WO2020125480A1 - 一种协作定位方法与装置、计算机设备、存储介质 - Google Patents

一种协作定位方法与装置、计算机设备、存储介质 Download PDF

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WO2020125480A1
WO2020125480A1 PCT/CN2019/124204 CN2019124204W WO2020125480A1 WO 2020125480 A1 WO2020125480 A1 WO 2020125480A1 CN 2019124204 W CN2019124204 W CN 2019124204W WO 2020125480 A1 WO2020125480 A1 WO 2020125480A1
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satellite
node
positioning
information
nodes
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陈孔阳
谭光
顾韶颀
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Shenzhen Institute of Advanced Technology of CAS
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/24—Acquisition or tracking or demodulation of signals transmitted by the system
    • G01S19/25—Acquisition or tracking or demodulation of signals transmitted by the system involving aiding data received from a cooperating element, e.g. assisted GPS
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position

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  • the invention belongs to the technical field of navigation and positioning, and in particular relates to a cooperative positioning method and device, computer equipment, and storage medium.
  • the satellite positioning system includes three components: a space station, a ground station, and a user receiver.
  • the satellite of the space station continuously broadcasts its position and time.
  • the ground station monitors and controls the operating status of the satellite.
  • the user receiver collects broadcast satellite signals. You can calculate your position by capturing more than 4 visible satellites. Satellite positioning does not require additional auxiliary equipment and can be independently positioned. It can provide positioning accuracy of about 10 meters in a sunny and visible environment. It has become an important positioning method for people's daily life.
  • satellite signals are very weak due to the obstruction and influence of buildings such as tall buildings, viaducts, etc., and the buildings will also cause interference such as multipath and non-line-of-sight reception, resulting in large deviations in satellite signals, often unable to The positioning, or the positioning result has a large deviation, and there are often positioning errors of tens of meters and hundreds of meters, which affect the actual positioning requirements.
  • how to design and implement a GPS high-precision positioning algorithm is still a very challenging problem.
  • Literature [2] A.Bilich,P.Axelrad,KMLarson.Scientific utility of the signal-to-noise ratio (SNR)reported by geodetic GPS receivers.Proc.of ION GNSS, 2007, which disclosed the detection of GPS multipath signals , Remove multipath satellites, hoping to reduce positioning errors.
  • Reference [2] can only be applied to the occasions with more visible satellites. In harsh environments such as high-rise buildings, the number of satellites can be seen to be small. After removing the multipath satellites, it is often impossible to locate.
  • Literature [3] P.D.Groves.Shadow matching: A new GNSS positioning for technology urban for canyons. Journal of Navigation, 2011 discloses that the 3D model of surrounding buildings is used to detect interfering satellites and reduce positioning errors.
  • Reference [3] requires a 3D model of surrounding buildings in advance, which is currently difficult to obtain on a large scale.
  • literature [3] also needs to have a relatively accurate initial position as a positioning reference, which is also difficult to guarantee in the actual environment.
  • the present invention aims to provide an inertial navigation device that does not depend on a large accumulation error, does not require 3D models, initial positions and other prerequisites, and can complete the position even when there are few visible satellites Computational positioning method to solve the positioning problem in complex urban environment.
  • a technical solution adopted by the present invention is to provide a collaborative positioning method, including the following steps:
  • the asynchronous CTN positioning method uses the asynchronous CTN positioning method to calculate the precise location information of the node to be located; the asynchronous CTN positioning method includes:
  • the clock deviation of the node and the rough positioning time deviation of the node, iteratively obtains the position iteration increment that meets the requirements through the least square method
  • the least square method is used to obtain the exact position of the seed node according to the clock deviation and the coarse time deviation;
  • the method further includes the steps before using the asynchronous CTN positioning method:
  • satellite signals independently collected by multiple receiver nodes, where the satellite signals include satellite pseudorange, satellite positioning accuracy, satellite signal strength, and satellite clock deviation information;
  • the original observation information set iteratively selects the optimal satellite pseudorange information, satellite positioning accuracy information, and satellite signal strength information.
  • the mapping method is: using the distance and direction of the mapping node and the seed node according to the satellite pseudorange of the seed node, to obtain the satellite pseudorange of the mapping node.
