WO2016041281A1 - 一种基于无线网络的定位方法及装置 - Google Patents

一种基于无线网络的定位方法及装置 Download PDF

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Publication number
WO2016041281A1
WO2016041281A1 PCT/CN2014/094091 CN2014094091W WO2016041281A1 WO 2016041281 A1 WO2016041281 A1 WO 2016041281A1 CN 2014094091 W CN2014094091 W CN 2014094091W WO 2016041281 A1 WO2016041281 A1 WO 2016041281A1
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target node
value
location
node
signal strength
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PCT/CN2014/094091
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English (en)
French (fr)
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郑侃
朱骅
李航
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北京邮电大学
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Publication of WO2016041281A1 publication Critical patent/WO2016041281A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Definitions

  • the present application relates to the field of communications, and in particular, to a wireless network-based positioning method and apparatus.
  • the terminal device may be a personal computer (PC) or a mobile phone.
  • PC personal computer
  • a mobile device such as a tablet computer, or a device or a monitoring system that provides an electronic tour guide service.
  • the methods for locating the target position are mainly divided into two types: one is a positioning method based on ranging technology, and the other is a positioning method without ranging.
  • the implementation principle of the positioning method based on the ranging technology mainly is to measure the received signal strength (Resived Signal Strength Indicator, RSSI) when the signal transmitted by the target node reaches the reference node (often a base station or other nodes in the wireless network). ), or the distance between different reference nodes to determine an estimate of the distance of the reference node from the target node, and then determine the location of the target directly based on the determined estimate.
  • RSSI Received Signal Strength Indicator
  • the positioning method based on ranging technology has the advantage of strong stability and can be applied in various environments, it also has certain defects: the estimated value of the reference node from the target node is likely to be related to the reference. There is a large deviation between the actual values of the distances of the nodes from the target node, resulting in a lower accuracy of the final determined position of the target node.
  • the embodiment of the present application provides a positioning method based on a wireless network, which solves the problem that the location of the target node cannot be accurately located in the prior art.
  • the embodiment of the present application further provides a positioning device based on a wireless network, which solves the problem that the location of the target node cannot be accurately located in the prior art.
  • a positioning method based on a wireless network comprising:
  • a positioning device based on a wireless network comprising:
  • An obtaining unit configured to obtain at least two pre-estimated values of the location of the target node; a fusion unit configured to fuse the obtained at least two pre-estimated values to obtain a fusion value; and determine a location unit, where the target is determined according to the fusion value The location of the node.
  • the fusion of the obtained estimated values of the positions of the at least two target nodes and the determination of the location of the target node based on the fusion result can solve the problem that the location of the target node cannot be accurately located in the prior art.
  • FIG. 1 is a flowchart of a specific implementation of a wireless network-based positioning method according to Embodiment 1 of the present application;
  • FIG. 2 is a schematic diagram showing a positional relationship between a reference node and a target node in the embodiment of the present application
  • FIG. 3 is a schematic structural diagram of a wireless network-based positioning apparatus according to Embodiment 2 of the present application.
  • FIG. 4 is a schematic diagram showing the comparison of the cumulative probability of the target node positioning error obtained by using the wireless network-based positioning scheme provided by the embodiment of the present application and the prior art.
  • the target node may be a device that can access the wireless network, such as a user equipment (for example, a mobile device that is portable, pocket-sized, handheld, built-in, or in-vehicle), a mobile terminal, or a mobile user device.
  • the reference node may be a mobile communication base station of various types (for example, a base station (BTS, Base Transceiver Station) in GSM or CDMA, or a base station in WCDMA), or may be another device that can receive signals from a target node, etc.
  • BTS Base Transceiver Station
  • WCDMA Wideband Code Division Multiple Access
  • the application embodiment does not limit the type of reference node here.
  • Embodiment 1 of the present application provides a positioning method based on a wireless network.
  • the specific implementation flow chart of the method is shown in FIG. 1 and mainly includes the following steps:
  • Step 11 Obtain at least two pre-estimated values of the location of the target node
  • Step 12 merging the obtained at least two pre-estimated values to obtain a fusion value
  • step 13 the location of the target node is determined according to the fusion value.
  • Embodiment 1 of the present application since the estimated value of the position of at least two target nodes is used as the basis for determining the position of the target node, the target node can be more accurately determined than the prior art.
  • the position solves the problem that the position of the target node cannot be accurately located in the prior art.
  • step 11 in one embodiment, the step can be implemented by the following sub-steps A to B sub-steps:
  • Sub-step A obtaining a plurality of reference nodes (hereinafter referred to as the plurality of reference nodes) respectively and the target The value of the propagation distance between nodes.
  • the propagation distance may be a propagation distance of a signal transmitted by the target node that is received by the reference node and whose location is unknown.
  • the propagation distance can be estimated by the received signal strength value of the plurality of signals received from the target node received by the reference node. This technique is prior art and will not be described again.
  • Sub-step B pre-estimating the position of the target node according to the value of the propagation distance, and obtaining at least two pre-estimated values of the position of the target node.
  • the received signal strength value of the signal transmitted by the target node when reaching each of the plurality of reference nodes respectively may be determined according to the value of the propagation distance; and then, according to the determined received signal strength value. , pre-estimate the location of the target node.
  • the received signal strength value of the signal transmitted by the target node when reaching the reference node may be determined by using formula [1], as follows:
  • the RSSI value of the signal transmitted by the target node when it reaches the reference node can be obtained according to the formula [1].
  • the formula [1] is:
  • d is the propagation distance of the signal transmitted by the target node
  • P(d) is the average received signal strength value when the signal transmitted by the signal transmitting end arrives at the signal receiving end when the signal transmitting end and the signal receiving end are separated by d. That is, the average RSSI value of the signal sent by the signal transmitting end when it reaches the signal receiving end
  • d 0 is the specific signal propagation distance (generally d 0 is selected as 1 m)
  • P(d 0 ) is the signal transmitting end and the signal receiving end When the distance between d 0 is 0 , the average RSSI value of the signal sent by the signal transmitting end when it reaches the signal receiving end
  • n p is the path loss parameter related to the actual environment.
