An unmanned, passive, and free of GNSS or similar external reference aides, sensing system is proposed for navigation of mobile vehicles. The sensor involves a new low-cost, accurate gravimeter that provides micro-gravity measurements. Although navigation using gravimeters has been studied in the past, no such system exists that can offer the advantages of the proposed technology in terms of cost, accuracy and size. A robust relative nonlinear filter that ingests sensor outputs as filter inputs will be designed, providing a capability for precise Earth-relative navigation. The newly derived filter, called the geometric extended Kalman filter, provides physically consistent estimates, unlike all existing filter formulations, while also providing faster convergence rates than currently used linearized filters. Simulation studies will be performed to assess the accuracy of the passive sensing system combined with standard inertial measurement units (IMUs), which include three-axis gyroscopes and accelerometers. The states to be estimated include Earth-referenced position, attitude, and their respective rates, in addition to IMU calibration parameters such as biases and scale factors. Conceptual design studies to transition the theoretical research to realize the analysis and filter design, and signal processing and computing requirements, will be assessed in the base period. Hardware studies that include using developed error budgets and margin transfers to set requirements for the system configuration, as well as determining the final hardware configuration and tabulating performance predictions for various mission scenarios, will be assessed in the option period. The proposed work has the capability to achieve all the desired attributes for precision navigation without the use of external sensors.
Benefit: The benefit of the proposed work is an increased ability for navigation of vehicles without the use of externally-aided sensors such as the GNSS, which may be prone to interruptions and jamming. The study will bring about significant advances over existing systems because optimal passive sensor suites and navigation filters will be the output of the work. The application is based on rigorously derived error definitions, so that physically correct uncertainty bounds are also provided. When fully matured, commercial and military operators will benefit from the capability because the proposed work will provide a robust and reliable navigation system for any mobile vehicle to meet their navigation requirements. Commercial applications include any civilian or military applications, such as driverless vehicles and drones, that require navigation in the presence or absence of a GNSS or other external sensor. This is especially important with the mounting reliance and growing number of unmanned vehicle platforms.
Keywords: Micro-Gravity Sensing Capability, Micro-Gravity Sensing Capability, Robust Navigation Filter, Precise Navigation Using Passive Sensor
