Demonstration of Adaptive Extended Kalman Filter for Low-Earth-Orbit Formation Estimation Using CDGPS

Abstract

Carrier‐phase differential GPS is an ideal sensor for formation flying missions in low earth orbit since it provides a direct measure of the relative positions and velocities of the vehicles in the fleet. This paper presents results for a relative navigation filter that achieves centimeter‐level precision using a customized GPS receiver. A precise, robust extended Kalman filter estimates the relative states based on simple measurement models and a linear Keplerian propagation model. To increase the filter robustness in the face of environment uncertainty, adaptive method of maximum likelihood estimation (MMLE) algorithms are implemented. The adaptive filter accurately identifies the process and sensor noise covariances for the system. Despite the simplicity of the filter, hardware‐in‐the‐loop simulations performed on the Formation Flying Testbed at Goddard Space Flight Center demonstrated that this filter can achieve ≅2 cm relative position accuracy and <0.5 mm/s relative velocity accuracy for a range of low‐earth‐orbit formation.

Explicit Model Predictive Control Approach for Low-Thrust Spacecraft Proximity Operations

“…The relative position observation model is based on the specifications of differential GPS and optical sensors [36,37], where the field of view of the optical sensor is assumed to be θ 30 deg. The standard deviation of the observation uncertainty is given, as a function of the along-track separation between the two spacecraft, in Fig.…”

Decentralized Estimation Algorithms for Formation Flying Spacecraft

“…Research is ongoing to invent fault detection and isolation routines that can sense failures and reconfigure systems to regain functionality [14,15]. In addition, highly accurate GPS estimators have been developed to estimate the relative positions and velocities to within 1 cm and 0.5 mm/s [16,17,18]. However, what has yet to be studied is the intricate interactions between all of the different algorithms required to execute a successful formation flying mission.…”

“…C&DH and modem hardware interfaces had been finalized, built and tested -software development was ongoing. The GPS hardware and estimation approach had been extensively tested on the NASA GSFC formation flying testbed [16,17,18].…”

“…Recent work on GPS estimators for relative navigation in LEO using Carrier-Phase Differential GPS (CDGPS) demonstrated a 1.0 cm accuracy in relative position and 0.5 mm/s in relative velocity [16,18,17]. These results were obtained using a fully decentralized filter, and the high levels of accuracy validate that While GPS can be used as an effective sensor for many ground, air and space applications, its viability relies on constant visibility of the NAVSTAR GPS constellation.…”

Low-end GPS Position Accuracy Enhancement Method by using Map Information

“…만약 무인 자동차가 위치 정보를 기반으로 경로 추종을 수 행해야 한다면 차선 구분이 가능할 정도의 위치 정확도가 제공되 어야 한다. 위치 정확도 향상을 위한 가장 쉬운 접근방법은 다양 한 오차에 대한 보정 알고리듬이 포함된 RTK(Real Time Kinematic)-GPS [4], A-GPS(Assisted GPS) [5], DGPS(Differential GPS) [6], CDGPS(Carrior phase DGPS) [7] …”