Synthetic aperture radar (SAR) processing on agile radar platforms requires a very accurate estimate of position due to the unpredictable trajectory of such platforms. This is even more challenging in GPS-denied scenarios where the bias in inertial sensors cannot be compensated. In this study, we propose a 3D radar-Aided positioning method based on SAR autofocusing to achieve subresolution positioning accuracy. The proposed multibeam autofocus algorithm builds on multiple SAR motion compensation techniques to generalize and provide a framework for simultaneous omnidirectional imaging and trajectory estimation and correction while taking advantage of the beamforming capabilities of the antenna array. Our initial simulations and proof of concept show that the performance of the proposed approach is adequate even in low signal-To-noise ratio cases.

Continuous navigation is crucial for small drones when flying a pre-planned route or during autonomous flight. In scenarios where a global positioning system (GPS) signal is unavailable, drift in the onboard sensors causes the inertial navigation system (INS) to quickly deviate from the planned route. This paper proposes a radar-aided navigation method for small drones which is able to estimate the horizontal velocity and height of the platform independently from GPS. The method is based on an omnidirectional radar system and takes advantage of multi-look processing to increase estimation precision. Simulations and experiments verify that an omnidirectional radar can be used to successfully estimate the velocity and course of a small drone platform.