  • the step of "selecting the optimal satellite pseudorange information, satellite positioning accuracy information, satellite signal strength information" specifically includes, by setting a distance threshold, a signal-to-noise ratio threshold, and a positioning contribution threshold, a preliminary selection is selected.
  • the required information set further selects the optimal satellite pseudorange information, satellite positioning accuracy information, and satellite signal strength information from the information set in an iterative manner.
  • the position iteration increment calculation process is as follows:
  • the original observation set can be updated among them Is the distance between node B 1 and satellite S j ; thus, the increment of the original observation can be updated Use ⁇ M 1 to update the position increment ⁇ p;
  • the position increment ⁇ p xyz of node B 1 is much smaller than the pseudo-range M 1 , so
  • the matrix form is:
  • the calculation process of the precise position of the seed node is as follows:
  • each node Since each receiver has independent clock deviation t b and coarse time deviation t c , and N nodes are selected, each node contributes q i original observations; then the offset of the seed node is
  • the matrix form is:
  • the satellites that meet the requirements need to be sufficiently separated from each other and have a good geometric distribution.
  • a cooperative positioning device including:
  • a plurality of satellite signal acquisition modules for acquiring satellite signals independently collected by multiple receiver nodes, the satellite signals including satellite pseudorange, satellite positioning accuracy, satellite signal strength and satellite clock deviation information;
  • the mapping module uses the receiver node with the best positioning accuracy as the seed node, and maps the satellite signals collected by other receiver nodes to the seed node to form the original observation information set;
  • the information selection module selects the optimal satellite pseudorange information, satellite positioning accuracy information, and satellite signal strength information through iteration based on the original observation information set;
  • Asynchronous CTN positioning module according to the three-dimensional position of the node to be located, the clock deviation of the node, and the coarse positioning time deviation of the node, iteratively obtains the position iteration increment that meets the requirements through the iterative method; then it is further used according to the clock deviation and the coarse time deviation
  • the least square method is used to obtain the precise position of the seed node; finally, the geometric position of each node is used to calculate the precise position of the other nodes.
  • a computer device has a processor and a memory, and the memory stores a computer program, and when the computer program is executed by the processor, the processor is caused to perform the steps of the cooperative positioning method of any of the foregoing embodiments.
  • the present invention provides a collaborative positioning method and device, computer equipment, and storage medium. It proposes an asynchronous CTN positioning method for the time difference error of multiple nodes; this patent does not require auxiliary sensors (such as inertial navigation, etc.), nor does it require 3D. Prior knowledge such as maps does not need to obtain a more accurate initial position in advance and can also complete position calculation in the case of fewer visible satellites, thereby solving the positioning problem in complex urban environments.
  • the technical solution of the present invention is used The positioning accuracy can be improved by 2-3 times compared with the existing positioning accuracy.
  • FIG. 1 is a schematic flowchart of a collaborative positioning method of the present invention
  • FIG. 2 is a schematic diagram of a module structure of a cooperative positioning device of the present invention.
  • FIG. 3 is a schematic diagram of the mapping of the original observation of the present invention.
  • FIG. 4 is a schematic diagram of the iterative process of the CTN method of the present invention from position P to position P′;
  • Figure 6 is a schematic diagram of the comparison of positioning accuracy of the three methods.
  • the present invention provides a collaborative positioning method, including the following steps:
  • the satellite signals include satellite pseudorange, satellite positioning accuracy, satellite signal strength, and satellite clock deviation information;
  • the mapping method is based on the satellite pseudorange of the seed node, using the distance and direction of the mapping node and the seed node to obtain the satellite pseudorange of the mapping node.
  • Each node has a satellite receiver, node B i can observe z i satellite signals, each satellite satellite corresponds to an original observation, so the original observation set of satellite signals of node B i is The satellite positioning accuracy of node B i is DOP(B i ).
  • the seed node has the maximum positioning accuracy DOP(B i ), and then maps the original observations of other nodes to the seed node B l .
  • Shown in Figure 3 is a diagram of the satellite's original observation mapping. Assuming that node B 2 can observe satellite S, but node B 1 cannot directly observe satellite S (for example, blocked by a building), we want to map the original observation of node B 2 to B 1 . In other words, the pseudorange m 2S from B 2 to satellite S is now known, and the distance and direction between B 1 and B 2 are also known. The pseudorange m 1S from B 1 to satellite S needs to be solved.
