Simultaneous Localization and Calibration for Cooperative Radio Navigation

Cooperative radio localization and navigation systems can be used in scenarios where the reception of global satellite system (GNSS) signals is not possible or impaired. While benefit cooperation has been highlighted by many papers, calibration widely considered, but equally important practice. Utilizing signal propagation time requires group delay ranging bias estimating directions-of-arrival (DoAs) antenna response calibration. Often, parameters are determined only once before operation. However, influenced e.g. changing temperatures frequency (RF) components surroundings antennas. To cope with that, we derive a cooperative simultaneous (SLAC) algorithm based on Bayesian filtering, which estimates responses biases simultaneously positions orientations. By simulations, show that estimated during operation without additional sensors. We further proof practical applicability SLAC evaluating measurement data from robotic rovers. With SLAC, both DoAs estimation performance improved, resulting better position orientation accuracy. thus able to provide reliable mitigate model mismatch. Finally, discuss open research questions extensions SLAC.