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A Research on TOA Three Dimensional Orientation Algorithm in View of MUSIC.doc

1、1A Research on TOA Three Dimensional Orientation Algorithm in View of MUSICAbstract. MUSIC algorithm refers to the use of covariance matrix (Rx) of received data so as to separate signal subspace and noise subspace, and to the use of the direction vector of signal and the orthogonality of noise subs

2、pace to form space scanning spectrum, and then conduct a whole domain research of spectrum peak so as to realize the parameter estimation of signals. TOA is a standard of judgment on the speed rate of signal transmission, which is feasible to be used as a calculation index of three dimensional orien

3、tation algorithms. This paper firstly introduces the characteristics of MUSIC and three dimensional orientation algorithm, on the base of which carries out a research on the TOA of MUSIC, so as to hope to inspire the follow-up work. Key words: MUSIC; TOA; Three dimensional orientation algorithm; res

4、earch Introduction Communication science and technology is one of the main subjects of modern social researches, the application of which 2can meet the requirements of information transmission, thus facilitating the functional needs of the users transmission signals in different time and position. W

5、ith the rapid development of science and technology, wireless communication, as the leader of new signal processing technology, is applied to ensure the efficiency of digital signal, which adopts data model with a higher level and computation methods. Spatial spectrum estimation algorithm (MUSIC) is

6、 a relatively adaptable way of calculation, by which carries out calculation estimation for the problems such as the arrival time in the three dimensional orientation algorithm (TOA) and performs a relatively better calculation efficiency. Characteristics of the MUSIC Its relatively higher error rat

7、e of signal result for traditional signal processing with the selection error of calculation method. MUSIC algorithm refers to the use of covariance matrix (Rx) of received data so as to separate signal subspace and noise subspace, and to the use of the direction vector of signal and the orthogonali

8、ty of noise subspace to form space scanning spectrum, and then conduct a whole domain research of spectrum peak so as to realize the parameter estimation of signals. According to the feedback data 3of practical application, the adoption of MUSIC algorithm has many functional advantages, which can pr

9、ovide reliable guarantee for TOA algorithm research, as is shown in figure 1. 1. The basic function: MUSIC algorithm is not a new kind of algorithm. In fact, it refers to the new methods listing on the basis of a certain calculation method, which adopts spatial spectrum estimation approach to cope w

10、ith the corresponding data signal. The application of MUSIC algorithm must resort to protocols agreed by mutual signal and play a real role in accordance with the corresponding data processing. Usually, the covariance matrix is used to separate signal space, and then rearrange the signal and noise s

11、ubspace so as to reflect the detailed results of signal calculation. 2. Noise immunity function: the early selected signal spectrum estimation method has a weak resistance to noise interference resistance, so that it can not accurately analyze the coding information of communication signal and it ha

12、s difficulty in mastering the specific signal transmission location. MUSIC algorithm designs multi-channel transmission approach, implements asymptotical un-deviation estimator according to signal strength and masters the calculation characteristics of the data signals. In addition, the spatial spec

13、trum estimation algorithm can also 4shield the source of interference in vicinity timely to ensure effective utilization of the signal Space. 3. wireless function: The MUSIC algorithm characteristics, from the judgment of determination direction , also has the infinite lateral features and ultimatel

14、y receives a scanning result corresponding to the actual signal without following the fixed signal path to make spatial spectrum estimation. For example, MUSIC algorithm can refer to the function characteristic between signal amount and noise space, and automatically generate the corresponding spati

15、al scanning spectrum, and then automatically search through a wide range of space to accurately evaluate the predetermined signal. Summary of TOA At present, the communication industry fundamentally realizes a reformation adjustment that wireless communication network replaces the cable communicatio

16、n network. The wireless network transmission will become the inevitable outcome of science and technology. Sensor is the main device to transmit and process the data signal. Its a must to speed up the research on the application of three dimensional orientation algorithm because of its constant opti

17、mization and upgrading in the function. TOA is a standard of judgment on the speed rate 5of signal transmission, which is feasible to be used as a calculation index of three dimensional localization algorithm. 1. The three dimensional network. Three-dimensional network is designed as a platform of n

18、ode transmission, and meanwhile an exclusively sole ID is equipped based on the node. Signal node is used to sign ID as anchor, some unfamiliar or unknown node as the un-known. Queue suitable to node is established, with a null initial condition. As for the unfamiliar or unknown nodes, its previousl

19、y ordered to set a standardized beacon node table. This TOA uses table 1. 2. Message sending. In wireless sensor network (WSN), to the beacon node to execute commands sent the hello message, several key parameters must necessarily be included to send the hello message with the commands of beacon nod

20、e: the ID, the 3 d coordinates, transmission speed rate, a process with the index of parameters in table 1. For unknown nodes, they are prepared to being dealt with message receiving, and the detailed addresses of the above three parameters are recorded and stored in the beacon nodes table as a new

21、reference data so that we can prepare for TOA assessment. 3. Data reading. After the calculation of the beacon nodes and space distance, useful data signal is read and dealt again with TOA. Known node has no 6obvious change in the orientation, while the unknown node orientation takes the initiative

