Robust Unambiguous Estimation of High-Order BOC Signals: The DOME Approach

Abstract

This paper presents a novel unambiguous estimation technique of high‐order BOC signals, dubbed the Double Optimization Multi‐correlator‐based Estimator (DOME). The DOME is a robust alternative to other unambiguous BOC estimation techniques found in the literature, being able to operate in harsh propagation conditions typical of urban environments, while fully exploiting the BOC signal properties. The approach followed consists of the solution of two parallel and dependent optimization problems in which N samples of the correlation function are exploited, solving the ambiguity problem at the same time that the high‐order BOC accuracy is preserved. The preliminary performance assessment of the DOME in both controlled and realistic propagation conditions is presented, demonstrating the robustness and accuracy of the approach proposed. Copyright © 2016 Institute of Navigation

Mitigation of false locks in the acquisition of high-order BOC signals in HS-GNSS receivers

“…To solve the problem of unambiguous estimation, we propose to use the ML estimator and the LS estimator. Although, these estimators have been already proposed [2] and [6], they have been applied from a point of view of the tracking stage. However, in this document, we use these estimators from a point of view of acquisition where PDI techniques must be used to detect the signal.…”

“…That is, we can apply the ML estimator taking into account the covariance matrix of the noise. Then, the cost function can be reformulated as follows [6]:…”

“…Different works have tried to mitigate the probability of false lock at the tracking stage by applying various methods such as the Bump Jumping [3], the Double Estimator [4] and the Code-Subcarrier Smoothing [5]. Lately, also an open-loop multi-correlator approach, namely the Double Optimization Multi-correlator-based Estimator (DOME) [6] [7] has been proposed for solving the unambiguous tracking estimation problem using as baseline the Maximum Likelihood (ML) estimator. Nonetheless, less attention has been paid to the problem of the main peak detection or of unambiguous estimation at acquisition stage.…”

“…Then, the received signal suffers some variations in the Doppler frequency, which might cause a degradation in the performance of PDI techniques. On the other hand, after the signal detection by using the NPDI method or the DPDI method, we propose to apply estimators using as baseline the Least Square (LS) and the ML approaches, used for the unambiguous tracking estimation of high-order BOC signals in [2] and [6], respectively, to solve the unambiguous estimation problem at acquisition stage.…”

Collective Unambiguous Positioning With High-Order BOC Signals

“…In general, these techniques are well suited for mild propagation conditions typical of open-sky scenarios, but start having limitations or become unstable in urban scenarios where low C/No conditions (typically below around 30 dB-Hz) are experienced by the receiver [9]. Indeed, it is important to highlight that just additive white Gaussian noise (AWGN) channel conditions, without the need of additional multipath components, are enough to trigger the appearance of false locks given the structure of the high-order BOC signals [1], [10].…”