  • the method for determining the received signal strength value when the signal transmitted by the target node reaches each of the plurality of reference nodes respectively is not limited to the above manner.
  • the pre-estimation of the location of the target node according to the determined received signal strength value described in sub-step B can be implemented in the following three ways:
  • the first method includes the following steps a1 to a3:
  • A1 determine the geographical area where the target node is located, the sub-area included in the geographical area, and multiple references a reference node in the node that is within the geographic area;
  • the geographic area where the target node is located may be determined by determining whether the received signal strength value of the target node received by the multiple reference nodes is greater than a preset value. For example, the geographical area where the reference node corresponding to the received signal strength value greater than the preset value is located may be determined as the geographical area where the target node is located (hereinafter referred to as “determined geographical area”).
  • the number of sub-regions that can be divided can be determined by using the formula [2], and then the sub-regions are divided according to the number to determine the sub-regions included in the geographic region:
  • the number of sub-regions that can be divided can be determined by the formula [2]:
  • S is the determined total area of the geographical area
  • N is the total number of the plurality of reference nodes
  • G is the number of sub-regions that can be divided.
  • reference nodes in a plurality of reference nodes that are within a determined geographic area may be determined, but are not limited to, using the following steps:
  • the pre-setting of the signal characteristic parameters can be completed in the following manner:
  • the sampling device set at different positions in the determined geographical area may be used to sample the signals respectively sent by the reference nodes in the geographical area to obtain corresponding signal characteristic parameters. set.
  • the sampling device may sample the signals respectively sent by the reference nodes in the geographic region, and then determine the signal characteristic parameters of the sampled signals.
  • the signal characteristic parameters may constitute a signal characteristic parameter set corresponding to the position A Hehe.
  • a set of signal feature parameters respectively corresponding to different locations within the geographic area can be obtained.
  • the reference node corresponding to the selected signal feature information is determined as a reference node in the determined geographical area.
  • the sub-area where the target node is located is determined from the sub-areas included in the geographical area.
  • the sub-region where the target node is located can be determined by the formula [3], where the formula [3] is:
  • Mode 2 is further described below.
  • mode 2 may include the following steps b1 b b2:
  • B1 selecting, from all the received signal strength values, a received signal strength value that is greater than a preset probability value in the received signal strength value
  • step b2 the specific implementation manner of the foregoing step b2 may be as follows:
  • r w of the signal strength P received by the reference node under the distance set r can be determined according to the probability calculation formula [4] ), where the formula [4] is as follows:
  • R is the signal strength obtained by the sampling node j is the reference node number and M is the total number of reference nodes.
  • the distance value corresponding to the maximum probability value is selected and determined as the position of the target node.
  • mode 3 may include the following steps c1 c c3:
  • the formula shown by the following formula [5] can be derived.
  • an estimated value d k of the distances of the respective reference nodes in the reference node set composed of the plurality of reference nodes from the target node, respectively, can be obtained.
  • k is the number of the reference node in the reference node set
  • k has a value range of [1, I]
  • I is the total number of reference nodes included in the reference node set
  • R k is the arrival number of the signal sent by the target node The average RSSI value for the reference node of k.
  • the geometric constraint includes: the absolute value of the difference between the reference nodes and the square of the estimated values of the distances respectively from the target node is not greater than the square of the distance between the pair of reference nodes.
  • the geometric constraint can be expressed by the formula [6]:
  • u is the number of the reference node pair included in the reference node set
  • the value range of u is [1, I]I is the total number of reference node pairs included in the reference node set
  • d u1 is the reference numbered u
  • d u2 is an estimate of the distance between the second reference node and the target node in the reference node pair numbered u
  • n u The distance value between the two reference nodes included for the reference node pair numbered u.
  • the distance value between the reference nodes may be determined according to the position coordinates of the reference node, which may be, but is not limited to, determined by a Global Position System (GPS) positioning method.
  • GPS Global Position System
  • C3. Determine the location of the target node by using the value of the distance of the specific reference node in the reference node pair that meets the preset geometric constraint from the target node.
  • step c3 in conjunction with FIG. 2:
  • the coordinates of the reference node A are (0, 0)
  • the coordinates of the reference node B are (m, 0)
  • the coordinates of the reference node C are (0, n)
  • the coordinates of the reference node D are (m, n).
  • the estimated values of the distances of the reference nodes A, B, C, and D from the target node are respectively d 1 , d 2 , d 3 , and d 4 .
  • the foregoing three methods may be combined according to different scenarios.
  • the first mode may be combined with the second mode and the third mode, or the first mode may be combined with the second mode and the third mode to perform pre-estimation on the target node.
  • the application is not limited thereto.
  • step 12 the obtained at least two pre-estimated values are fused to obtain a fused value.
  • the foregoing step 12 may obtain, according to at least two pre-estimated values, a confidence level of at least two pre-estimated values; and further perform, according to the obtained confidence of the at least two pre-estimated values, the at least two pre-estimated values. Fusion.
  • the pre-estimated value of the target node obtained by mode 1 is (x 1 , y 1 ), and the pre-estimated value of the target node obtained by mode 2 is (x 2 , y 2 ), and the target node obtained by mode 3 is obtained.
  • the pre-estimated value is (x 3 , y 3 ).
  • the pre-estimated value obtained by the first method can be used as a reference value, and the distance between the pre-estimated value obtained by the second method and the third method and the pre-estimated value obtained by the first method, that is, a 1 and a 2 , respectively, is calculated. Equation [11] and formula [12]:
  • the fusion value of the pre-estimated value is obtained by the formula [14] as M(x, y).
  • step 13 the location of the target node is determined according to the fusion value.
  • the estimated values of the obtained positions of at least two target nodes are fused, and the position of the target node is determined based on the fusion result, thereby reducing the position of the positioning target in the prior art.
