ESTIMATION AND CALIBRATION OF UAV TRAJECTORY DEVIATION FOR THROUGH-WALL RADAR DETECTION

The small Unmanned Aerial Vehicle (UAV) equipped with Frequency-Modulated Continuous Wave (FMCW) Radar can flexibly detect the enclosed environments within high-rise buildings by through-wall detection and thus has been widely studied recently. However, mini-UAVs are susceptible to large and complex trajectory deviations caused by environmental disturbances. Such deviations with complex pattern significantly affect both the envelope and phase of the radar echoes. Traditional algorithms for compensating motion errors are ineffective. This article introduces a self-focusing algorithm that relies on Back Projection (BP) imaging results. The algorithm performs iterative optimization based on the linear properties of the wall and the image contrast of the distributed multi-objectives behind the wall. Instead of estimating the 2D space-variation phase error, trajectory deviations in the line-of-sight direction and along the heading are estimated and compensated in two steps. In cases where the trajectory deviates larger than the range resolution, the algorithm can effectively estimate and compensate for large deviations, achieving estimation accuracy at the range resolution level.