:The National Natural Science Fundation of China (61901288)
摘要
摘要:基于毫米波雷达的机场异物(FOD)检测技术具有高分辨率和低功耗的特点，但是传统恒虚警(CFAR)类检测算法在低信杂比(SCR)情况下虚警过高。该文提出一种基于Duffing振子的FOD检测算法。该算法首先利用杂波图CFAR检测算法将雷达接收机接收回波中的背景杂波初步分离，获得目标(包含虚警)的距离信息，并利用该信息构造Duffing方程，之后将此方程作为系统检测模型，输入接收回波信号，求解输出信号方差，采用方差极值法区分目标和虚警。仿真结果表明，在低信杂比情况下，即使虚警概率为10–3，该文检测算法也可以降低虚警率，实现目标与虚警的自动判决。与传统CFAR检测算法相比，该算法的检测概率高于传统检测算法且随信杂比的下降减小速度缓慢，即使在信杂比–30 dB的情况下所提算法仍然可以保持84%的检测概率。
关键词:机场异物检测/
微弱信号/
Duffing振子/
频率检测/
方差
Abstract:The Foreign Objects Debris (FOD) detection technology based on millimeter wave radar has the advantages of high resolution and low power consumption, but the traditional Constant False Alarm Rate (CFAR) detection algorithm has high false alarm probability under the condition of low Signal-to-Clutter Ratio (SCR). A FOD detection method based on Duffing oscillator is proposed. In this method, the clutter map CFAR detection method is firstly used to separate the background clutter from the received echo signal in the radar receiver, after that the distance information of target (including false alarm) can be acquired, and the Duffing equations are constructed by using the distance information. Then the Duffing equations are used as the system detection model, and the received echo signal is considered as the input. Therefore, the output variance can be calculated by solving the Duffing equations. Finally the target can be distinguished from the false alarm by using the variance extremum method. Simulation results show that, even if the false alarm probability is 10–3, the detection method in this paper can distinguish the target from the false alarm automatically under the condition of low SCR. Furthermore, it can also reduce the false alarm probability. Compared with the traditional CFAR detection algorithm, the detection probability of this method is higher and reduces more slowly with the decrease of SCR. Meanwhile, the detection probability can be maintained at 84% under the condition of SCR=–30 dB.
Key words:Foreign Objects Debris (FOD) detection/
Weak signal/
Duffing oscillator/
Frequency detection/
Variance
PDF全文下载地址:
https://jeit.ac.cn/article/exportPdf?id=4e575ebc-ac97-4adf-803d-3a368147e256