  • the problem of large deviation of accuracy makes it possible to more accurately determine the position of the target node.
  • the method may further include: performing the step 13 according to the sub-area where the target node is determined by performing step a2 It is judged whether the position of the determined target node needs to be corrected.
  • the sub-area in which the target node is located is numbered 10 in advance by the above-described manner, and the position of the target node is determined as the fusion value M (x) obtained by the formula [14].
  • y it can be judged whether the determined position M(x, y) of the target node is within the sub-area of the number 10. If M(x, y) is in the sub-area of number 10, there is no need to correct M(x, y); if M(x, y) is not in the sub-area of number 10, then M(x, y) is needed. ) Make corrections.
  • the optional correction method first, the sub-region to which M(x, y) belongs can be determined; and then, in the sub-region to which the determined M(x, y) belongs, the positioning method proposed by the present application is utilized Or other positioning methods (eg, using a neural network method or a probabilistic method) to position the target node.
  • the execution bodies of the steps of the method provided in Embodiment 1 may all be the same device, or the method may also be performed by different devices.
  • the execution body of step 11 and step 12 may be device 1, and the execution body of step 13 may be device 2; for example, the execution body of step 11 may be device 1, and the execution body of step 12 and step 13 may be device 2. ;and many more.
  • Embodiment 2 provides a wireless network-based positioning device to solve the problem of low target positioning accuracy in the prior art.
  • a schematic structural diagram of the target positioning device is shown in FIG. 3, and includes an acquisition unit 31, a fusion unit 32, and a determination position unit 33. The specific description of these three functional units is as follows:
  • the obtaining unit 31 is configured to obtain at least two pre-estimated values of the target node location
  • the merging unit 32 is configured to fuse the obtained at least two pre-estimated values to obtain a merging value
  • the determining location unit 33 is configured to determine the location of the target node based on the fused value.
  • the obtaining unit 31 is further configured to obtain a value of a propagation distance between the multiple reference nodes and the target node, and pre-estimate the location of the target node according to the value of the propagation distance, to obtain at least two locations of the target node. Pre-estimated value.
  • the obtaining unit 31 further includes: determining the two functional units of the received signal strength subunit and the pre-estimating subunit as follows:
  • Determining a received signal strength subunit configured to determine, according to a value of the propagation distance, a received signal strength value when the signal transmitted by the target node reaches each of the plurality of reference nodes respectively;
  • the pre-estimation sub-unit is configured to pre-estimate the position of the target node according to the received signal strength value.
  • the pre-estimation sub-unit is used to:
  • the average received signal strength capability value of the reference node in the domain determines the sub-region where the target node is located from the sub-region included in the geographic region, and determines the location of the target node according to the determined position of the preset sampling point in the sub-region.
  • the pre-estimation sub-unit is further used to:
  • the pre-estimation sub-unit is further used to:
  • the reference node set is composed of a plurality of reference nodes;
  • the geometric constraint includes: the absolute value of the difference between the squares of the estimated values of the distances of the reference nodes respectively from the target node is not greater than the square of the distance value between the pair of reference nodes;
  • the value of the distance of the specific reference node in the reference node pair of the geometric constraint from the target node is determined, and the position of the target node is determined.
  • the merging unit 32 further includes two functional subunits for determining a confidence subunit and a fusion subunit, which are specifically described as follows:
  • a confidence subunit is determined for obtaining a confidence level of at least two pre-estimates based on the at least two pre-estimated values.
  • a fusion subunit configured to fuse at least two pre-estimated values according to a confidence of at least two pre-estimated values.
  • the apparatus shown in FIG. 3 may further include: a determining unit, configured to determine, according to the location area where the target node is pre-estimated, the determined target node Whether the position needs to be corrected.
  • the estimated values of the obtained positions of at least two target nodes are fused, and the position of the target node is determined based on the fusion result, thereby reducing the position of the positioning target in the prior art.
  • a problem with a large degree of accuracy deviation, which can be more accurately determined The location of the target node.
  • the abscissa is the error distance (unit: m); the ordinate is the error probability.
  • (1) represents the error and cumulative probability distribution of the target node position calculated by the location fingerprint location method, the error is up to 50M, which seriously affects the accuracy of the positioning.
  • (2) the fusion positioning method proposed in the present application ensures that the abnormal error is eliminated under the same conditions, and the maximum error is reduced to 5M, which greatly improves the positioning accuracy performance.
  • (3) indicates the positioning result of the MLE method, and the maximum error is about 8M.
  • It indicates that the positioning error of the LSE method is the largest, and is much larger than the other two methods, and the positioning error of 8M or more is prone to occur, and the positioning performance does not meet the requirements of precise positioning.
  • the position fingerprint method (1) takes the center of the positioning sub-region as the output result, so the positioning error is relatively large, followed by the positioning methods of MLE(3) and LSE(4). Low, however, is greater than the target node position calculated by the target positioning method proposed by the present application. At the same time, within the same error tolerance range, the accuracy of the target positioning method proposed by the present application is also higher than (1) and (4), thereby demonstrating the superior positioning performance of the positioning method proposed by the present application.
  • embodiments of the present invention can be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or a combination of software and hardware. Moreover, the invention can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.
  • computer-usable storage media including but not limited to disk storage, CD-ROM, optical storage, etc.
  • the computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device.
  • the apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
  • These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device.
  • the instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.
  • a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
  • processors CPUs
  • input/output interfaces network interfaces
  • memory volatile and non-volatile memory
  • the memory may include non-persistent memory, random access memory (RAM), and/or non-volatile memory in a computer readable medium, such as read only memory (ROM) or flash memory.
  • RAM random access memory
  • ROM read only memory
  • Memory is an example of a computer readable medium.
  • Computer readable media includes both permanent and non-persistent, removable and non-removable media.
  • Information storage can be implemented by any method or technology.
  • the information can be computer readable instructions, data structures, modules of programs, or other data.
  • Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory. (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disk read only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, Magnetic tape cartridges, magnetic tape storage or other magnetic storage devices or any other non-transportable media can be used to store information that can be accessed by a computing device.
  • computer readable media does not include temporary storage of computer readable media, such as modulated data signals and carrier waves.
  • embodiments of the present application can be provided as a method, system, or computer program product.
  • the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment in combination of software and hardware.
  • the application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.

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Abstract

本申请公开了一种基于无线网络的定位方法及装置，其中，方法包括：获得目标节点位置的至少两个预估计值；对得到的至少两个预估计值进行融合，得到融合值；根据融合值，确定目标节点的位置。以解决现有技术不能准确定位目标节点位置的问题。本申请还公开一种基于无线网络的定位装置.

Description

一种基于无线网络的定位方法及装置 技术领域
本申请涉及通信领域，尤其涉及一种基于无线网络的定位方法及装置。
背景技术
随着无线网络技术的发展，基于位置的服务成为最具发展潜力的移动互联网业务之一。无论在室内还是室外，快速准确地获得终端设备的位置信息或提供用户所需求的位置信息服务已变得日益迫切，其中，终端设备可以是个人计算机(Personal Computer，PC)，也可以是手机、平板电脑等移动设备，或者，也可以是提供电子导游服务的设备或监控系统等。
目前，在无线网络定位中，定位目标位置的方法主要分为两种：一种是基于测距技术的定位方法，另一种是无需测距的定位方法。其中，基于测距技术的定位方法实现原理主要是，通过测量目标节点发送的信号在到达参考节点(往往是基站，或者无线网络中的其他节点)时的接收信号强度(Received Signal Strength Indicator,RSSI)，或不同参考节点间的距离来确定参考节点相距目标节点的距离的估计值，进而直接根据确定的估计值确定目标的位置。
尽管基于测距技术的定位方法的优势在于稳定性强、可在各种环境中应用，然而它也存在一定的缺陷，即：确定出的参考节点相距目标节点的距离的估计值有可能与参考节点相距目标节点的距离的实际值存在较大偏差，从而导致最终确定出的目标节点的位置的准确度较低。
发明内容
本申请实施例提供一种基于无线网络的定位方法，用以解决现有技术中不能准确定位目标节点位置的问题。
本申请实施例还提供一种基于无线网络的定位装置，用以解决现有技术中不能准确定位目标节点位置的问题。
本申请实施例采用下述技术方案：
一种基于无线网络的定位方法，包括：
获得目标节点位置的至少两个预估计值；对得到的至少两个预估计值进行融合，得到融合值；根据融合值，确定目标节点的位置。
一种基于无线网络的定位装置，包括：
获取单元，用于获得目标节点位置的至少两个预估计值；融合单元，用于对得到的至少两个预估计值进行融合，得到融合值；确定位置单元，用于根据融合值，确定目标节点的位置。
本申请实施例采用的上述至少一个技术方案能够达到以下有益效果：
通过对得到的至少两个目标节点的位置的估计值进行融合，并基于融合结果来确定目标节点的位置，从而可以解决现有技术中不能准确定位目标节点位置的问题。
附图说明
此处所说明的附图用来提供对本申请的进一步理解，构成本申请的一部分，本申请的示意性实施例及其说明用于解释本申请，并不构成对本申请的不当限定。在附图中：
图1为本申请实施例1提供的一种基于无线网络的定位方法的具体实现流程图；
图2为采用本申请实施例中参考节点与目标节点的一种位置关系示意图；
图3为本申请实施例2提供的一种基于无线网络的定位装置的具体结构示意图；
图4为采用本申请实施例提供的基于无线网络的定位方案与采用现有技术分别得到的目标节点定位误差累计概率对比示意图。
具体实施方式
为使本申请的目的、技术方案和优点更加清楚，下面将结合本申请具体实 施例及相应的附图对本申请技术方案进行清楚、完整地描述。显然，所描述的实施例仅是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
在本申请实施例中，目标节点可以是用户设备(例如，可以是便携式、袖珍式、手持式、计算机内置的或者车载的移动装置)、移动终端或移动用户设备等可接入无线网络的设备。参考节点可以是各种类型移动通信基站(例如，GSM或CDMA中的基站(BTS，BaseTransceiver Station)，也可以是WCDMA中的基站)，还可以是其他可接收目标节点发信号的设备等，本申请实施例在此并不对参考节点的类型做限定。
以下结合附图，详细说明本申请各实施例提供的技术方案。
实施例1
为了用以解决现有技术中不能准确定位目标节点位置的问题，本申请实施例1提供一种基于无线网络的定位方法。该方法的具体实现流程图如图1所示，主要包括下述步骤：
步骤11，获得目标节点位置的至少两个预估计值；
