Current Issue : January - March Volume : 2015 Issue Number : 1 Articles : 4 Articles
TDDM (time division data modulation) technique will be used in the next generation GNSS (global navigation satellite system)\nto improve processing performance and to reduce inter-GNSS interference; however, the emergence of TDDM signal causes the\nestimation frequency and message reversal fuzz problems in the acquisition process of a GNSS receiver. At present, the traditional\nacquisition methods have some limitations and shortcomings. Therefore, aiming at the unique characteristics of TDDM signal, a\nfast acquisition algorithm is proposed to overcome these fuzz problems in this paper. In the proposed algorithm, three stages are\nobtained by some key technologies, which are the I-Q frequency compensation, superposition processing, subsection processing,\nand reversion position estimation. Besides, the algorithm is simulated from carrier frequency error, code phase error, message\ninversion error, and processing speed. Theoretical and simulation results show that the new algorithm can quickly overcome the\nfuzz problems, and the new algorithm is better than the existing algorithm in the speed and accuracy, which demonstrates that this\nnew algorithm is an effective search scheme for the next generation GNSS signals....
We propose a systematic framework for moving target positioning based on a distributed camera network. In the proposed\nframework, low-cost static cameras are deployed to cover a large region, moving targets are detected and then tracked using\ncorresponding algorithms, target positions are estimated by making use of the geometrical relationships among those cameras\nafter calibrating those cameras, and finally, for each target, its position estimates obtained from different cameras are unified\ninto the world coordinate system. This system can function as complementary positioning information sources to realize moving\ntarget positioning in indoor or outdoor environments when global navigation satellite system (GNSS) signals are unavailable. The\nexperiments are carried out using practical indoor and outdoor environment data, and the experimental results show that the\nsystematic framework and inclusive algorithms are both effective and efficient....
Satellite navigation is critical in signal-degraded environments where signals are corrupted and GNSS systems do not guarantee an\naccurate and continuous positioning. In particular measurements in urban scenario are strongly affected by gross errors, degrading\nnavigation solution; hence a quality check on the measurements, defined as RAIM, is important. Classical RAIM techniques work\nproperly in case of single outlier but have to be modified to take into account the simultaneous presence of multiple outliers.\nThis work is focused on the implementation of random sample consensus (RANSAC) algorithm, developed for computer vision\ntasks, in the GNSS context. This method is capable of detecting multiple satellite failures; it calculates position solutions based on\nsubsets of four satellites and compares them with the pseudoranges of all the satellites not contributing to the solution. In this\nwork, amodification to the original RANSA Cmethod is proposed and an analysis of its performance is conducted, processing data\ncollected in a static test....
A terminal of Compass Navigation Satellite System (CNSS), which can not only support Bei Dou-1 and BeiDou-2 but also support\nGlobal Positioning System (GPS), is designed to research the activities of the migrant birds, with our novel design of a multi band\nantenna. By a high-density integration, this terminal is designed with a compact size and light weight. When the terminal is\nassembled to a whooper swan, its flying trace is recorded by the CNSS, which is in agreement with that of GPS. The flying route\nmap based on the CNSS is useful to check the situation and habit of the migrant bird, which is important for animal protection and\nbird flu outbreak prediction....
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