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•

In this paper a method of monostatic RCS measuring in real conditions for complex shaped objects is proposed. The basic idea of the method is to provide measuring in near field zone for different parts of the object (fragments) separately. This technique is titled "decomposition method". After such measurements all RCS data are summed and one can obtain the average RCS of investigated object. Such method is much more accessible in comparison with natural measurements in far field zone. In this paper the decomposition method is tested numerically. For this a model of complex shape object (tank T-90) is divided into the fragments for some direction of view. It is shown that the sum of RCS of the fragments is close to the full object RCS for corresponding direction.

The time delay of echo generated by the moving target simulator based on digital delay technique is discrete. So there are range and phase errors between the simulated target and real target, and the simulated target will move discontinuously due to the discrete time delay. In order to solve this problem and generate a continuously moving target, this paper uses signal processing technique to adjust the range and phase errors between the two targets. By adjusting the range gate, the time delay error is reduced to be smaller than sampling interval. According to the relationship between range and phase, the left error within one range bin can be removed equivalently by phase compensation. The simulation results show that by adjusting the range gate, the time delay errors are greatly reduced, and the left errors can be removed by phase compensation. In other words, a real continuously moving target is generated and the problem is solved.