步骤12，对得到的至少两个预估计值进行融合，得到融合值；
步骤13，根据融合值，确定目标节点的位置。
采用本申请实施例1提供的上述方法，由于以至少两个目标节点的位置的估计值作为确定目标节点的位置的依据，从而与现有技术相比，可以更准确地确定出的目标节点的位置，解决了现有技术中不能准确定位目标节点位置的问题。
以下具体说明上述各步骤的具体实现方式：
针对步骤11而言，在一种实施方式中，该步骤可以通过以下子步骤A～B子步骤实现：
子步骤A，获得多个参考节点(下文简称所述多个参考节点)分别与目标 节点之间的传播距离的值。
其中，传播距离，可以是参考节点所接收到的、该位置未知的目标节点所发射的信号的传播距离。该传播距离可以通过对参考节点所接收到的来自该目标节点的多个信号的接收信号强度值推测得到，此技术为现有技术，不再赘述。
子步骤B，根据传播距离的值，对目标节点的位置进行预估计，得到目标节点位置的至少两个预估计值。
在上述子步骤B中，可以根据传播距离的值，确定目标节点发射的信号在分别到达多个参考节点中的各参考节点时的接收信号强度值；然后，再根据确定出的接收信号强度值，对目标节点的位置进行预估计。
可选地，目标节点发射的信号在到达参考节点时的接收信号强度值，可通过公式[1]确定，具体如下：
由于无线信号传播衰落服从对数正态分布，因此，可以根据公式[1]得到目标节点发射的信号在到达参考节点时的RSSI值，公式[1]为：
Figure PCTCN2014094091-appb-000001
其中，d为目标节点发射的信号的传播距离，P(d)为当信号发送端与信号接收端之间相距d时，信号发送端发送的信号在到达信号接收端时的平均接收信号强度值，即信号发送端发送的信号在到达信号接收端时的平均RSSI值；d0为特定的信号传播距离(一般d0选择为1m)；P(d0)为信号发送端与信号接收端之间的距离为d0时，信号发送端发送的信号在到达信号接收端时的平均RSSI值；np为与实际环境相关的路径损耗参数。
对于确定出目标节点发射的信号在分别到达多个参考节点中的各参考节点时的接收信号强度值的取得，本申请并不限于采用上述方式。
实施例1中，子步骤B中所述的根据确定出的接收信号强度值对目标节点的位置进行预估计可以通过如下三种方式实现：
方式一包括下述步骤a1～a3：
a1、确定目标节点所在的地理区域、该地理区域包含的子区域和多个参考 节点中处于该地理区域内的参考节点；
具体而言，可以通过判断多个参考节点所接收到的目标节点的接收信号强度值是否大于预设值，来确定目标节点所在的地理区域。比如，可以将大于预设值的接收信号强度值所对应的参考节点所在的地理区域，确定为目标节点所在的地理区域(下文简称“所确定的地理区域”)。
进一步地，可以利用公式[2]，确定可划分得到的子区域的数目，进而根据该数目，对所确定的地理区域进行子区域划分，以确定地理区域内所包含的子区域：
可选地，如图2所示，可划分得到的子区域的数目可通过公式[2]确定：
Figure PCTCN2014094091-appb-000002
其中，S是所确定的地理区域总面积，N是所述多个参考节点的总数目，G是可划分得到的子区域的数目。
此外，可以但不限于采用下述步骤，确定多个参考节点中处于确定的地理区域内的参考节点：
1、确定多个参考节点中的各参考节点的信号特征参数；其中，信号特征参数可以是：信号场强或多径相角分量功率；
2、从确定出的信号特征参数中，选取与预先设置的信号特征参数相匹配的信号特征参数；
其中，可以采用下述方式完成对信号特征参数的预先设置：
可以利用在所确定的地理区域内的不同位置设置的采样设备(此时的采样设备相当于目标节点)，对该地理区域内的各参考节点分别发送的信号进行采样，得到相应的信号特征参数集合。
比如，当采样设备位于该地理区域内的位置A时，采样设备可以对该地理区域内的各参考节点分别发送的信号进行采样，进而确定出采样得到的信号的信号特征参数。该些信号特征参数，可以构成对应于位置A的信号特征参数集 合。类似地，采用上述方式，可以得到分别对应于该地理区域内的不同位置的信号特征参数集合。
3、将选取的信号特征信息对应的参考节点确定为处于确定的地理区域内的参考节点。
a2、利用接收信号强度值和处于地理区域内的参考节点的平均接收信号强度能力值，从地理区域包含的子区域中，确定目标节点所在的子区域。
可选地，若假设确定出地理区域内的参考节点为4个，其中，4个参考节点实际接收的目标节点所发送的接收信号强度值为{R1,R2,R3,R4}，以及利用采样所获得的4个参考节点在每个子区域内的平均接收信号强度能力值为
Figure PCTCN2014094091-appb-000003
(i为子区域序号，G为划分得到的子区域总数目)，则可以由公式[3]来确定目标节点所在的子区域，其中，公式[3]为：
Figure PCTCN2014094091-appb-000004
通过上述公式[3]，可以得到{△i}，i＝(1，G)，进一步地，对所得到的{△i}进行排序，选出最小的△i所对应的子区域，确定为目标节点所在的子区域。
a3、根据确定出的子区域内预设采样点的位置，对目标节点的位置进行预估计。
以下进一步介绍方式2的实现方式。
可选地，方式2可以包括下述步骤b1～b2：
b1，从确定出的所有接收信号强度值中，选取在接收信号强度值中的出现概率值大于预设概率值的接收信号强度值；
b2，根据选取的接收信号强度值所对应的距离值，对目标节点的位置进行预估计。
方式2中，可选地，上述步骤b2的具体实现方式可以如下：
如图2所示，若假设已知4个参考节点的位置为{A，B，C，D}，且由上述公式[1]，得到该4个参考节点接收信号强度值分别为p1,p2,p3,p4(该4个接收信号强度值构成的集合记为P＝{p1,p2,p3,p4})，则通过在该4个参考节点所 在范围内设置采样节点N个，并计算每个采样节点分别与上述4个参考节点中的每个参考节点之间的距离，可以得到距离集合
Figure PCTCN2014094091-appb-000005
(w为采样节点编号，N为采样节点总个数)；然后，可根据概率计算公式[4]，确定在距离集合r下所参考节点接收的信号强度P的概率值P(p|rw)，其中，公式[4]如下所式：
Figure PCTCN2014094091-appb-000006
其中，R为采样节点所获得的信号强度
