A5042618715- GNSS positioning and interference
- Satellite Communication Systems
- Space Satellite Systems and Control
- Inertial Sensor and Navigation
- Autonomous Vehicle Technology and Safety
- Robotic Path Planning Algorithms
- Wireless Communication Networks Research
- Advanced Frequency and Time Standards
- Air Traffic Management and Optimization
- Real-time simulation and control systems
- Vehicle Dynamics and Control Systems
University of California, Irvine
2022-2024
Irvine University
2023
A framework to exploit megaconstellation low Earth orbit (LEO) satellite signals of opportunity for navigation is developed. This framework, termed simultaneous tracking and (STAN), estimates the navigating vehicle's states simultaneously with orbiting LEO satellites. STAN employs a cognitive receiver that exploits downlink produce observables: pseudorange, Doppler, and/or carrier phase. These observables are fused through an extended Kalman filter (EKF) aid inertial system (INS) in tightly...
A hybrid analytical-machine learning (ML) framework for improved low Earth orbit (LEO) satellite prediction is developed. The assumes the following three stages. (i) LEO first pass: terrestrial receiver with knowledge of its position produces carrier phase measurements from received signals, enabling it to estimate time arrival. satellite's states are initialized simplified general perturbations 4 (SGP4)-propagated two-line element (TLE) data, and subsequently estimated via an extended...
A comprehensive study is performed for low Earth orbit (LEO) space vehicles (SVs) tracking by a receiver opportunistically extracting navigation observables from their downlink radio frequency signals. First, framework to characterize the LEO SVs orbital motion process noise covariance developed. Second, performance via an extended Kalman filter (EKF) analyzed Monte Carlo simulations three different sets of observables: 1) pseudorange, 2) Doppler, and 3) fused pseudorange Doppler...
A framework for refining the ephemerides of low Earth orbit (LEO) space vehicles (SVs) is presented. This based on a known receiver that tracks LEO SVs using pseudorange and Doppler measurements extracted from SVs' signals. procedure to determine process noise covariance motion developed. Monte Carlo simulations are performed demonstrate improvements in tracked over open-loop SGP4-propagated three measurement scenarios: (i) pseudorange, (ii) Doppler, (iii) Doppler. The improved subsequently...
An interacting multiple-model (IMM) estimator is developed to adaptively estimate the process noise covariance of low Earth orbit (LEO) satellite clocks for improved positioning. Experimental results are presented showing a stationary ground receiver localizing itself with carrier phase measurements from single Orbcomm LEO satellite. The IMM shown reduce localization error and improve filter consistency over two fixed mismatched extended Kalman filters (EKFs). Starting an initial position...
<div class="section abstract"><div class="htmlview paragraph">This paper studies the implementation and validation of control algorithms for an autonomous drag racing vehicle. The previously developed modeling equations are first implemented with in a realistic simulation environment complete synthetic sensor data decision-making algorithms. controller is then transformed into embedded on-board processing unit on-vehicle testing. Camera, lidar, radar investigated created to...