A Diffraction Measurement Model and Particle Filter Tracking Method for RSS-Based DFL

2015 ◽  
Vol 33 (11) ◽  
pp. 2391-2403 ◽  
Author(s):  
Zhenghuan Wang ◽  
Heng Liu ◽  
Shengxin Xu ◽  
Xiangyuan Bu ◽  
Jianping An
2010 ◽  
Vol 24 (11) ◽  
pp. 1007-1011
Author(s):  
Xuezhi Xiang ◽  
Yu Peng ◽  
Zhiying Han ◽  
Zhihong Xi

2021 ◽  
Author(s):  
Amal Gunatilake ◽  
Karthick Thiyagarajan ◽  
sarath kodagoda ◽  
Lasitha Piyathilaka ◽  
Poojaben Darji

<div>Underground water pipes are important to any country’s infrastructure. Overtime, the metallic pipes are prone to corrosion, which can lead to water leakage and pipe bursts. In order to prolong the service life of those assets, water utilities in Australia apply protective pipe linings. Long-term monitoring and timely intervention are crucial for maintaining those lining assets. However, the water utilities do not possess the comprehensive technology to achieve it. The main reasons for lacking such technology are the unavailability of sensors and accurate robot localization technologies. Feature based localization methods such as SLAM has limited use as the application of liners alters the features and the environment. Encoder based localization is not accurate enough to observe the evolution of defects over a long period of time requiring unique defect correspondence. This motivates us to explore accurate contact-less and wireless based localization methods. We propose a cost-effective localization method using UHFRFID signals for robot localization inside pipelines based on Gaussian process combined particle filter. Experiments carried out in field extracted pipe samples from the Sydney water pipe network show that using the RSSI and Phase data together in the measurement model with particle filter algorithm improves the localization accuracy up to 15 centimeters precision.</div>


2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Fei Cai ◽  
Hongqi Fan ◽  
Qiang Fu

A particle filter based track-before-detect (PF-TBD) algorithm is proposed for the monopulse high pulse repetition frequency (PRF) pulse Doppler radar. The actual measurement model is adopted, in which the range is highly ambiguous and the sum and difference channels exist in parallel. A quantization method is used to approximate the point spread function to reduce the computation load. The detection decisions of the PF-TBD are fed to a binary integrator to further improve the detection performance. Simulation results show that the proposed algorithm can detect and track the low SNR target efficiently. The detection performance is improved significantly for both the single frame and the multiframe detection compared with the classical detector. A performance comparison with the PF-TBD using sum channel only is also supplied.


2012 ◽  
Vol 51 (4) ◽  
pp. 1 ◽  
Author(s):  
Yu Liu ◽  
Shiming Lai ◽  
Bin Wang ◽  
Maojun Zhang ◽  
Wei Wang

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