Biblio

Promising means of detecting small UAVs are FMCW radar systems. Small UAVs with an RCS value of the order of 10−3••• 10−1m2 are characterized by a low SNR (less than 10 dB). To ensure an acceptable probability of detection in the resolution element (more than 0.9), it becomes necessary to reduce the detection threshold. However, this leads to a significant increase in the probability of false alarms (more than 10−3) and is accompanied by the appearance of a large number of false plots. The work describes an algorithm for trajectory detecting of a small UAV based on a “l/n-d” criterion using Kalman filtering in a spherical coordinate system due to FMCW radar data. Statistical analysis of algorithms based on two types of criteria “3/5-2” and “5/9-2” is performed. It is shown that the algorithms allow to achieve the probability of target trajectory detection greater than 0.9 and low probability of false detection of the target trajectory less than 10−4 with the false alarm probability in the resolution element 10−3••• 10−2•

A new approach to micro-Doppler signal analysis is presented in this article. Novel chirp rate estimators in the time-frequency domain were used for this purpose, which provided the chirp rate of micro-Doppler signatures, allowing the classification of objects in the urban environment. As an example verifying the method, a signal from a high-resolution radar with a linear frequency modulated continuous wave (FMCW) recording an echo reflected from a pedestrian was used to validate the proposed algorithms for chirp rate estimation. The obtained results are plotted on saturated accelerograms, giving an additional parameter dedicated for target classification in security systems utilizing radar sensors for target detection.