A novel angle computation and calibration algorithm of bio-inspired sky-light polarization navigation sensor

Navigation plays a vital role in our daily life. As traditional and commonly used navigation technologies, Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) can provide accurate location information, but suffer from the accumulative error of inertial sensors and cannot b...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2014-09, Vol.14 (9), p.17068-17088
Main Authors: Xian, Zhiwen, Hu, Xiaoping, Lian, Junxiang, Zhang, Lilian, Cao, Juliang, Wang, Yujie, Ma, Tao
Format: Article
Language:English
Subjects:
Algorithms
angle computation
Animals
bio-inspired navigation sensor
Biomimetics - instrumentation
Biomimetics - methods
Calibration
China
Compasses
Geographic Information Systems - instrumentation
Geographic Information Systems - standards
Insects
Light
Navigation systems
Neurons
Photoreceptors
polarization skylight
Refractometry - instrumentation
Refractometry - standards
sensor calibration
Sensors
Spatial Navigation
Sunlight
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Summary:Navigation plays a vital role in our daily life. As traditional and commonly used navigation technologies, Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS) can provide accurate location information, but suffer from the accumulative error of inertial sensors and cannot be used in a satellite denied environment. The remarkable navigation ability of animals shows that the pattern of the polarization sky can be used for navigation. A bio-inspired POLarization Navigation Sensor (POLNS) is constructed to detect the polarization of skylight. Contrary to the previous approach, we utilize all the outputs of POLNS to compute input polarization angle, based on Least Squares, which provides optimal angle estimation. In addition, a new sensor calibration algorithm is presented, in which the installation angle errors and sensor biases are taken into consideration. Derivation and implementation of our calibration algorithm are discussed in detail. To evaluate the performance of our algorithms, simulation and real data test are done to compare our algorithms with several exiting algorithms. Comparison results indicate that our algorithms are superior to the others and are more feasible and effective in practice.
ISSN:1424-8220
1424-8220
DOI:10.3390/s140917068