Information Fusion for Positioning System With Location Constraint of Camera and UWB

In this paper, a fusion estimator is investigated for positioning systems with location constraint of a camera and an ultra-wideband (UWB). Local camera and UWB estimators are designed independently for positioning with missed detections and local UWB estimates are aligned to local camera estimates for fusion estimation. Next the location constraint of the camera and UWB is transformed to a state constraint by state extension, and a constrained estimation projection method is applied to construct a fusion estimator. To measure the accuracy of the designed constrained fusion estimator, it is demonstrated that the estimation error covariance of the proposed method is equal to that of the matrix-weighted fusion method. Moreover, it is found that the proposed method has significant advantages over the matrix-weighted fusion method in computational cost, which is crucial for the real-time requirements of perception systems. Finally, the effectiveness of the proposed fusion estimator is displayed by simulation results and experimental results on the positioning system for an Ackerman vehicle. Note to Practitioners—The proposed method aims to solve the challenges of missed detections and different location coordinates from two sensors in the positioning systems. The paper introduces independently designed local estimators for both the camera and UWB sensors, which are capable of handling missed detections. The local UWB estimates are aligned with the local camera estimates to ensure that local estimates from two sensors are time-aligned in the fusion process. The location constraint of the sensors is transformed into a state constraint through state extension for constructing the fusion estimator with the constrained estimation projection method. The paper demonstrates that the estimation error covariance of the proposed fusion estimator is equivalent to that of the traditional matrix-weighted fusion method. Moreover, the proposed method offers significant advantages in terms of computational cost, which is critical for real-time performance in perception systems. Practitioners can use the proposed fusion estimator to enhance the accuracy and reliability of positioning systems that incorporate two different sensors with missed detections and location constraint. The method is particularly well-suited for applications where real-time performance is a requirement.