Integrated Self-Contained Trajectory Estimation and Multistatic SAR Imaging in a Non-Static Uncoupled Bistatic Radar Network

Abstract

Radar imaging performance can be significantly improved by creating synthetic apertures along a radar sensor's trajectory compared to standard MIMO imaging radars. Additionally, observing the scenery from both monostatic and bistatic perspectives with large bistatic angles can further increase the information content of radar images, as different parts of complex targets can exhibit different scattering mechanisms. Both technologies, synthetic aperture radar and coherent multistatic radar networks, come with demanding system requirements regarding the localization and synchronization of the involved radars, which are addressed by the proposed approach. The unique aspect of our novel bi-/multistatic radar approach is that no auxiliary sensor technology is needed to determine the trajectory. The same radar signals are jointly used at the same time for trajectory determination, clock synchronization, and bistatic SAR imaging. The integrated self-contained trajectory estimation is based on a particle filter algorithm that processes the line-of-sight radar signals of the bistatic radar pairs, which are exchanged in a double-sided two-way ranging manner. This approach opens up new applications of bi-/multistatic radar for autonomous air and ground vehicles. However, the requirement of a line-of-sight connection between the radar pairs imposes a constraint on possible bistatic constellations and trajectories. Therefore, it is shown that suitable compromises regarding the geometry, localization accuracy, and resolution of SAR imaging must also be taken into account. We demonstrate the capabilities of this approach by generating monostatic and bistatic SAR images with 77 GHz SIMO FMCW radar sensors from indoor and outdoor measurement scenarios with synthetically generated apertures estimated by the integrated self-contained localization algorithm.