  • the steps of “selecting the optimal satellite pseudorange information, satellite positioning accuracy information, and satellite signal strength information” specifically include that, by setting a distance threshold, a signal-to-noise ratio threshold, and a positioning contribution threshold, a preliminary selection of information sets that meet the requirements is selected, and further passed
  • the iterative method selects the optimal satellite pseudorange information, satellite positioning accuracy information, and satellite signal strength information from the information set.
  • the receiver After the mapping, the receiver has a lot of original observation information, and it is necessary to select a part of the original observations with better positioning effect, which includes: assuming that the original observation set of all K nodes is W, the algorithm selects one original observation at a time. Observation collection And add to the selected original observation set Q.
  • the selection process of the set U should consider the geometric distribution of the satellite, the signal strength of the satellite, and the positioning quality of the satellite, which respectively correspond to the three indicators of satellite distance, signal-to-noise ratio, and positioning accuracy.
  • the selected satellites need to be sufficiently separated from each other to ensure a good geometric distribution.
  • This patent uses the average distance between satellites to measure the geometric distribution.
  • the selected satellite set is Q, and the distance between each satellite in the candidate satellite set W-Q and the satellite in Q needs to be calculated, namely:
  • the selected satellite is considered to be sufficiently separated from Q, where ⁇ d is the distance threshold.
  • the signal-to-noise ratio of each original observation m is SNR(m). If the signal-to-noise ratio is high enough, the satellite signal is considered to be more reliable. If SNR(m)> ⁇ S , it is considered that the signal-to-noise ratio of the selected satellite is sufficiently high, where ⁇ S is the signal-to-noise ratio threshold.
  • the positioning contribution of each original observation should be strong enough to ensure that it can be used for positioning calculations. If DOP(m)> ⁇ P , it is considered that the positioning contribution of the selected satellite is sufficiently high, where ⁇ P is the positioning contribution threshold.
  • a satellite in the set WQ satisfies the three conditions of d> ⁇ d , SNR(m)> ⁇ S , and DOP(m)> ⁇ P at the same time, it is added to the set Q of the selected satellites.
  • the three threshold parameters ⁇ d , ⁇ S , and ⁇ P will be iterated step by step in the selection process, ensuring that only one optimal satellite (corresponding to an optimal satellite original observation) is added to the set Q at a time.
  • the asynchronous CTN positioning method includes:
  • the original observation set can be updated among them Is the distance between node B 1 and satellite S j ; thus, the increment of the original observation can be updated Use ⁇ M 1 to update the position increment ⁇ p;
  • the position increment ⁇ p xyz of node B 1 is much smaller than the pseudo-range M 1 , so
  • the matrix form is:
  • the least square method is used to obtain the exact position of the seed node according to the clock deviation and the coarse time deviation;
  • each node Since each receiver has independent clock deviation t b and coarse time deviation t c , and N nodes are selected, each node contributes q i original observations; then the offset of the seed node is
  • the matrix form is:
  • a cooperative positioning apparatus 100 includes:
  • a plurality of satellite signal collection modules 110 are used to obtain satellite signals independently collected by a plurality of receiver nodes, and the satellite signals include satellite pseudorange, satellite positioning accuracy, satellite signal strength, and satellite clock deviation information;
  • the mapping module 120 uses the receiver node with the best positioning accuracy as a seed node, and maps the satellite signals collected by other receiver nodes to the seed node to form an original observation information set;
  • the information selection module 130 selects the optimal satellite pseudorange information, satellite positioning accuracy information, and satellite signal strength information by iteration based on the original observation information set;
  • Asynchronous CTN positioning module 140 according to the three-dimensional position of the node to be positioned, the clock deviation of the node, and the coarse positioning time deviation of the node, iteratively obtains the position iteration increment that meets the requirements by using the least square method; further according to the clock deviation and the coarse time deviation
  • the least square method is used to obtain the exact position of the seed node; finally, the geometric position of each node is used to calculate the precise position of the other nodes.
  • a computer device has a processor and a memory, and the memory stores a computer program, and when the computer program is executed by the processor, the processor is caused to perform the steps of the cooperative positioning method of any of the foregoing embodiments.
  • the invention has been experimentally verified under a typical urban environment.
