CN102359787A - WSN/MINS high-precision and real-time combination navigation information fusion method - Google Patents
WSN/MINS high-precision and real-time combination navigation information fusion method Download PDFInfo
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Abstract
The invention relates to a WSN/MINS high-precision and real-time combination navigation information fusion method, and belongs to the technical field of combined positioning under a complex environment. According to the method, a wireless positioning network is autonomously built under a closed and complex environment; a LS-SVM method is adopted to train a navigation error model of a MINS navigation system; when the MINS navigation system leaves the training area, the navigation system is compensated depending on the previous trained error model. In the prior art, the positioning precision of the conventional MINS navigation system generates the drift along with the time, and the effective training network can not be provided under the closed environment. With the present invention, the disadvantages and the problems of the conventional MINS navigation system in the prior art are overcome; the persistent high-precision and real-time navigation is provided; the method can be applicable for long-distance and high-precision target positioning and tracking in the indoor environment, the underground mine and other closed and complex environments.
Description
Technical field
The integrated navigation information fusion method belongs to combined orientation technology field under the complex environment when the present invention relates to a kind of WSN/MINS high-precision real.
Background technology
In recent years, the demand of unknown node precise position information has been promoted the development of placement technology, this trend will remain unchanged in the following a very long time.In existing locator meams, satellite navigation and inertial navigation are the most frequently used dual modes.Wherein (Global Positioning System GPS) is a kind of mode the most commonly used to GPS.Though GPS can pass through the continual and steady positional information of precision; The drawbacks limit of external environments such as but it is subject to electromagnetic interference (EMI), block influence its range of application; Particularly in some scenes airtight, circumstance complication such as indoor, underground passages; Gps signal is seriously blocked, and can't effectively work.Micro-inertial navigation system (MEMS inertial navigation system; MINS) have complete autonomous, movable information comprehensively, in short-term, high-precision advantage; Though can realize independent navigation, error accumulates in time, will cause navigation accuracy seriously to descend under the service condition during long the boat.In order to overcome the shortcoming that independent use MINS or GPS navigation equipment are produced, combine the advantage of the two, many scholars merge above-mentioned two kinds of navigate modes, have formed GPS/MINS integrated navigation technology.Though integrated navigation system can compensate GPS losing lock situation through MINS; But because the error of MINS accumulates in time; This compensation can only be the short-term compensation, in case system is under the situation of GPS losing lock for a long time, bearing accuracy is difficult to reach long-time steady state (SS).In order to obtain metastable bearing accuracy, many scholars are applied to some intelligent algorithms in the integrated navigation system, and this method can make navigational system keep long-time must stablizing, but its bearing accuracy has very big dependence to the selection of training space.Yet under environment such as indoor, underground passage, gps signal is very faint, is difficult to build suitable training space.
In recent years, (Wireless Sensors Network, WSN) characteristics with its low cost, low-power consumption and low system complexity show very big potentiality in the short distance positioning field to wireless sensor network.Adopt WSN to carry out the short distance location and become a research focus gradually.The WSN location needs two category nodes to accomplish the location jointly: anchor node and blind node.Wherein anchor node is the node of location aware, and blind node is the unknown node in position.Adopting location technology among the present WSN all is to accomplish through one or several wireless channel physical parameter of measuring between unknown node and the known node.In position fixing process, when needs obtained the positional information of blind node, blind node at first sent Location Request obtaining corresponding wireless channel physical parameter between itself and the anchor node to anchor node, and these parameter informations are converted into corresponding range information.Obtain after the corresponding range information, (estimate that like maximum likelihood (Maximum Likehood Estimate, MLE) etc.) calculates the relative position information of blind node and anchor node, its concrete steps are as shown in Figure 1 through some data fusion methods.Compare with the conventional positioning mode; Except characteristics with low cost, low-power consumption and low system complexity; WSN can also independently accomplish the establishment of network, and making to position in some scenes airtight, circumstance complication such as indoor, underground passages becomes possibility.
