| Title | Analysis Of The Small UAV Trajectory Detection Algorithm Based On The “l/n-d” Criterion Using Kalman Filtering Due To FMCW Radar Data |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Neuimin, Oleksandr S., Zhuk, Serhii Ya., Tovkach, Igor O., Malenchyk, Taras V. |
| Conference Name | 2022 IEEE 16th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET) |
| Keywords | Channel estimation, composability, False Data Detection, false plots, Filtering, FMCW radar, Human Behavior, Kalman filtering, probability, pubcrawl, Radar cross-sections, radar detection, Radar tracking, resilience, Resiliency, spherical coordinate system, target tracking, trajectory detection |
| Abstract | Promising means of detecting small UAVs are FMCW radar systems. Small UAVs with an RCS value of the order of 103*** 101m2 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 103) 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 104 with the false alarm probability in the resolution element 103*** 102* |
| DOI | 10.1109/TCSET55632.2022.9766929 |
| Citation Key | neuimin_analysis_2022 |
Analysis Of The Small UAV Trajectory Detection Algorithm Based On The “l/n-d” Criterion Using Kalman Filtering Due To FMCW Radar Data