Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Reliability of a navigation system is one of great importance for navigation purposes. Therefore, an integrity monitoring system is an inseparable part of aviation navigation system. Failures or faults due to malfunctions in the systems should be detected and repaired to keep the integrity of the system intact. According to the characteristic of GPS (Global Positioning System) receiver noise distribution and particle degeneracy and sample impoverishment problem in particle filter, an improved particle filter algorithm based on genetic algorithm for detecting satellite failures is proposed. The combination of the re-sampling method based on genetic algorithm and basic particle filter is used for GPS receiver autonomous integrity monitoring (RAIM). Dealing with the low ight particles on the basis of the genetic operation, genetic algorithm is used to classify the particles. It brings the selection, crossover and mutation operation in genetic algorithm into the basis particle filter .The method for detecting satellite failures which affect only subsets of system measurement. In addition to a main particle filter, which processes all the measurements to give the optimal state estimate, a bank of auxiliary particle filters is also used, which process subsets of the measurements to provide the state estimates which serve as failure detection references. The consistency of test statistics for detection and isolation of satellite fault is established. The failure detection is undertaken by checking the system state logarithmic likelihood ratio (LLR). The RAIM algorithm combined the genetic particle filter and the likelihood method is illustrated in detail. Experimental results based on GPS real raw data demonstrate that the algorithm under the condition of non-Gaussian measurement noise can improve the accuracy of state estimation, effectively detect and isolate fault satellite, improve the performance of the fault detection. Experimental results demonstrate that the proposed approach is available and effective for GPS RAIM.
['Ershen Wang', 'Tao Pang', 'Zhixian Zhang', 'Pingping Qu']
I am writing a research paper on a idea GPS Receiver Autonomous Integrity Monitoring Algorithm Based on Improved Particle Filter
[{"from": "human", "value": "I am writing a research paper on a idea GPS Receiver Autonomous Integrity Monitoring Algorithm Based on Improved Particle Filter"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Reliability of a navigation system is one of great importance for navigation purposes. Therefore, an integrity monitoring system is an inseparable part of aviation navigation system. Failures or faults due to malfunctions in the systems should be detected and repaired to keep the integrity of the system intact. According to the characteristic of GPS (Global Positioning System) receiver noise distribution and particle degeneracy and sample impoverishment problem in particle filter, an improved particle filter algorithm based on genetic algorithm for detecting satellite failures is proposed. The combination of the re-sampling method based on genetic algorithm and basic particle filter is used for GPS receiver autonomous integrity monitoring (RAIM). Dealing with the low ight particles on the basis of the genetic operation, genetic algorithm is used to classify the particles. It brings the selection, crossover and mutation operation in genetic algorithm into the basis particle filter .The method for detecting satellite failures which affect only subsets of system measurement. In addition to a main particle filter, which processes all the measurements to give the optimal state estimate, a bank of auxiliary particle filters is also used, which process subsets of the measurements to provide the state estimates which serve as failure detection references. The consistency of test statistics for detection and isolation of satellite fault is established. The failure detection is undertaken by checking the system state logarithmic likelihood ratio (LLR). The RAIM algorithm combined the genetic particle filter and the likelihood method is illustrated in detail. Experimental results based on GPS real raw data demonstrate that the algorithm under the condition of non-Gaussian measurement noise can improve the accuracy of state estimation, effectively detect and isolate fault satellite, improve the performance of the fault detection. Experimental results demonstrate that the proposed approach is available and effective for GPS RAIM."}]