%0 Journal Article %1 Vanek1999 %A Vanek, B. J. %A Maybeck, P. S. %A Raquet, J. F. %D 1999 %J Proc. of the ION GPS Conf. %K GPS, acquisition, kalmanFilter, satnav tracking %P 2243-2252 %T GPS Signal Offset Detection and Noise Strength Estimation in a Parallel Kalman Filter Algorithm %X Measurements from Global Positioning System (GPS) satellites are subject to corruption by signal interference and induced offsets. This paper.presents two independent algorithms to ensure the navigation system remains uncorrupted by these possible GPS failures. The first is parameter estimation algorithm that estimates the measurement noise variance of each satellite. A redundant measurement differencing (RMD) technique provides direct observability of the differenced white measurement noise samples. The variance of the noise process is estimated and provided to the second algorithm, a parallel Kalman filter, which then adapts to changes in the real-world measurement noise strength. The parallel Kalman filter structure detects and isolates signal offsets in individual GPS satellites. The offset detection algorithm calculates test statistics on each of the filters and decides which satellites to use in the solution based on these statistics. The two algorithms contain several user-definedparameters thathave significant effects when adjusted. The various effects of parameter variation are described and a parameter set is chosen at which to evaluate the algorithms. The combined algorithm performs quite well in computer simulations.

@article{Vanek1999, abstract = {Measurements from Global Positioning System (GPS) satellites are subject to corruption by signal interference and induced offsets. This paper.presents two independent algorithms to ensure the navigation system remains uncorrupted by these possible GPS failures. The first is parameter estimation algorithm that estimates the measurement noise variance of each satellite. A redundant measurement differencing (RMD) technique provides direct observability of the differenced white measurement noise samples. The variance of the noise process is estimated and provided to the second algorithm, a parallel Kalman filter, which then adapts to changes in the real-world measurement noise strength. The parallel Kalman filter structure detects and isolates signal offsets in individual GPS satellites. The offset detection algorithm calculates test statistics on each of the filters and decides which satellites to use in the solution based on these statistics. The two algorithms contain several user-definedparameters thathave significant effects when adjusted. The various effects of parameter variation are described and a parameter set is chosen at which to evaluate the algorithms. The combined algorithm performs quite well in computer simulations.}, added-at = {2011-05-30T10:41:10.000+0200}, author = {Vanek, B. J. and Maybeck, P. S. and Raquet, J. F.}, biburl = {https://www.bibsonomy.org/bibtex/2705c9288e3082ff281bba34b12202dea/bmuth}, groups = {private}, interhash = {804e29e63a56cc6a165654e42b8fed47}, intrahash = {705c9288e3082ff281bba34b12202dea}, journal = {Proc. of the ION GPS Conf.}, keywords = {GPS, acquisition, kalmanFilter, satnav tracking}, owner = {bmuth}, pages = {2243-2252}, timestamp = {2014-08-11T22:37:44.000+0200}, title = {{GPS Signal Offset Detection and Noise Strength Estimation in a Parallel Kalman Filter Algorithm}}, username = {bmuth}, year = 1999 }