Signal Tracking Algorithm with Adaptive Multipath Mitigation and Experimental Results for LTE Positioning Receivers in Urban Environments

2021 ◽  
pp. 1-1
Author(s):  
Pai Wang ◽  
Yang Wang ◽  
Jade Morton
Keyword(s):  
Urban Environments ◽  
Tracking Algorithm ◽  
Experimental Results ◽  
Multipath Mitigation ◽  
Signal Tracking

scholarly journals Two-Step Galileo E1 CBOC Tracking Algorithm: When Reliability and Robustness Are Keys!

2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Aleksandar Jovanovic ◽  
Cécile Mongrédien ◽  
Youssef Tawk ◽  
Cyril Botteron ◽  
Pierre-André Farine
Keyword(s):  
Tracking Algorithm ◽  
Tracking Accuracy ◽  
Multipath Mitigation ◽  
Binary Offset Carrier ◽  
Signal Tracking ◽  
Gps Navigation ◽  
Tracking Process ◽  
Galileo Satellite ◽  
Navigation Signals ◽  
Reliability And Robustness

The majority of 3G mobile phones have an integrated GPS chip enabling them to calculate a navigation solution. But to deliver continuous and accurate location information, the satellite tracking process has to be stable and reliable. This is still challenging, for example, in heavy multipath and non-line of sight (NLOS) environments. New families of Galileo and GPS navigation signals, such as Alternate Binary Offset Carrier (AltBOC), Composite Binary Offset Carrier (CBOC), and Time-Multiplex Binary Offset Carrier (TMBOC), will bring potential improvements in the pseudorange calculation, including more signal power, better multipath mitigation capabilities, and overall more robust navigation. However, GNSS signal tracking strategies have to be more advanced in order to profit from the enhanced properties of the new signals.In this paper, a tracking algorithm designed for Galileo E1 CBOC signal that consists of two steps, coarse and fine, with different tracking parameters in each step, is presented and analyzed with respect to tracking accuracy, sensitivity and robustness. The aim of this paper is therefore to provide a full theoretical analysis of the proposed two-step tracking algorithm for Galileo E1 CBOC signals, as well as to confirm the results through simulations as well as using real Galileo satellite data.

A Tracking Window Adaptive Compressive Tracking Algorithm

2019 ◽  
Vol 33 (14) ◽  
pp. 1959045 ◽  
Author(s):  
Wenhao Wang ◽  
Mingxin Jiang ◽  
Xiaobing Chen ◽  
Li Hua ◽  
Shangbing Gao
Keyword(s):  
Texture Features ◽  
Candidate Region ◽  
Tracking Algorithm ◽  
Experimental Results ◽  
Scale Invariant ◽  
Compressive Tracking ◽  
Multi Scale ◽  
Feature Normalization ◽  
Object Region ◽  
Candidate Regions

In the original compression tracking algorithm, the size of the tracking box is fixed. There should be better tracking results for scale-invariant objects, but worse tracking results for scale-variant objects. To overcome this defect, a scale-adaptive compressive tracking (CT) algorithm is proposed. First of all, the imbalance of the gray and texture features in the original CT algorithm is balanced by the multi-feature method, which makes the algorithm more robust. Then, searching different candidate regions by using the method of multi-scale search along with feature normalization makes the features extracted from different scales comparable. Finally, the candidate region with the maximum discriminate degree is selected as the object region. Thus, the tracking-box size is adaptive. The experimental results show that when the object scale changes, the improving CT algorithm has higher accuracy and robustness than the original CT algorithm.

Target Scale Adaptation Based on Corner Registration

2014 ◽  
Vol 556-562 ◽  
pp. 4260-4263
Author(s):  
Bing Yun Dai ◽  
Hui Zhao ◽  
Zheng Xi Kang
Keyword(s):  
Kalman Filter ◽  
Target Tracking ◽  
Mean Shift ◽  
Tracking Algorithm ◽  
Experimental Results ◽  
Distance Ratio ◽  
Scale Adaptation ◽  
Mean Shift Algorithm

Target tracking algorithm mean-shift and kalman filter does well in tracking target. However, mean-shift algorithm may not do well in tracking the target which the size of target is changing gradually. Although some scholars put forward by 10% of the positive and negative incremental to scale adaptive,the algorithm can not be applied to track the target which gradually becomes bigger. In this paper, we propose registration corners of the target of the two adjacent frames, then calculate the distance ratio of registration corners.Use the distance ratio to determine the target becomes larger or smaller. The experimental results demonstrate that the proposed method performs better compared with the recent algorithms.