Figure PCTCN2014094091-appb-000007
j为参考节点编号，M为参考节点总数。
在计算出概率值P(p|rw)，后，从所得到的P(p|rw)概率值中，选取最大概率值所对应的距离值，确定为目标节点的位置。
可选地，方式3可以包括下述步骤c1～c3：
c1，根据接收信号强度值，确定所述多个参考节点中的各参考节点分别相距目标节点的距离的估计值。
针对步骤c1，可选地，根据公式[1]，可以推出如下式[5]所示的公式。根据公式[5]，可以得到由所述多个参考节点构成的参考节点集合中的各个参考节点分别相距目标节点的距离的估计值dk。
Figure PCTCN2014094091-appb-000008
其中，k为参考节点集合中的参考节点的编号，k的取值范围为[1，I]，I为参考节点集合所包含的参考节点总数目；Rk为目标节点发送的信号在到达编号为k的参考节点时的平均RSSI值。
根据公式[5]可以得到4个参考节点分别相距目标节点的距离的估计值d＝{d1,d2,d3,d4}。
c2，分别判断参考节点集合中的每个参考节点对是否符合预设的几何约束条件。
其中，几何约束条件包括：该参考节点对分别相距目标节点的距离的估计值平方之差的绝对值不大于该对参考节点之间距离值的平方。
针对上述步骤c2，可选地，几何约束条件可以用公式[6]表示：
Figure PCTCN2014094091-appb-000009
其中，u为参考节点集合所包含的参考节点对的编号，u的取值范围为[1，I]I为参考节点集合所包含的参考节点对的总数目；du1为编号为u的参考节点对中的第1个参考节点与目标节点之间的距离的估计值；du2为编号为u的参考节点对中的第2个参考节点与目标节点之间的距离的估计值；nu为编号为u的参考节点对包含的两个参考节点之间的距离值。
参考节点之间的距离值可以根据参考节点的位置坐标确定，该位置坐标可以但不限于通过全球定位系统(Global Position System，GPS)定位方式确定。
c3，利用符合预设的几何约束条件的参考节点对中的特定参考节点相距目标节点的距离的值，确定目标节点的位置。
可选的，以下结合附图2，具体说明如何实现步骤c3：
若下述假设成立：
1、参考节点A点坐标为(0,0)，参考节点B点坐标为(m,0)，参考节点C点坐标为(0,n)，参考节点D点坐标为(m,n)。
2、参考节点A、B、C、D分别相距目标节点的距离的估计值依次为d1、d2、d3、d4。
3、待定位的目标节点坐标设为X＝(x,y)。
基于上述假设，可以采用公式[7]计算目标节点坐标：
Figure PCTCN2014094091-appb-000010
将表达式[7]进一步整理得到表达式[8]为：
Figure PCTCN2014094091-appb-000011
进一步将公式[8]写成矩阵表达式[9]为：
2AX＝b   [9]
其中，
Figure PCTCN2014094091-appb-000012
为距离值的矩阵形式，那么目标节点的坐标值表达式[10]为：
Figure PCTCN2014094091-appb-000013
由上述公式[10]可以预估计出目标节点的位置X＝(x,y)
实施例1中，上述三种方式可以根据不同场景需要进行结合使用，例如，方式一可以分别结合方式二和方式三，或者方式一与方式二、方式三一起结合，以对目标节点进行预估计，以得到至少两个预估计值，对此本申请并不限于此。
步骤12，对得到的至少两个预估计值进行融合，得到融合值。
具体而言，上述步骤12可以根据至少两个预估计值，得到至少两个预估计值的置信度；再根据所得到的至少两个预估计值的置信度，对至少两个预估计值进行融合。
可选地，以下结合附图2，置信度计算方式如下：
若下述假设成立：
1、采用方式一所得到的目标节点的预估计值为(x1,y1),方式二所得到的目标节点的预估计值为(x2,y2)，方式三所得到的目标节点的预估计值为(x3,y3)。
2、可基于方式一所获得的预估计值作为参考值，分别计算方式二和方式三所获得的预估计值与方式一获得的预估计值之间的距离，即a1和a2，如公式[11]和公式[12]所示：
Figure PCTCN2014094091-appb-000014
Figure PCTCN2014094091-appb-000015
3、将a1和a2的倒数作为方式二和方式三对目标节点位置预估计值的置信度。
4、对上述所得到的预估计值(x1,y1)、(x2,y2)、(x3,y3)可以采用公式[13]进行融合:
Figure PCTCN2014094091-appb-000016
将公式[13]进一步整理得到公式[14]为：
Figure PCTCN2014094091-appb-000017
进而由公式[14]得到对预估计值的融合值为M(x,y)。
步骤13，根据融合值，确定目标节点的位置。
采用实施例1提供的上述方法，通过对得到的至少两个目标节点的位置的估计值进行融合，并基于融合结果来确定目标节点的位置，进而降低了现有技术中对定位目标的位置的准确度偏差较大的问题，从而可以更准确地确定出的目标节点的位置。
实施例1中，为了增强对目标节点定位的准确性，在图1所示的步骤13之后，还可以包括：根据通过执行步骤a2而确定出的目标节点所在的子区域，对通过执行步骤13而判断确定出的目标节点的位置是否需要进行校正。
例如，如图2所示，若假设由上述方式一预先估计出目标节点所在子区域为编号10的子区域，且目标节点的位置被确定为由公式[14]所得到的融合值M(x,y)，那么，可以判断所确定出的目标节点的位置M(x,y)是否在编号10的子区域内。如果M(x,y)在编号10的子区域内，则无需对M(x,y)进行校正；如果M(x,y)不在编号10的子区域内，则需要对M(x,y)进行校正。
其中，可选的校正方式：首先，可以确定出M(x,y)所属子区域；然后，在所确定出的M(x,y)所属的子区域内，利用本申请所提出的定位方法或其他定位方法(如，采用神经网法或概率法等)进行目标节点的位置定位。
需要说明的是，实施例1所提供方法的各步骤的执行主体均可以是同一设备，或者，该方法也由不同设备作为执行主体。比如，步骤11和步骤12的执行主体可以为设备1，步骤13的执行主体可以为设备2；又比如，步骤11的执行主体可以为设备1，步骤12和步骤13的执行主体可以为设备2；等等。
实施例2
