Navigation by inertial device and signals of opportunity

Inertial navigation systems are known to yield rather accurate measurements over short time intervals, while their error variance tends to increase with time. In order to keep the error within specification most systems use GPS signals. In the absence of GPS data, due to jamming or spoofing, it is desirable to use signals of opportunity instead. We examine the use of time of arrival measurements of signals of opportunity that have known structure. We propose a low complexity semi-definite relaxation algorithm by converting the maximum likelihood location estimator to a convex optimization problem. Simulation results demonstrate that the proposed algorithms converge to the Cramer-Rao lower bound under some geometrical and noise limitations. HighlightsA fixing approach for navigation based on signals of opportunity is proposed.The structure of the transmitted signals is exploited to relate between measurements.The maximum likelihood estimator was converted to a convex optimization problem.The convex problem can be effectively solved by semi-definite programming.We reduced algorithm complexity while preserving its RMSE convergence to the CRLB.