An Anti- Occlusion Tracking Algorithm Based on MCD Correlation Matching

2013 ◽  
Vol 718-720 ◽  
pp. 2005-2010
Author(s):  
Pu Liu ◽  
Chun Ping Wang ◽  
Qiang Fu
Keyword(s):  
Target Tracking ◽  
Template Matching ◽  
Tracking Algorithm ◽  
Experimental Results ◽  
Template Method ◽  
Target Movement ◽  
Movement Prediction ◽  
Tracking Algorithms ◽  
The Stability ◽  
Correlation Matching

In order to improve the stability of target tracking under occlusion conditions，on the basis of researching some target tracking algorithms, this paper presents an algorithm based on MCD correlation matching, which combines multi sub-templates matching and target movement prediction. Besides, for occlusion characteristics, corresponding template matching criterions and updating methods are put forward. Experimental results show that, comparing with the single template method which updating frame by frame, the proposed algorithm has a certain anti-occlusion ability with better stability and continuity of target tracking under occlusion conditions.

scholarly journals Part-Based Visual Tracking via Online Weighted P-N Learning

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Heng Fan ◽  
Jinhai Xiang ◽  
Jun Xu ◽  
Honghong Liao
Keyword(s):  
Visual Tracking ◽  
State Of The Art ◽  
The State ◽  
Tracking Algorithm ◽  
Local Feature ◽  
Experimental Results ◽  
Learning Method ◽  
Target Model ◽  
Tracking Process

We propose a novel part-based tracking algorithm using online weighted P-N learning. An online weighted P-N learning method is implemented via considering the weight of samples during classification, which improves the performance of classifier. We apply weighted P-N learning to track a part-based target model instead of whole target. In doing so, object is segmented into fragments and parts of them are selected as local feature blocks (LFBs). Then, the weighted P-N learning is employed to train classifier for each local feature block (LFB). Each LFB is tracked through the corresponding classifier, respectively. According to the tracking results of LFBs, object can be then located. During tracking process, to solve the issues of occlusion or pose change, we use a substitute strategy to dynamically update the set of LFB, which makes our tracker robust. Experimental results demonstrate that the proposed method outperforms the state-of-the-art trackers.

scholarly journals Multipath mitigation and NLOS detection using vector tracking in urban environments

GPS Solutions ◽  
2014 ◽  
Vol 19 (2) ◽  
pp. 249-262 ◽  
Author(s):  
Li-Ta Hsu ◽  
Shau-Shiun Jan ◽  
Paul D. Groves ◽  
Nobuaki Kubo
Keyword(s):  
Urban Environments ◽  
Multipath Mitigation ◽  
Vector Tracking

scholarly journals Research on Acquisition and Tracking Algorithm of Global Satellite Positioning Receiver Based on UWB

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Li Yang ◽  
Danshi Sun ◽  
Haote Ruan
Keyword(s):  
Influence Factor ◽  
Three Dimensional ◽  
Doppler Frequency ◽  
Pulse Generation ◽  
Tracking Algorithm ◽  
Tracking Accuracy ◽  
Signal Tracking ◽  
Satellite Positioning ◽  
Working Principle ◽  
Satellite Signal

In order to overcome the problems of the traditional algorithm, such as the time-consuming execution of acquisition instructions, low signal tracking accuracy, and low signal capture accuracy, a global satellite positioning receiver acquisition and tracking algorithm based on UWB technology is designed in this study. On the basis of expounding the pulse generation method and working principle in UWB technology, this paper analyzes in detail the characteristics of UWB technology, such as antimultipath, low power consumption, and strong penetration. Then, on the basis of window function filtering, in the process of three-dimensional search of global satellite positioning signal, firstly, the satellite signal entering the GPS software receiver is processed by RF front-end mixing and AD sampling, and then, the signal tracking and navigation message solving are completed according to the relationship between the influence factor and Doppler frequency offset. The experimental results show that the execution time of the acquisition instruction of the proposed algorithm varies between 1129 ms and 1617 ms; the signal tracking accuracy ranges between 0.931 and 0.951, and the signal capture accuracy ranges between 93.3% and 95.6%, which proves that the proposed algorithm has achieved the design expectation.

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