实施例2提供一种基于无线网络的定位装置，用以解决现有技术中对目标定位准确度不高的问题。该目标定位装置的具体结构示意图如图3所示，包括获取单元31、融合单元32、确定位置单元33。这三个功能单元的具体介绍如下：
获取单元31，用于获得目标节点位置的至少两个预估计值；
融合单元32，用于对得到的至少两个预估计值进行融合，得到融合值；
确定位置单元33，用于根据融合值，确定目标节点的位置。
可选地，获取单元31，还可用于获得多个参考节点与目标节点之间的传播距离的值，根据传播距离的值，对目标节点的位置进行预估计，得到目标节点位置的至少两个预估计值。
可选地，获取单元31还包括：确定接收信号强度子单元和预估计子单元二个功能单元的具体介绍如下：
确定接收信号强度子单元，用于根据传播距离的值，确定目标节点发射的信号在分别到达多个参考节点中的各参考节点时的接收信号强度值；
预估计子单元，用于根据接收信号强度值，对目标节点的位置进行预估计。
可选地，预估计子单元用于：
确定目标节点所在的地理区域、所述地理区域包含的子区域和所述多个参考节点中处于所述地理区域内的参考节点，利用接收信号强度值和处于地理区 域内的参考节点的平均接收信号强度能力值，从地理区域包含的子区域中，确定目标节点所在的子区域，根据确定出的子区域内预设采样点的位置，确定目标节点的位置。
可选地，预估计子单元还用于：
从确定出的所有接收信号强度值中，选取在接收信号强度值中的出现概率值大于预设概率值的接收信号强度值，根据选取的接收信号强度值所对应的所述距离值，确定目标节点的位置。
可选地，预估计子单元还用于：
根据接收信号强度值，确定、多个参考节点中的各参考节点分别相距目标节点的距离的估计值；分别判断参考节点集合中的每个参考节点对是否符合预设的几何约束条件；其中，参考节点集合由多个参考节点构成；几何约束条件包括：该参考节点对分别相距目标节点的距离的估计值平方之差的绝对值不大于该对参考节点之间距离值的平方；利用符合预设的几何约束条件的参考节点对中的特定参考节点相距目标节点的距离的值，确定目标节点的位置。
可选地，融合单元32还包括确定置信度子单元和融合子单元二个功能子单元具体介绍如下：
确定置信度子单元，用于根据至少两个预估计值，得到至少两个预估计值的置信度。
融合子单元，用于根据至少两个预估计值的置信度，对至少两个预估计值进行融合。
实施例2中，为了增强对目标节点定位的准确性，在图3所示装置中还可以包括：判断单元，用于根据预估计目标节点所在的位置区域，判断确定出的所述目标节点的位置是否需要进行校正。
采用实施例2提供的上述方法，通过对得到的至少两个目标节点的位置的估计值进行融合，并基于融合结果来确定目标节点的位置，进而降低了现有技术中对定位目标的位置的准确度偏差较大的问题，从而可以更准确地确定出的 目标节点的位置。
本申请实施例中，通过实验，对比了采用本申请实施例提供的目标定位方案，以及采用现有技术的目标定位。对比结果如图4所示。
图4所示坐标系中，横坐标为误差距离(单位：m)；纵坐标为误差概率。其中，(1)表示位置指纹定位方法计算出的目标节点位置的误差和累计概率分布，该误差最大可达50M，严重影响了定位的精准性。相比较，(2)为本申请提出的融合的定位方法，保证了在相同条件下，消除了异常误差，将最大误差缩小至5M范围内，大幅度地提高了定位精准性能。(3)表示MLE方法的定位结果，其最大误差约为8M左右。(4)表示LSE方法的定位误差最大，且远大于其他两种方法，容易出现8M以上的定位误差，定位性能完全不符合精准定位的要求。
相比较而言，位置指纹法(1)由于取得定位子区域的中心作为输出结果，因此定位误差相对较大，其次是MLE(3)和LSE(4)的定位方法相对(1)定位误差较低，然而，皆大于比本申请所提出的目标定位方法计算出的目标节点位置。同时，在同样的误差允许范围内，本申请提出的目标定位方法的准确率也高于(1)和(4)，从而证明了本申请提出的定位方法的优越定位性能。
本领域内的技术人员应明白，本发明的实施例可提供为方法、系统、或计算机程序产品。因此，本发明可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本发明可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本发明是参照根据本发明实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算 机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
在一个典型的配置中，计算设备包括一个或多个处理器(CPU)、输入/输出接口、网络接口和内存。
内存可能包括计算机可读介质中的非永久性存储器，随机存取存储器(RAM)和/或非易失性内存等形式，如只读存储器(ROM)或闪存(flash RAM)。内存是计算机可读介质的示例。
计算机可读介质包括永久性和非永久性、可移动和非可移动媒体可以由任何方法或技术来实现信息存储。信息可以是计算机可读指令、数据结构、程序的模块或其他数据。计算机的存储介质的例子包括，但不限于相变内存(PRAM)、静态随机存取存储器(SRAM)、动态随机存取存储器(DRAM)、其他类型的随机存取存储器(RAM)、只读存储器(ROM)、电可擦除可编程只读存储器(EEPROM)、快闪记忆体或其他内存技术、只读光盘只读存储器(CD-ROM)、数字多功能光盘(DVD)或其他光学存储、磁盒式磁带，磁带磁磁盘存储或其他磁性存储设备或任何其他非传输介质，可用于存储可以被计算设备访问的信息。按照本文中的界定，计算机可读介质不包括暂存电脑可读媒体(transitory media)，如调制的数据信号和载波。
还需要说明的是，术语“包括”、“包含”或者其任何其他变体意在涵盖非 排他性的包含，从而使得包括一系列要素的过程、方法、商品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、商品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、商品或者设备中还存在另外的相同要素。
本领域技术人员应明白，本申请的实施例可提供为方法、系统或计算机程序产品。因此，本申请可采用完全硬件实施例、完全软件实施例或结合软件和硬件方面的实施例的形式。而且，本申请可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
