GPS/INS

About: GPS/INS is a research topic. Over the lifetime, 3554 publications have been published within this topic receiving 62784 citations.

GPS/INS Kalman filter design for spacecraft operating in the proximity of the international space station

Abstract: The next generation reusable launch vehicle will operate in flve ∞ight phases: ascent, on-orbit, proximity operations, re-entry and landing. Navigation during each of these ∞ight phases presents unique challenges. The Space Shuttle addresses these challenges by the use of a number of navigation sensors. However, an integrated GPS/INS navigation system may be able to meet the navigation requirements of all ∞ight phases. Integrated GPS/INS systems have been built and demonstrated for the ascent, re-entry and landing phases and their performance is known. However, the same cannot be said for integrated GPS/INS systems for the on-orbit and proximity operations ∞ight phases. Therefore, this research examines the performance of GPS/INS navigation during a rendezvous with the ISS. Error models for INS and GPS navigation sensors operating in the vicinity of the ISS have been developed. The GPS error model includes the efiects of GPS signal blockage and multipath near the ISS. These error models have been used to develop an integrated GPS/INS extended Kalman fllter. A simulation of the fllter has been developed and the flrst test case shows position errors of less than 1 meter and velocity errors of less than 0.02 m/s in each axis. The second test case shows the position errors grow to approximately 47.5 meters and the velocity errors grow to 0.13 m/s during a ten minute GPS outage. Finally, the third test case shows that the GPS/INS EKF performance is not signiflcantly degraded by GPS signal blockage due to the ISS during a simulated rendezvous with the ISS.

Loosely coupled Kalman filtering for fusion of Visual Odometry and inertial navigation

Abstract: Visual Odometry (VO) is the process of estimating the motion of a system using single or stereo cameras. Performance of VO is comparable to that of wheel odometers and GPS under certain conditions; therefore it is an accepted choice for integration with inertial navigation systems especially in GPS denied environments. In general, VO is integrated with the inertial sensors in a state estimation framework. Despite the various instances of estimation filters, the underlying concepts remain the same, an assumed kinematic model of the system is combined with measurements of the states of that system. The drawback of using kinematic models for state transition is that the state estimate will only be as good as the precision of the model used in the filter. A common approach in navigation community is to use an error propagation model of the navigation solution using inertial sensor instead of an assumed dynamical model. High rate IMU will trace the dynamic better than an assumed model. In this paper, we propose a loosely coupled indirect feedback Kalman filter integration for visual odometry and inertial navigation system that is based on error propagation model and takes into account different characteristics of individual sensors for optimum performance, reliability and robustness. Two measurement models are derived for the accumulated and incremental visual odometry measurements. A practical measurement model approach is proposed for the delta position and attitude change measurements that inherently includes delayed-state. The non-Gaussian, non-stationary and correlated error characteristics of VO, that is not suitable to model in a standard Kalman filter, is tackled with averaging the measurements over a Kalman period and utilizing a sigma-test within the filter.

Improvement in the UAV position estimation with low-cost GPS, INS and vision-based system: Application to a quadrotor UAV

Abstract: In this paper, we develop a position estimation system for Unmanned Aerial Vehicles formed by hardware and software. It is based on low-cost devices: GPS, commercial autopilot sensors and dense optical flow algorithm implemented in an onboard microcomputer. Comparative tests were conducted using our approach and the conventional one, where only fusion of GPS and inertial sensors are used. Experiments were conducted using a quadrotor in two flying modes: hovering and trajectory tracking in outdoor environments. Results demonstrate the effectiveness of the proposed approach in comparison with the conventional approaches presented in the vast majority of commercial drones.

Position and velocity Kalman filter for use with global navigation satelite system receivers

Abstract: A GPS receiver utilizes measurements which span previous and current times, such as delta phase measurements, in a modified Kalman filter. The modified Kalman filter updates position information relating to both the current and the previous times, and s propagates the current position and velocity related information. Using both the current and the previous position related information in the filter in conjunction with delta phase measurements, essentially eliminates the effect of system dynamics from the system model, and a position difference can thus be formed that is directly observable by the phase difference measured between the previous and current time epochs.

A Novel Architecture for Ultra-Tight HSGPS-INS Integration

Abstract: Global Positioning System (GPS) currently fulfills the positioning requirements of many applications under Line-Of-Sight (LOS) environments. However, many Location-Based Services (LBS) and navigation applications such as vehicular navigation and personal location require positioning capabilities in environments where LOS is not readily available, e.g., urban areas, indoors and dense forests. Such environments either block the signals completely or attenuate them to a power level that is 10-30 dB lower than the nominal signal power. This renders it impractical for a standard GPS receiver to acquire and maintain signal tracking, which causes discontinuous positioning in such environments. In order to address the issue of GPS tracking and positioning in degraded signal environments, a novel architecture for ultra-tight integration of a High Sensitivity GPS (HSGPS) receiver with an inertial navigation system (INS) is proposed herein. By enhancing receiver signal tracking loops through the use of optimal estimators and with external aiding, the capabilities of the receiver can be substantially improved. The proposed approach is distinct from the commonly used ultra-tightly coupled GPS/INS approaches and makes use of different tracking enhancement technologies used in typical HSGPS receivers, multichannel cooperated receivers and the current ultra-tightly coupled GPS/INS methods. Furthermore, the effects of inertial measurement unit (IMU) quality, receiver oscillator noise and coherent integration time on weak signal tracking are also analyzed. Simulated test results in both static and dynamic testes show that, the designed INS-aided GPS receiver can track the incoming weak GPS signals down to 15 dB-Hz without carrier phase locked, or 25 dB-Hz with carrier phase locked. When there are multiple strong GPS signals in view, the other weak signals can be tracked down to 15 dB-Hz with carrier phase locked.