Information Fusion Strategies for Collaborative Inertial Radio SLAM

Information fusion strategies for vehicles navigating while aiding their inertial navigation systems (INSs) with terrestrial signals of opportunity (SOPs) are developed and studied. The following problem is considered. Multiple navigating vehicles with access to global navigation satellite system (GNSS) signals are aiding their on-board INSs with GNSS pseudoranges. While navigating, vehicle-mounted receivers draw pseudorange measurements from terrestrial SOPs (e.g., AM/FM radio, digital television, cellular) with unknown emitter positions and unknown and unsynchronized clocks. The vehicles share INS data and SOP pseudoranges to collaboratively estimate the SOPs' states through an extended Kalman filter using tight coupling. After some time, GNSS signals become unavailable, at which point the navigating vehicles use shared INS and SOP information to continue navigating in a collaborative inertial radio simultaneous localization and mapping (CIRSLAM) framework. This paper develops such CIRSLAM framework and synthesizes what SOP and INS information should be shared between collaborators. Two information fusion strategies are compared: 1) sharing time-of-arrival (TOA) measurements from SOPs; 2) sharing time-difference-of-arrival (TDOA) measurements taken with reference to an SOP. Next, a strategy to efficiently share INS information along with SOP information is discussed. Monte Carlo simulation results are presented that support the analytical findings that vehicles navigating in a CIRSLAM framework, while sharing and fusing SOP TOA measurements, produce a smaller or equal estimation error covariance compared to fusing SOP TDOA measurements. Experimental results are presented demonstrating two unmanned aerial vehicles (UAVs) navigating in a CIRSLAM framework with SOP TOA measurements from terrestrial cellular towers. The final UAVs' localization error after 30 seconds of GPS unavailability were reduced compared to using an INS alone from around 55 m to around 6 m.

Automated summary

This paper develops information fusion strategies for vehicles navigating with the assistance of terrestrial signals, sharing INS data and SOP pseudoranges for collaboratively estimating the states of SOPs. Results show that sharing and fusing SOP TOA measurements in a CIRSLAM framework lead to smaller estimation error covariances compared to fusing SOP TDOA measurements.