22、to convert signs to the anchor, and be used as a new node so as to facilitate the three-dimensional orientation of other nodes data. On this basis, a new message is sent with the process above. Research on the three-dimensional orientation algorithm in view of MUSIC Wireless communication technology

23、 research in the new period has made remarkable achievements, and there have been more and more applications of all kinds of calculation methods in the measurement of the space signal, so the wireless network marks the improvement in application value of communication signal transmission. In view of

24、 the continually increasing number of wireless signal transmission users insomuch that the single signal positioning mode has been unable to adapt to the new network load requirements, so it is necessary to choose a higher level of network signal platform. The key lies in the arrival time of signal

25、with the combination of signals practical experience, which can judge the efficiency of signal transmission. The MUSIC algorithm is proposed to apply to the research on TOA calculation, which can play a role with the necessity of scientific computing process. Specific algorithm 7steps are as below.

26、1. The node set. As the operation requirements of MUSIC algorithm, the nodes location should be set in advance as shown in figure 3 to prepare correspondingly for related to the later calculation. After the nodes setting, the network initialization configuration will optimize the network linking to

27、the wireless sensor. Beacon nodes broadcast messages to the network, and meanwhile the unknown nodes monitor the information of beacon nodes. The received information from unknown nodes should be updated at any time in case of the error influence caused by the topology changes in Okada network. Mean

28、while, the set node should be effectively stored to facilitate the operation of automatic processing among the same nodes. 2. Coordinate entry. Data coordinate is set to better judge the calculation results so as to rapidly reflect the results of data processing, as is shown in Figure 4. MUSIC appli

29、cation to TOA has strict coordinate requirements; the number of beacon nodes monitored by he unknown node M is generally set as n (n = 0, 1, 2, 3, 4, 5, 6.), with he coordinates of beacon nodes A1, A2, A3, A4. An. The unknown node will store the monitored beacon node coordinates in the array and sta

30、rt the next step if 8n is less than 5. In the process of coordinate entry, the node coordinate should be automatically screened and selected. 3. Real-time monitoring. Signal monitoring should be added in the operation of TOA to estimate the process of the signal band transmission in different nodes

31、quantity and provide a relatively stable transmission environment for signal calculating. For example, when n is 4, 3 or 2, i.e. the unknown node can only monitor 4, 3 or 2 beacon nodes. The beacon node monitored by unknown nodes can be regarded as the ball center, and the communication distance as

32、the ball radius, with two balls respectively intersected, to calculate the barycenter in overlap region by 4 spheres, 3 spheres, 2 spheres as unknown node coordinates. 4. The set coordinates. According to the coordinate data obtained by calculation, the time in the TOA can de determined to actually

33、reflect the processing of the signal transmission in wireless sensor. E.g., Picking 4 nodes from n beacon nodes to form i tetrahedrons ( i = 1, 2, 3, 4, ., C4n), resulting in getting all tetrahedrons including all the unknown nodes, according to the overlapping area of tetrahedral intersection, calc

34、ulating the coordinates of the barycenter of this overlapping area as the coordinates of the unknown nodes. 9Thus, the users can grasp the detailed coordinates of three-dimensional algorithm so as to provide a reference for the signal calculation. Conclusion Wireless Communication Technology is the

35、main trend of the information transmission. It is an important research object of the wireless communications technology transmission to apply wireless sensor network node algorithm to orientate. With the TOA of MUSIC, the time of signal arrival can be accurately calculated so as to provide a valid

36、reference for data processing and evaluation. Acknowledgment This work is supported by the Science Research and Technology Development Project of Wuzhou City Guangxi Province of China under Grant No. 201201025-2. References 1 Lv Liang-bin, Cao Yang, Gao Xun, Luo Hui, Three dimensional orientation al

37、gorithm of sensor network in view of spherical shell intersectionJ. Journal of Beijing University of posts and telecommunications, 2006, (S1). 2 Chen Wan-ming, MeiTao, Meng Qing-hu, Liang hua-wei, LiuYuMei, An iteration orientation algorithm based on 10multidimensional scaling in wireless sensor net

38、work J. Journal of sensing technology, 2007, (05). 3 Sun Pei-gang, Zhao hai, Luo Ding-ding, Zhang Xi-yuan, An estimation model of communication link in wireless sensor network J. Journal of northeastern university (natural science edition), 2007, (07). 4 Chen Qian, Wang Xiao-dong, Zhou Xing-ming, Lo

39、cal orientation in ANGEPS system: Three dimensional GPS-free orientation algorithm of single hop ad-hoc network J. Electronic journals, 2004, (09). 5 Dai Gui-lan; Zhao Chong-chong, Qiu Yan, A three-dimensional orientation mechanism of the wireless sensor network (WSN) in view of spherical coordinate

40、s J. Electronic journals, 2008, (07). 6 Shi Jun-feng, Zhong Xian-xin, Chen Shuai, Shao Xiao-liang, The analysis of the structure and characteristics of Wireless sensor networkJ. Journal of Chongqing university (natural science edition), 2005, (02). 7 Liu Li-jun, Han Yan, Of Newton iteration source orientation algorithm based on the least squares algorithm J. The journal of projectile guidance, 2006, (03).

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