WSN is that the unknown node location under the closed environment provides possibility; But because the communication technology that WSN adopts is generally short-distance wireless communication technology (like ZigBee, WIFI etc.); Therefore if want to accomplish the target following location of long distance; Need a large amount of network nodes to accomplish jointly, this does not also meet the demand of WSN low cost, low-power consumption.Though MINS can accomplish independent navigation, broken away from not the shortcoming that bearing accuracy is drifted about in time.
Summary of the invention
In order to address the above problem; Integrated navigation information fusion method when the invention provides a kind of WSN/MINS high-precision real; Through under airtight complex environment, independently building the wireless location network, adopt the navigation error model training of least square support vector long-pending (LS-SVM method), when the MINS navigational system is left training space to the MINS navigational system; The error model of training compensates navigational system before relying on; Overcome the shortcoming that traditional MINS positioning precision of navigation system is drifted about in time, and the problem that effective training network can't be provided under closed environment, lasting high precision real-time navigation is provided.
The present invention adopts following technical scheme for solving its technical matters:
The integrated navigation information fusion method comprises the following steps: during a kind of WSN/MINS high-precision real
(1) integrated navigation system is divided into training space and adaptive equalization zone two parts; Described training space is the zone of building WSN, and described adaptive equalization zone is for having only the zone of MINS signal;
(2) at training space; Wireless location and MINS navigational system based on WSN are worked simultaneously; At first utilize the relative navigation information of measuring unknown node based on the wireless location technology of WSN, the absolute navigation information that obtains on relative navigation information and the micro-inertial navigation system is carried out data fusion through extended Kalman filter;
(3) adopting EKF to carry out data fusion; And when drawing optimum navigation information, wave filter is made the error model that control information feeds back to WSN and MINS respectively, to the WSN wireless location system; Error model can be revised the relative position and the speed of unknown node; And to the MINS system, the optimal estimation that position, velocity error and the wave filter that MINS self is estimated provides gives training through the LS-SVM intelligent algorithm, seeks the relation between the two;
(4) leave the zone of building WSN when unknown node and get into the adaptive equalization zone; In this zone; Integrated navigation system obtains the relative navigation information of measuring less than WSN; Can only rely on the MINS system to accomplish this a part of independent navigation, the error model that MINS is utilized in the training space training carries out error compensation to the absolute navigation information of measuring, and obtains optimum navigation information.
Beneficial effect of the present invention is following:
1, utilizes the relative navigation information of measuring based on the wireless location technology of WSN; Carry out data fusion with the absolute navigation information that obtains on the MINS through extended Kalman filter; The navigation information that obtains, the precision of information that obtains than above-mentioned any single air navigation aid is higher.
2, the MINS error model that is utilized in training space training carries out error compensation to the absolute navigation information of measuring, and obtains optimum navigation information, has avoided can't working because of the WSN navigation causing navigation error to descend, can't guarantee the problem of navigation accuracy fast.
3, can be used for indoorly, the length under the airtight complex environment such as underground mine is followed the tracks of apart from the high precision target localization.
Description of drawings
Fig. 1 is the node locating step based on WSN.
Fig. 2 is a training space integrated navigation model.
Fig. 3 is adaptive equalization zone integrated navigation model.
Embodiment
Below in conjunction with accompanying drawing the invention is explained further details.
Like Fig. 2 is training space integrated navigation model; At training space; Wireless location and MINS navigational system based on WSN are worked simultaneously; At first utilize the relative navigation information of measuring unknown node based on the wireless location technology of WSN, the absolute navigation information that obtains on relative navigation information and the micro-inertial navigation system is carried out data fusion through extended Kalman filter; Adopting EKF to carry out data fusion; And when drawing optimum navigation information, wave filter is made the error model that control information feeds back to WSN and MINS respectively, to the WSN wireless location system; Error model can be revised the relative position and the speed of unknown node; And to the MINS system, the optimal estimation that position, velocity error and the wave filter that MINS self is estimated provides gives training through the LS-SVM intelligent algorithm, seeks the relation between the two.Concerning the WSN wireless location system, error model can be revised the relative position and the speed of unknown node.And concerning the MINS system, the optimal estimation that position, velocity error and the wave filter that MINS self is estimated provides gives training, seeks the relation between the two.
