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Implementation of a GNU radio and python FMCW radar toolkit

机译:实现GNU Radio和Python FMCW雷达工具包

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The use of GNU Radio in order to explore FMCW radar is growing rapidly, where it is used for radar signal processing. In this paper we implement FMCW surveillance radar for drone detection on SDR using GNU Radio and the USRP B210. The requirement was to design and implement an FMCW surveillance radar to detect a drone with a radar cross-section of 0.1 m2 and a maximum range of 150 m for the purpose of point detection. The signal processing takes the beat frequency which has pulse compression gain and performs coherent integration. It windows and displays the results on a range Doppler map using two-dimensional fast Fourier transform. The pulse repetition frequency of the waveform is selected as 2200 Hz with a chirp bandwidth of 28 MHz, allowing for resolving a maximum velocity of 30 m/s unambiguously, which is the typical maximum speed of a small drone. Experiments were conducted using a human being and a car target as a drone was not available. The B210 induced a phase drift in the results which causes a Doppler shift. The phase drift was resolved by creating a phase equalization matrix, which was used to correct the phase drift in real-time. Verification of the designed radar system yielded a 63% probability of detection and probability of false alarm of 1.7 × 10-6.
机译:使用GNU收音机以探索FMCW雷达正在快速增长,在那里它用于雷达信号处理。在本文中,我们在使用GNU无线电和USRP B210对SDR进行无人机检测的FMCW监控雷达。该要求是设计和实施FMCW监控雷达,以检测雷达横截面为0.1M 2 的无人机,最大范围为150 m,以便检测。信号处理采用具有脉冲压缩增益并执行相干积分的节拍频率。 IT Windows使用二维快速傅立叶变换在范围多普勒地图上显示结果。波形的脉冲重复频率选择为2200Hz,具有28 MHz的啁啾带宽,允许解析毫不曼奇的最大速度为30米/秒,这是小无人机的典型最大速度。使用人的实验和作为无人机的汽车靶来进行。 B210在导致多普勒偏移的结果中诱导相偏移。通过创建相位均衡矩阵来解决相位漂移,该矩阵用于实时校正相位漂移。设计的雷达系统的验证产生了63×%的检测概率和误报的概率为1.7×10 -6

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