Shuqing Zeng

Shuqing Zeng

We consider the problem of carrier-phase differential GPS positioning for an land vehicle navigation system (LVNS), tightly coupled with an inertial measurement unit (IMU) and a speedometer. The primary focus is to apply Bayesian network to an IMU-aided GPS positioning system based on carrier-phase differential GPS. We describe the implementation details of the positioning system that integrates GPS measurements (i.e., pseudo-range, carrier-phase and doppler), IMU measurements, and speedometer measurements. We derive the linearized state process equation and the measurement equation for GPS and speedometer. To account for constraints of land vehicle, we add two more pseudo measurements to ensure the perpendicular velocities close to zero.

Shuqing Zeng

Sensor fusion of multiple sources plays an important role in vehicular systems to achieve refined target position and velocity estimates. In this article, we address the general registration problem, which is a key module for a fusion system to accurately correct systematic errors of sensors. A fast maximum a posteriori (FMAP) algorithm for joint registration-tracking (JRT) is presented. The algorithm uses a recursive two-step optimization that involves orthogonal factorization to ensure numerically stability. Statistical efficiency analysis based on Cramèr-Rao lower bound theory is presented to show asymptotical optimality of FMAP. Also, Givens rotation is used to derive a fast implementation with complexity O(n) with $n$ the number of tracked targets. Simulations and experiments are presented to demonstrate the promise and effectiveness of FMAP.

Shuqing Zeng

We address the problem of estimating a rigid transformation between two point sets, which is a key module for target tracking system using Light Detection And Ranging (LiDAR). A fast implementation of Expectation-maximization (EM) algorithm is presented whose complexity is O(N) with $N$ the number of scan points.