A per-survivor phase acquisition and tracking algorithm for detection of TCM signals with phase jitter and frequency error

1997 ◽  
Vol 45 (11) ◽  
pp. 1381-1384 ◽  
Author(s):  
E.S. Esteves ◽  
R. Sampaio-Neto
Keyword(s):  
Tracking Algorithm ◽  
Frequency Error ◽  
Phase Jitter

A filter algorithm for receiver tracking loops assisted by inertial information

2021 ◽  
pp. 1-11
Author(s):  
Zhifeng Han ◽  
Zheng Fang
Keyword(s):  
Integration Time ◽  
Frequency Error ◽  
Loop Filter ◽  
Signal Tracking ◽  
Phase Jitter ◽  
Loop Bandwidth ◽  
Tracking Ability ◽  
Negative Effect ◽  
Tracking Loops ◽  
Signal Environment

Abstract In traditional satellite navigation receivers, the parameters of tracking loop such as loop bandwidth and integration time are usually set in the design of the receivers according to different scenarios. The signal tracking performance is limited in traditional receivers. In addition, when the tracking ability of weak signals is improved by extending the integration time, negative effect of residual frequency error becomes more and more serious with extension of the integration time. To solve these problems, this paper presents out research on receiver tracking algorithms and proposes an optimised tracking algorithm with inertial information. The receiver loop filter is designed based on Kalman filter, reducing the phase jitter caused by thermal noise in the weak signal environment and improving the signal tracking sensitivity. To confirm the feasibility of the proposed algorithm, simulation tests are conducted.

scholarly journals Vector Tracking Algorithm Based on Adaptive Cubature Kalman Filter

2018 ◽  
Vol 36 (6) ◽  
pp. 1108-1115
Author(s):  
Xiaojun Zou ◽  
Baowang Lian ◽  
Zesheng Dan
Keyword(s):  
Kalman Filter ◽  
Carrier Frequency ◽  
Phase Error ◽  
Tracking Algorithm ◽  
Frequency Error ◽  
Test Results ◽  
Tracking Loop ◽  
Cubature Kalman Filter ◽  
Vector Tracking ◽  
Present Algorithm

In the vector tracking loop, there is a great error in the output of discriminator owing to the disturbance of noise. Cubature Kalman filter is proposed to replace the discriminator to process I/Q data and generate code phase error and the carrier frequency error in this paper. The present algorithm not only can avoid the nonlinear problem of discriminator, but also can reduce the bad effect of noise. Moreover, using cubature Kalman filter to deal with the nonlinear I/Q data is beneficial to preserve the accuracy of data processing. Because noise is unknown or time-varying, the filter should have the ability to respond to the changes of environmental noise. The innovation of measurements is used to estimate the covariance matrix of measurement noise in real time. Finally, a comparison is carried out between the present algorithm and the vector tracking algorithm based on discriminator. The test results show that the code phase error and the carrier frequency error are smaller, and the accuracy of navigation solution is also higher.

New LQG based Vector Tracking Algorithm using Additional Tracking Loops for High Disturbances Environment

2017 ◽  
Author(s):  
Minhuck Park ◽  
Sanghoon Jeon ◽  
Beomju Shin ◽  
Heekwon No ◽  
Changdon Kee ◽  
...  
Keyword(s):  
Tracking Algorithm ◽  
Vector Tracking ◽  
Tracking Loops

Automatic CamShift tracking algorithm based on multi-feature

2010 ◽  
Vol 30 (3) ◽  
pp. 650-652 ◽  
Author(s):  
Xuan LU ◽  
Hang LEI ◽  
Zong-bo HAO
Keyword(s):  
Tracking Algorithm

Robust tracking algorithm based on multi-feature fusion and particle filter

2010 ◽  
Vol 30 (3) ◽  
pp. 643-645 ◽  
Author(s):  
Wei ZENG ◽  
Gui-bin ZHU ◽  
Jie CHEN ◽  
Ding-ding TANG
Keyword(s):  
Particle Filter ◽  
Feature Fusion ◽  
Tracking Algorithm ◽  
Robust Tracking
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