With the considerable increase of visible satellites for positioning, the fault detection and identification performance of Range Consensus (RANCO) algorithm for Receiver Autonomous Integrity Monitoring (RAIM) will significantly be improved. However, the calculation amount of RANCO algorithm will exponentially increase for the sharp addition of visible satellite subsets. This paper proposes a modified RANCO algorithm based on genetic algorithm (GA-RANCO) for RAIM to inhibit the exponentially expanded calculation amount. To reduce the calculation amount in searching the optimal minimal necessary subset (MNS), the preselection step is developed to speed up the convergence process of GA-RANCO. It is executed to exclude the chromosome-represented MNS for which the count of faulty satellites will exceed the upper limit of independent simultaneous satellite faults to be monitored. Mathematical simulations are introduced to determine the GA parameters, and simulation experiments under different schemes are designed to evaluate the performance of GA-RANCO algorithm. Results illustrate that the time consumption under a large number of visible satellites of GA-RANCO is much lower than that of RANCO and the faulty detection and identification performance of GA-RANCO is the same as that of RANCO.

Utilizing the least squares residuals (LSR) algorithm to detect the faulty satellite, the faulty satellite with a large characteristic slope will bring a high miss detection risk (MDR) and that with a small characteristic slope will bring a high false alert risk (FAR). However, the magnitude of characteristic slopes whether large or small is currently indefinite. In this paper, analyzing the MDR whether exceeding its allowable value or not, we propose the critical value of characteristic slopes to define the magnitude of a characteristic slope. The slope with the value larger than the critical one can be defined as a large slope whereas the slope with value smaller than the critical one can be defined as a small slope. To reduce the fault detection risk of the LSR algorithm, including the MDR caused by a large slope faulty satellite and the FAR caused by a small slope faulty satellite, a modified LSR algorithm based on the critical value of characteristic slopes is proposed. In the modified algorithm, the most potential faulty satellite is determined via correlation analysis. Then a subset fault detection methodology will be used to reduce the MDR when the most potential faulty satellite owns a large slope, whereas a threshold amplification fault detection methodology will be used to reduce the FAR when the most potential faulty satellite owns a small slope. The performance evaluation simulations of the modified LSR algorithm show that both the MDR caused by a large slope faulty satellite and the FAR caused by a small slope faulty satellite could be effectively reduced.

Feature extraction of cotton plant height based on DSM difference method

The availability assessment is an important step for onboard application in Receiver Autonomous Integrity Monitoring (RAIM)s. It is commonly implemented using the protection level (PL)-based method. This paper analyzes the deficiencies of three kinds of PL-based methods: RAIM availability might be optimistically or conservatively assessed using the classic-PL-base method; might be conservatively assessed using the enhanced-PL-based method, and neither be optimistically nor conservatively assessed using the ideal-PL-based method with the cost of large calculation amount on-board. An improved slope-based RAIM availability assessment method is proposed, in which the characteristic slope is designed as the assessment basis, and its threshold that can exactly match the integrity risk requirement is derived. The slope-based method has the same RAIM availability assessment result as the ideal-PL-based method. Moreover, because the slope threshold can be calculated offline and searched online, the on-board calculation burden can be reduced using the slope-based method. Simulation is presented to verify the theoretical analysis of the RAIM availability assessment performances for the three PL-based and the slope-based methods.