以上所述仅为本申请的实施例而已，并不用于限制本申请。对于本领域技术人员来说，本申请可以有各种更改和变化。凡在本申请的精神和原理之内所作的任何修改、等同替换、改进等，均应包含在本申请的权利要求范围之内。

Claims (16)

  1. 一种基于无线网络的定位方法，其特征在于，包括：
    获得目标节点位置的至少两个预估计值；
    对得到的所述至少两个预估计值进行融合，得到融合值；
    根据所述融合值，确定所述目标节点的位置。
  2. 如权利要求1所述的方法，其特征在于，获得目标节点位置的至少两个预估计值，包括：
    获得多个参考节点分别与目标节点之间的传播距离的值；
    根据所述传播距离的值，对目标节点的位置进行预估计，得到所述目标节点位置的至少两个预估计值。
  3. 如权利要求2所述的方法，其特征在于，根据所述传播距离的值，对目标节点的位置进行预估计，包括：
    根据所述传播距离的值，确定所述目标节点发射的信号在分别到达所述多个参考节点中的各参考节点时的接收信号强度值；
    根据所述接收信号强度值，对目标节点的位置进行预估计。
  4. 如权利要求3所述的方法，其特征在于，根据所述接收信号强度值，对目标节点的位置进行预估计，包括：
    确定目标节点所在的地理区域、所述地理区域包含的子区域和所述多个参考节点中处于所述地理区域内的参考节点；
    利用所述接收信号强度值和处于所述地理区域内的参考节点的平均接收信号强度能力值，从所述地理区域包含的子区域中，确定目标节点所在的子区域；
    根据确定出的子区域内的预设采样点的位置，对目标节点的位置进行预估计。
  5. 如权利要求4所述的方法，其特征在于，根据所述接收信号强度值，对目标节点的位置进行预估计，还包括：
    从确定出的所有接收信号强度值中，选取在所述接收信号强度值中的出现概率值大于预设概率值的接收信号强度值；
    根据选取的接收信号强度值所对应的所述距离值，对目标节点的位置进行预估计。
  6. 如权利要求4或5所述的方法，其特征在于，根据所述接收信号强度值，对目标节点的位置进行预估计，还包括：
    根据所述接收信号强度值，确定所述多个参考节点中的各参考节点分别相距目标节点的距离的估计值；
    分别判断参考节点集合中的每个参考节点对是否符合预设的几何约束条件；其中，所述参考节点集合由所述多个参考节点构成；所述几何约束条件包括：该参考节点对分别相距目标节点的距离的估计值平方之差的绝对值不大于该对参考节点之间距离值的平方；
    利用符合预设的几何约束条件的参考节点对中的特定参考节点相距目标节点的距离的值，对目标节点的位置进行预估计。
  7. 如权利要求6所述的方法，其特征在于，根据所述融合值，确定所述目标节点的位置之后，所述方法还包括：
    根据确定出的目标节点所在的子区域，判断确定出的所述目标节点的位置是否需要校正。
  8. 如权利要求1所述的方法，其特征在于，对得到的目标节点位置的至少两个预估计值进行融合，包括：
    根据所述至少两个预估计值，得到所述至少两个预估计值的置信度；
    根据所述至少两个预估计值的置信度，对所述至少两个预估计值进行融合。
  9. 一种基于无线网络的定位装置，其特征在于，包括：
    获取单元，用于获得目标节点位置的至少两个预估计值；
    融合单元，用于对得到的所述至少两个预估计值进行融合，得到融合值；
    确定位置单元，用于根据所述融合值，确定所述目标节点的位置。
  10. 如权利要求9所述的装置，其特征在于，所述获取单元用于：
    获得多个参考节点分别与目标节点之间的传播距离的值，根据所述传播距离的值，对目标节点的位置进行预估计，得到所述目标节点位置的至少两个预估计值。
  11. 如权利要求10所述的装置，其特征在于，所述获取单元，包括：
    确定接收信号强度子单元，用于根据所述传播距离的值，确定所述目标节点发射的信号在分别到达所述多个参考节点中的各参考节点时的接收信号强度值；
    预估计子单元，用于根据所述接收信号强度值，对目标节点的位置进行预估计。
  12. 如权利要求11所述的装置，其特征在于，所述预估计子单元用于：
    确定目标节点所在的地理区域、所述地理区域包含的子区域和所述多个参考节点中处于所述地理区域内的参考节点，利用所述接收信号强度值和处于所述地理区域内的参考节点的平均接收信号强度能力值，从所述地理区域包含的子区域中，确定目标节点所在的子区域，根据确定出的子区域内预设采样点的位置，对目标节点的位置进行预估计。
  13. 如权利要求12所述的装置，其特征在于，所述预估计子单元还用于：
    从确定出的所有接收信号强度值中，选取在所述接收信号强度值中的出现概率值大于预设概率值的接收信号强度值，根据选取的接收信号强度值所对应的所述距离值，对目标节点的位置进行预估计。
  14. 如权利要求12或13所述的装置，其特征在于，所述预估计子单元还用于：
    根据所述接收信号强度值，确定所述多个参考节点中的各参考节点分别相距目标节点的距离的估计值；
    分别判断参考节点集合中的每个参考节点对是否符合预设的几何约束条件；其中，所述参考节点集合由所述多个参考节点构成；所述几何约束条件包括：该参考节点对分别相距目标节点的距离的估计值平方之差的绝对值不大于该对参考节点之间距离值的平方；
    利用符合预设的几何约束条件的参考节点对中的特定参考节点相距目标节点的距离的值，确定目标节点的位置。
  15. 如权利要求14所述的装置，其特征在于，所述装置还包括：
    判断单元，用于在确定位置单元根据所述融合值，确定所述目标节点的位置之后，根据确定出的目标节点所在的子区域，判断确定出的所述目标节点的位置是否需要校正。
  16. 如权利要求9所述的装置，其特征在于，所述融合单元，包括：
    确定置信度子单元，用于根据所述至少两个预估计值，得到所述至少两个预估计值的置信度；
    融合子单元，用于根据所述至少两个预估计值的置信度，对所述至少两个预估计值进行融合。
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