An Improved Position Determination Algorithm Based on Nonlinear Compensation for Ground-Based Positioning Systems

Abstract

In the absence of GNSS or when signals from satellites are blocked in harsh environments, a ground-based positioning system can be used to estimate the position of users and receivers. Nevertheless, ground-based systems suffer dramatic nonlinear error resulting from the linearization used in typical positioning algorithms. Robust positioning algorithms that are capable of handling strong nonlinearity cases are therefore of great value. In this paper, we propose an algorithm termed promoted iterative least-squares based on nonlinear-compensation (PILSBON) to effectively alleviate the influence of nonlinear effects. This algorithm is based on the accurate expression of the nonlinear error terms in the double-differenced pseudorange measurement model. In order to eliminate the effects of nonlinearity for targeted solutions, the PILSBON uses iterative numerical estimation to compensate for nonlinear error so that the nonlinear position determination is transformed into a linear model, which can then be estimated with a linear estimation algorithm. In this paper, we analyze the properties of the PILSBON and compare it to conventional solutions. Because of its specific strategy for nonlinearity, our results show that the PILSBON improves the overall accuracy by approximately 30% compared with conventional solutions according to statistic RMSE data from over 500 experiments and positions. Moreover, by deploying a practical ground-based positioning system with six transmitters on the rooftop of our laboratory building, we demonstrate that the PILSBON algorithm can be efficiently employed in real-world experiments.INDEX TERMS Nonlinear compensation, ground-based positioning system, positioning algorithm, differential pseudorange, least-squares estimation.

Weighted Direct Position Determination via the Dimension Reduction Method for Noncircular Signals

“…From the figures, the proposed NRD-WSDF algorithm can estimate the targets successfully with fewer array elements, and the estimation accuracy becomes higher with the increase of array elements. is section compares the RMSE performance of different algorithms with different SNRs under different σ 2 error .…”

“…is section compares the RMSE performance of different algorithms with different snapshots under different σ 2 error . e number of snapshots changed from 10 to 460. e estimation is simulated when σ 2 error is 2 (Figure 11) and 50 (Figure 12).…”

“…As we all know, wireless position determination is a significant research work about signal processing, which has developed rapidly in recent years. It has been widely used in many fields including communication, radar, military, astronomy, and so on [1][2][3][4]. Research on wireless location can be divided into two categories: traditional two-step location technology and direct position determination technology (DPD).…”

A Holistic Approach to Guarantee the Reliability of Positioning Based on Carrier Phase for Indoor Pseudolite

“…Furthermore, since the pseudolite constellation is fixed, there are no ephemeris errors and relativistic effects. Therefore, the indoor single-frequency pseudolite DD observation equations can be formulated as [33][34][35], ∇∆P ks br = ∇∆ρ ks br + ∇∆e P + ∇∆M P ∇∆L ks br = λ 1 ∇∆ϕ ks br = ∇∆ρ ks br + ∇∆ε L + ∇∆m L + λ 1 ∇∆N ks br (1) where ∇∆ is a DD operator; r and b represent the rover and base stations, respectively. k and s represent pseudolites.…”