Development of a Frequency Dependent INS/GPS System Response Model for Bridging GPS Outages

The integration of Inertial Navigation System (INS) and Global Positioning System (GPS) architectures can be achieved through the use of many time domain filters such as, an extended Kalman filter, an unscented Kalman filter, divided difference filter, and particle filter. The main objective of all the above filters is to achieve precise fusion of the data from GPS and INS to provide INS only navigation solution during GPS outages. The prediction mode performance of all state of the art time domain filters is poor with significant drift in the INS only solution. In this paper, a new frequency domain dynamic response method with variable frequency bandwidth is proposed to model the INS/GPS system. The Least Squares Spectral Analysis (LSSA), Parzen window based smoothing, and the Inverse Least Squares Fourier Transform (ILSFT) are employed to develop the INS/GPS system frequency response (transfer function). The input to this dynamic system is the INS only solution and the output is the INS/GPS integration solution. The discrete inverse ILSFT of the transfer function is applied to estimate the impulse response of the INS/GPS system. The focus of this paper is the improvement in velocity solution, which leads to almost the same level of improvement in the position solution in an INS/GPS system. To examine the performance of the proposed approach, a kinematic dataset (Dual frequency GPS data from a Trimble BD950 receiver and inertial data from DQI100 IMU) is collected in Hamilton Harbour, Ontario, onboard a hydrographic surveying vessel owned by the Canadian Hydrographic Service. The loosely coupled INS/GPS with unscented Kalman filter is developed to obtain an INS/GPS integrated navigation solution and an INS only solution. Then, the INS/GPS and INS only navigation solutions are used to develop the impulse response of the INS/GPS system. It is shown that the developed impulse response can be used to detect and recover the long term motion dynamics of DQI100 IMU during 300s GPS outages with about 65% dynamic recovery of the north velocity and 45% dynamic recovery of east velocity solution when compared with the INS only solution. We will present and discuss many examples from a variety of GPS outages that exemplify the effectiveness of our method.