  • the experimental scene is in a densely populated urban community with an experimental area of 650 ⁇ 300 square meters.
  • 12 satellite receiver nodes are randomly arranged, and the distribution of each node is shown in Figure 5.
  • Each node continuously samples 5 minutes of satellite data and performs satellite positioning calculations. It was found that only nodes 4, 5, 7, and 10 could complete positioning independently. Compared with the real position, the positioning errors are 76.1 meters, 86.4 meters, 36.0 meters, and 43.2 meters. Among them, the real position is obtained by recording the current position and then searching Google Earth. The remaining eight nodes have too few visible satellites, or the signal offset error is too large to calculate their positions independently. In other words, the positioning accuracy of these 12 nodes is (as shown in Table 1):
  • the positioning accuracy of the node 7 is improved from 36.0 meters to 15.2 meters, and the remaining nodes have correspondingly obtained high-precision positioning positions.
  • the positioning of this patent is superior to the independent positioning of each node.
  • the average positioning accuracy of the four nodes of the independent positioning method is 60.4 meters
  • the average positioning accuracy of the patented method is 20.4 meters
  • the positioning accuracy is improved by 2.96 times.
  • this patent uses the distance and direction of each node. If these constraints are present, the positions of nodes 4, 5, 7, and 10 that can be independently located can also be transferred to the other 8 nodes. This method is called positioning-level collaboration. As a difference, this patent is an original observation-level satellite collaboration, which has penetrated into the node positioning, and there is an essential difference between the two.
  • the positioning accuracy of these 12 nodes is shown in the following table.
  • the average positioning accuracy of the 12 nodes is 41.2 meters. After calculation, the positioning accuracy of the patented method is improved by 2.02 times than the positioning-level collaboration method.
  • the present invention provides a collaborative positioning method and device, computer equipment, and storage medium. It proposes an asynchronous CTN positioning method for the time difference error of multiple nodes; this patent does not require auxiliary sensors (such as inertial navigation, etc.), nor does it require 3D. Prior knowledge such as maps does not need to obtain a more accurate initial position in advance and can also complete position calculation in the case of fewer visible satellites, thereby solving the positioning problem in complex urban environments.
