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Indoor range finding positioning method based on improved traceless Kalman filtering

An unscented Kalman and Kalman filter technology, applied in radio wave measurement systems, positioning, measurement devices, etc., can solve the problems of non-line-of-sight errors and accuracy effects that cannot be suppressed

Active Publication Date: 2017-05-24
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

Early Hightower et al [HIGHTOWER J, WANT R, BORRIELLO G.SpotON: An Indoor 3D LocationSensing Technology Based on RF Signal Strength[D].UW CSE 00-02-02, University of Washington, Department of Computer Science and Engineering, Seattle, WA , 2000, 1] estimate the distance between two points by the received signal strength (RSSI, Received Signal Strength Indicator) ranging method, and locate by the mutual position between the nodes, but the indoor environment has a serious impact on the accuracy of the method
Literature [MINGHUI Z, HUIQING Z.Research on Model of IndoorDistance Measurement Based on Receiving SignalStrength[C] / / Computer Design and Applications (ICCDA), 2010International Conference on.IEEE, 2010,5:54-58] using linear regression analysis Two parameters in the distance model (RSSI value and path loss index at 1m distance from the transmitting node), but still cannot suppress the non-line-of-sight (NLOS) error

Method used

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  • Indoor range finding positioning method based on improved traceless Kalman filtering
  • Indoor range finding positioning method based on improved traceless Kalman filtering
  • Indoor range finding positioning method based on improved traceless Kalman filtering

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Embodiment

[0162] Set up two nodes in the laboratory, the transmitting node and the receiving node, and place them at the same height for data collection. The experimental range is 0-15m, and the measurement starts at 0.96m away from the transmitting node, and measures 100 RSSI at each interval of 0.96m. Value, the experimental data is processed accordingly, the distance value is the state value, the preprocessed RSSI value is the observation value, and the improved unscented Kalman filter method is used to obtain the distance value. The experimental results are as follows figure 2 , image 3 shown. From figure 2 and image 3It can be seen from the results that among the three processing methods, the data change of the improved unscented Kalman filter method (aukf) based on the logarithmic robust function is the largest, and the Kalman filter and the unscented Kalman filter (kf+ukf) are used to process The RSSI value, and the Kalman filter and the unscented Kalman filter improvement...

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Abstract

The invention discloses an indoor range finding positioning method based on improved traceless Kalman filtering, and the method comprises the steps: selecting the Kalman filtering to carry out the processing of a received RSSI value, and obtaining the optimal estimation of a state vector; carrying out the numerical fitting of the RSSI value, processed through the Kalman filtering, through the least square method, and obtaining two environment parameters A and m in a current test environment; carrying out the secondary processing of the RSSI value through the improved traceless Kalman filtering, and obtaining the value of the distance between an anchor node and a target node; and estimating the position coordinates of an unknown node through the solved distance value between the anchor node and the target node and a three-side measurement method. The method corrects the noise estimation value in the traceless Kalman filtering in real time through a robust target function, reduces the weight of an estimation value with the in accurate noise, and improves the state variable estimation precision.

Description

technical field [0001] The invention relates to an indoor ranging and positioning method based on an improved unscented Kalman filter, and belongs to the technical field of indoor ranging and positioning. Background technique [0002] In today's era, with the development of mobile communication and wireless sensor network technology, location-based services (Location-Based Services, LBS) have received widespread attention, such as the literature ERYA B O, RALPH WP. Theory and practice of simultaneous data reconciliation a Gross error detection for chemical processes [J]. Computers and Chemical Engineering, 2004, 28(3): 381-402. For outdoor positioning systems, the Global Navigation Satellite System (GNSS) can provide precise positioning and is widely used, such as the literature ZHEN L, FANG H J.Modified state prediction algorithm based on UKF[J].Journal of Systems Engineering and Electronics.2013 , 24(1):135-140. In densely built areas or complex indoor environments, due ...

Claims

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Application Information

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IPC IPC(8): G01S5/10
CPCG01S5/10
Inventor 陈晓邹胜男
Owner NANJING UNIV OF INFORMATION SCI & TECH
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