An adaptive unscented kalman filter for tightly-coupled INS/GPS integration

Download

index.pdf

Date

2012

Author

Akça, Tamer

Metadata

Show full item record

Item Usage Stats

307
views

170
downloads

In order to overcome the various disadvantages of standalone INS and GPS, these systems are integrated using nonlinear estimation techniques and benefits of the two complementary systems are obtained at the same time. The standard and most widely used estimation algorithm in the INS/GPS integrated systems is Extended Kalman Filter (EKF). Linearization step involved in the EKF algorithm can lead to second order errors in the mean and covariance of the state estimate. Another nonlinear estimator, Unscented Kalman Filter (UKF) approaches this problem by carefully selecting deterministic sigma points from the Gaussian distribution and propagating these points through the nonlinear function itself leading third order errors for any nonlinearity. Scaled Unscented Transformation (SUT) is one of the sigma point selection methods which gives the opportunity to adjust the spread of sigma points and control the higher order errors by some design parameters. Determination of these parameters is problem specific. In this thesis, effects of the SUT parameters on integrated navigation solution are investigated and an “Adaptive UKF” is designed for a tightly-coupled INS/GPS integrated system. Besides adapting process and v measurement noises, SUT parameters are adaptively tuned. A realistic fighter flight trajectory is used to simulate IMU and GPS data within Monte Carlo analysis. Results of the proposed method are compared with standard EKF and UKF integration. It is observed that the adaptive scheme used in the sigma point selection improves the performance of the integrated navigation system especially at the end of GPS outage periods.

Subject Keywords

Kalman filtering., Inertial navigation systems., Global Positioning System.

URI

http://etd.lib.metu.edu.tr/upload/12614049/index.pdf
https://hdl.handle.net/11511/21337

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

An Adaptive Unscented Kalman Filter For Tightly Coupled INS/GPS Integration Akca, Tamer; Demirekler, Mübeccel (2012-04-26) In order to overcome the various disadvantages of standalone INS and GPS, these systems are integrated using nonlinear estimation techniques. The standard and most widely used estimation algorithm for the INS/GPS integration is Extended Kalman Filter (EKF) which makes a first order approximation for the nonlinearity involved. Unscented Kalman Filter (UKF) approaches this problem by carefully selecting deterministic sigma points from Gaussian distributions and propagating these points through the nonlinear f...
Extended kalman filter based multi-purpose inertial sensor field calibration algorithm Yaman, Lisan Ozan; Azgın, Kıvanç; Department of Mechanical Engineering (2017) The Global Satellite Navigation System (GNSS) is widely adopted for common positioning system due to its precision, cost and effectiveness. Despite its advantages, GNSS receivers are susceptible to signal degradation both intentional cases such as jamming/spoofing and unintentional cases like signal blockage in urban environment due to tall buildings. On the other hand, dead reckoning navigation system such as Inertial Navigation System (INS) is immune to external interferences and it can supply continuous ...
Identification of inertial sensor error parameters Altınöz, Bağış; Leblebicioğlu, Mehmet Kemal; Department of Electrical and Electronics Engineering (2015) Inertial sensors (gyroscopes and accelerometers) that are used in navigation systems have distinct error characteristics such as bias, scale factor, random walk, etc. Calibration and characterization tests are done with 2 or 3 axes rate tables in order to identify these errors. It is possible to utilize error characteristics of these devices, and the navigation accuracy is directly dependent on the accuracy of this identification process. In this thesis, inertial sensor error parameters are identified by a ...
AN ADAPTIVE HYBRID ARQ SCHEME FOR SLOWLY TIME-VARYING COMMUNICATION CHANNELS MEMISOGLU, AT; BILGEN, S (1994-04-14) An adaptive hybrid ARQ scheme for slowly timevarying channels that aims to maximize the average throughput under a given reliability constraint is presented. Punctured convolutional codes and the Viterbi algorithm with the Yamemoto-Itoh retransmission protocol are employed for encoding and decoding, respectively. A procedure based on exponentially weighted moving averages is developed to detect channel state changes
Vector tracking loop design for GPS receivers Üzel, Deniz; Baykal, Buyurman; Department of Electrical and Electronics Engineering (2016) This study describes the design of a modern GPS receiver architecture based on vector tracking loops. Since the traditional tracking loops process the signals independently, there is no information exchange between channels. Due to that fact, aiding of weaker signals in the presence of relatively strong signals is impossible. On the other hand, vector tracking loops simultaneously process the signals from all visible channels. Therefore, they are able to perform better than the traditional tracking loops in...

Citation Formats

T. Akça, “An adaptive unscented kalman filter for tightly-coupled INS/GPS integration,” M.S. - Master of Science, Middle East Technical University, 2012.