When unknown node is left the zone of building WSN, then integrated navigation system gets into the adaptive equalization zone, and is as shown in Figure 3.In this zone, integrated navigation system obtains the relative navigation information of measuring less than WSN, can only rely on the MINS system to accomplish this a part of independent navigation.The error model that MINS is utilized in the training space training carries out error compensation to the absolute navigation information of measuring; Obtain optimum navigation information; Avoided causing navigation error to descend, can't guarantee the problem of navigation accuracy fast, had certain feasibility and perspective because of WSN navigates to work.
Claims (1)
1. integrated navigation information fusion method during a WSN/MINS high-precision real is characterized in that comprising the following steps:
(1) integrated navigation system is divided into training space and adaptive equalization zone two parts, described training space is the zone of building WSN, and described adaptive equalization zone is for having only the zone of MINS signal;
(2) at training space; Wireless location and MINS navigational system based on WSN are worked simultaneously; At first utilize the relative navigation information of measuring unknown node based on the wireless location technology of WSN, the absolute navigation information that obtains on relative navigation information and the micro-inertial navigation system is carried out data fusion through extended Kalman filter;
(3) adopting EKF to carry out data fusion; And when drawing optimum navigation information, wave filter is made the error model that control information feeds back to WSN and MINS respectively, to the WSN wireless location system; Error model can be revised the relative position and the speed of unknown node; And to the MINS system, the optimal estimation that position, velocity error and the wave filter that MINS self is estimated provides gives training through the LS-SVM intelligent algorithm, seeks the relation between the two;
(4) leave the zone of building WSN when unknown node and get into the adaptive equalization zone; In this zone; Integrated navigation system obtains the relative navigation information of measuring less than WSN; Can only rely on the MINS system to accomplish this a part of independent navigation, the error model that MINS is utilized in the training space training carries out error compensation to the absolute navigation information of measuring, and obtains optimum navigation information.
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| CN105737833A (en) * | 2016-05-13 | 2016-07-06 | 上海会志信息科技有限公司 | Indoor navigation method and indoor navigation device |
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| CN102682572A (en) * | 2012-03-27 | 2012-09-19 | 南京邮电大学 | Wireless sensor network positioning-based intelligent person nursing method |
| CN102679977A (en) * | 2012-06-20 | 2012-09-19 | 南京航空航天大学 | Distributive navigation unit based on inertia network and information fusion method thereof |
| CN104374389A (en) * | 2014-12-10 | 2015-02-25 | 济南大学 | Indoor mobile robot oriented IMU/WSN (inertial measurement unit/wireless sensor network) integrated navigation method |
| CN104374389B (en) * | 2014-12-10 | 2017-04-05 | 济南大学 | A kind of IMU/WSN Combinated navigation methods towards indoor mobile robot |
| CN105737833A (en) * | 2016-05-13 | 2016-07-06 | 上海会志信息科技有限公司 | Indoor navigation method and indoor navigation device |
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| CN109655060A (en) * | 2019-02-19 | 2019-04-19 | 济南大学 | Based on the KF/FIR and LS-SVM INS/UWB Integrated Navigation Algorithm merged and system |
| CN109655060B (en) * | 2019-02-19 | 2021-07-06 | 济南大学 | INS/UWB integrated navigation algorithm and system based on KF/FIR and LS-SVM fusion |
| CN109916401A (en) * | 2019-04-17 | 2019-06-21 | 济南大学 | Using the seamless tight integration navigation methods and systems of distribution of LS-SVM auxiliary EKF filtering method |
| CN109916401B (en) * | 2019-04-17 | 2021-03-12 | 济南大学 | Distributed seamless tight combination navigation method and system adopting LS-SVM assisted EKF filtering method |
| CN110530362A (en) * | 2019-09-05 | 2019-12-03 | 北京航空航天大学 | A kind of fireman's indoor orientation method based on single reference mode/inertia combination |
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Application publication date: 20120222 Assignee: Jiangsu Rothwell Electric Co., Ltd. Assignor: Southeast University Contract record no.: 2014320000094 Denomination of invention: A WSN/MINS high precision real-time integrated navigation information fusion method Granted publication date: 20130703 License type: Exclusive License Record date: 20140228 |
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