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36th IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Zhang, Jun Jin, Tian Qiu, Lei Liu, Wenyan Zhou, Zhimin Natl Univ Def Technol Coll Elect Sci & Engn Changsha 410073 Hunan Peoples R China Collaborat Innovat Ctr Informat Sensing & Underst Xian 710071 Peoples R China

ISBN: (纸本)9781509033324

Multistatic radar system has a great potential for human detection and tracking for its fine localization precision, wide coverage and good observability. T-R-N (one transmitting antenna and N receiving antennas) radar system is the most popular multistatic radar structure. In this paper, the localization performance of T-R-N radar is evaluated using Cramer-Rao lower bound (CRLB). The localization precision of different radar topology types and different numbers of receiving antennas are compared. The localization performance is also evaluated by experimental data. The results reveal that more separated receiving antenna configurations and more numbers of receiving antennas have better localization precision.

关键词： Multistatic radar T-R-N (one transmitting antenna and N receiving antennas) radar system Cramer-Rao lower bound (CRLB) target localization taylor series algorithm

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A New Distance based algorithm for TDOA Localization in Cellular Networks

A New Distance based Algorithm for TDOA Localization in Cell...

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3rd IEEE International Conference on Computer Science and Information Technology (ICCSIT)

作者： Gong, Fuxiang Qing, Wang Zhang, Xiaoguo Southeast Univ Sch Instrument Sci & Engn Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781424455379

In wireless location area, taylor series algorithm is essential to find the solution to minimize the objective function the sum of squared TDOA measurement remains. This paper proposes a new objective function definition: the sum of squared distance from iterative point to each TDOA hyperbola. Then steepest descent method is used to find the optimized solution of the new model. In the end the two algorithms are compared using simulation tests under different environments. Results show that the new algorithm can achieve stabler and higher accuracy than taylor series algorithm especially under high noise environment.

关键词： taylor series algorithm Distance Based algorithm Line of Sight Non Line of Sight Time Difference of Arrival Steepest Descent Method

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A New Distance based algorithm for TDOA Localization in Cellular Networks

A New Distance based Algorithm for TDOA Localization in Cell...

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2010 3rd IEEE International Conference on Computer Science and Information Technology—ICCSIT 2010

作者： Fuxiang Gong School of Instrument Science and Engineering Southeast University Nanjing, China Wang Qing School of Instrument Science and Engineering Southeast University Nanjing, China Xiaoguo, Zhang School of Instrument Science and Engineering Southeast University Nanjing, China

In wireless location area, taylor series algorithm is essential to find the solution to minimize the objective function- the sum of squared TDOA measurement remains. This paper proposes a new objective function definition: the sum of squared distance from iterative point to each TDOA hyperbola. Then steepest descent method is used to find the optimized solution of the new model. In the end the two algorithms are compared using simulation tests under different environments. Results show that the new algorithm can achieve stabler and higher accuracy than taylor series algorithm especially under high noise environment.

关键词： taylor series algorithm Distance Based algorithm Line of Sight Non Line of Sight Time Difference of Arrival Steepest Descent Method

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taylor series method with numerical derivatives for initial value problems

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Journal of Computational Methods in Sciences and Engineering 2004年第1-2期4卷 105 - 114页

作者： E. Miletics G. Molnárka Department of Mathematics Széchenyi István University Györ Hungary

The taylor series method is one of the earliest analytic-numeric algorithms for approximate solution of initial value problems for ordinary differential equations. The main idea of the rehabilitation of these algorithms is based on the approximate calculation of higher derivatives using well-known technique for the partial differential equations. In some cases such algorithms will be much more complicated than a R-K methods, because it will require more function evaluation than well-known classical algorithms. However these evaluations can be accomplished fully parallel and the coefficients of truncated taylor series can be calculated with matrix-vector operations. For large systems these operations suit for the parallel computers. The approximate solution is given as a piecewise polynomial function defined on the subintervals of the whole interval and the local error of this solution at the interior points of the subinterval is less than that one at the end point. This property offers different facility for adaptive error control. This paper describes several above-mentioned algorithms and examines its consistency and stability properties. It demonstrates some numerical test results for stiff systems herewith we attempt to prove the efficiency of these new-old algorithms.

关键词： taylor series algorithm numerical derivatives parallel algorithms

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