To address the importance of code-deviation threshold selection in signal quality detection, a code-deviation-based threshold selection algorithm is proposed, firstly, a code-deviation threshold calculation model is given, a threshold selection method based on maximum likelihood estimation is derived, a small amount of abnormal data is eliminated by the box plot method, and then the mean and Then, the mean and standard deviation of the overall data are estimated by the maximum likelihood estimation method, and the thresholds that conform to the overall data distribution are calculated. The results show that the detection of code-carrier divergence can effectively identify the abnormal signals, prove the rationality of the threshold selection, solve the problem that the traditional threshold model is too conservative and less accurate, and improve the reliability of the threshold. 

Code-carrier divergence threshold selection algorithm

To address the importance of code-deviation threshold selection in signal quality detection, a code-deviation-based threshold selection algorithm is proposed, firstly, a code-deviation threshold calculation model is given, a threshold selection method based on maximum likelihood estimation is derived, a small amount of abnormal data is eliminated by the box plot method, and then the mean and Then, the mean and standard deviation of the overall data are estimated by the maximum likelihood estimation method, and the thresholds that conform to the overall data distribution are calculated. The results show that the detection of code-carrier divergence can effectively identify the abnormal signals, prove the rationality of the threshold selection, solve the problem that the traditional threshold model is too conservative and less accurate, and improve the reliability of the threshold.

Civil aviation transportation equipment is more convenient and faster than other transportation tools and is an essential part of intelligent transportation. It is significant to study the reliability of positioning information and enhance traffic safety. Advanced receiver autonomous integrity monitoring (ARAIM) can provide vertical guidance during the different navigation stages in civil aviation fields. The traditional multiple hypothesis solution separation (MHSS) algorithm distributes the probability of hazardous misleading information (PHMI) and probability of false alarm (PFA) uniformly over all visible satellites resulting in reduced global availability of ARAIM. Aiming at this problem, we proposed an adaptive simulated annealing particle swarm optimization (ASAPSO) algorithm to redistribute integrity and continuity risks and establish a protection level optimization model. Based on the real BeiDou navigation satellite system/global positioning system (BDS/GPS) data, the experimental results show that the optimized algorithm can reduce the vertical protection level (VPL), and the ARAIM global availability of BDS/GPS is improved by 1.73%∼2.73%. The optimized algorithm can improve the availability of integrity monitoring at different stages of the navigation system and provide a basis for ensuring the reliability of the positioning results.

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An Improved Adaptive Simulated Annealing Particle Swarm Optimization Algorithm for ARAIM Availability

To better understand the shallow sea geological information and avoid the risk caused by potential geo-disasters, the efficient offshore geological exploration methods are required. Better detection resolution can be obtained by using a spark source. As the foundation, the observation system plays an important role for geological detection. The influence of the variation of the parameters of the observation system on the detection accuracy is analysed theoretically. Then, the numerical simulations based on the finite difference method was applied, and imaging characteristics of observation system with different parameter were studied. For submarine acoustic exploration, the spark source with frequency over 200 Hz can obtain the clear reflections for geological interpretation; besides, the receiver array with the interval of 5 m–10 m helps to obtain better wave signals when the buried depth of a geological body is less than 300 m, and the width is more than 10 m. Based on numerical simulations, the observation system was optimized and designed. The results of numerical examples show that the accurate position information of the structure can be obtained by using the observation system proposed in this paper. Different imaging performances are obtained by adjusting the parameters of the observation system. On this basis, combined with directivity analysis, the optimal observation system parameters are proposed. Finally, the proposed observation system is used to image the fault model. The research results of this paper can provide reference for the observation system design in similar projects.

Observation System Optimization of Offshore Acoustic Exploration for Estimating Submarine Geological Structures via Directivity Analysis

In the Global Navigation Satellite System (GNSS), the multipath error affected by many aspects is the main error source that affects satellite navigation, and it is difficult to establish a much more accurate model to analyze it. Based on the ground multipath reflection model, it firstly deeply studies the influence of GNSS satellite orbit parameters on multipath fading frequency and establishes a multipath signal model related to satellite orbit parameters. Secondly, the influence of carrier phase cycle slip, receiver clock adjustment, and GNSS satellite orbit on multiparameter- (MP-) combined observations is analyzed in detail based on the measured data. Finally, aiming at the common phenomenon of code-carrier divergence in the Beidou system, the elevation-based pseudorange correction model and a sidereal filtering are built to correct the MP errors; experiments with measured data show that there is a fluctuation range reduction of 35.7% after sidereal filtering when the receiver reaches a steady state.

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Baowang Lian

Papers

A Multipath Processing Technology Based on Multiparameter-Combined Observation in GNSS