  • the technical solution of the present invention is used The positioning accuracy can be improved by 2-3 times compared with the existing positioning accuracy.

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Abstract

一种协作定位方法与装置、计算机设备、存储介质，方法包括：获取多个接收机节点独立采集的卫星信号（S1）；将其中定位精度最好的接收机节点作为种子节点，将其他接收机节点采集的卫星信号映射到种子节点，形成原始观测量信息集（S2）；根据原始观测量信息集通过迭代选择最优卫星伪距信息、卫星定位精度信息、卫星信号强度信息（S3）；利用异步CTN定位方式计算待定位节点的精确位置信息（S3）。该协作定位方法可用于解决复杂城市环境下的定位问题。

Description

一种协作定位方法与装置、计算机设备、存储介质 技术领域
本发明属于导航、定位技术领域，具体涉及一种协作定位方法与装置、计算机设备、存储介质。
背景技术
卫星定位系统包括空间站、地面站和用户接收机三个组成部分，空间站的卫星不断往外广播自己的位置和时间，地面站监测和控制卫星的运行状态，用户接收机采集广播的卫星信号，如果能捕获到4个以上可见卫星就能计算出自己的位置。卫星定位不需要额外的辅助设备，能独立自主定位，在晴朗可见的环境下能提供10米左右定位精度，已经成为人们日常生活的重要定位手段。
在城市环境中，由于高楼、高架桥等建筑物的遮挡和影响，卫星信号非常微弱，而且，建筑物还会引起多径、非视线接收等干扰，导致卫星信号产生很大的偏移，经常无法定位，或者定位结果存在很大的偏差，经常会有几十米、上百米的定位误差，影响着实际定位需求。在复杂城市环境下，如何设计和实现一个GPS高精度定位算法，仍是一个很有挑战的问题。
随着智能终端的普及，人们对室外导航、定位的需求不断增长，但是城市高楼附近，GPS经常定位失败、或者定位误差特别大，给智能终端的定位带来很多不便之处。
文献[1]C.Bo,X.Li,T.Jung,X.Mao,Y.Tao,and L.Yao.SmartLoc:Push the Limit of the Inertial Sensor Based Metropolitan Localization Using Smartphone.ACM MobiCom,2013，公开了在GPS定位失败时候，使用惯性传感器来辅助定位，提共一个位置参考。文献[1]方法的缺点是，当GPS不工作，惯性导航定位精度特别低，只能提供几十米甚至几百米的定位精度，而且惯导的累加误差特别大，难以满足终端的定位需求。
文献[2]A.Bilich,P.Axelrad,K.M.Larson.Scientific utility of the signal-to-noise ratio(SNR)reported by geodetic GPS receivers.Proc.of ION  GNSS,2007，公开了检测出GPS多径信号，去掉多径卫星，希望能降低定位误差。文献[2]只能适用于可见卫星较多的场合。在高楼等恶劣环境下，可见卫星数目较少，去掉多径卫星后，经常无法定位。
文献[3]P.D.Groves.Shadow matching:A new GNSS positioning technique for urban canyons.Journal of Navigation,2011公开了，利用周边建筑物的3D模型，来检测干扰卫星，降低定位误差。文献[3]需要事先有周边建筑的3D模型，目前很难大规模获取。而且，文献[3]还需要有一个比较准确的初始位置作为定位参考，在实际环境下也很难保证。
发明内容
针对以上问题，本发明旨在提供一种不依赖于累加误差大的惯导等器件，也不需要3D模型、初始位置等前提条件，而且能在可见卫星较少的场合下，也能完成位置计算，从而解决复杂城市环境下定位问题的协作定位方法。
为解决上述技术问题，本发明采用的一个技术方案是：提供一种协作定位方法，包括如下步骤：
利用异步CTN定位方式计算待定位节点的精确位置信息；所述异步CTN定位方式包括：
根据待定位节点的三维位置、节点的时钟偏差、节点的粗定位时间偏差利用最小二乘法通过迭代方式得到符合要求的位置迭代增量；
再进一步根据时钟偏差和粗时间偏差使用最小二乘法得到种子节点的精确位置；
最后利用各个节点之间的几何关系计算出其他节点的精度位置。
在其中一个实施例中，在利用异步CTN定位方式之前还包括步骤：
获取多个接收机节点独立采集的卫星信号，所述卫星信号包括卫星伪距、卫星定位精度、卫星信号强度和卫星时钟偏差信息；
将其中定位精度最好的接收机节点作为种子节点，将其他接收机节点采集的卫星信号映射到种子节点，形成原始观测量信息集；
根据原始观测量信息集通过迭代选择最优卫星伪距信息、卫星定位精度信息、卫星信号强度信息。
在其中一个实施例中，所述映射方法为：根据种子节点的卫星伪距，利用映射节点与种子节点的距离和方向，得到映射节点的卫星伪距。
在其中一个实施例中，所述“选择最优卫星伪距信息、卫星定位精度信息、卫星信号强度信息”步骤具体包括，通过设定距离阈值、信噪比阈值、定位贡献阈值初步选择出符合要求的信息集合，进一步通过迭代方式从信息集合中选择出最优卫星伪距信息、卫星定位精度信息、卫星信号强度信息。
在其中一个实施例中，位置迭代增量计算过程如下：
预设节点B 1的位置p＝[x,y,z,t b,t c] T，每个迭代的位置增量δp＝[δx,δy,δz,δt b,δt c] T；首先初始化p＝[0,0,0,0,0] T；
已知位置p后，就可以更新原始观测量集合
Figure PCTCN2019124204-appb-000001
其中
Figure PCTCN2019124204-appb-000002
是节点B 1和卫星S j的距离；从而，可以更新原始观测量的增量
Figure PCTCN2019124204-appb-000003
使用δM 1来更新位置增量δp；
节点B 1的位置增量δp xyz来远小于伪距M 1，因此
Figure PCTCN2019124204-appb-000004
因此，δM 1和δp的关系可以综合如下：
Figure PCTCN2019124204-appb-000005
矩阵形式为：
δM 1＝H·δp
Figure PCTCN2019124204-appb-000006
使用最小二乘法求解上面的矩阵δM 1＝H·δp，得到δp＝(H TH) -1H TδM 1；
重复步骤上述直至位置迭代增量小于预设数值。
在其中一个实施例中，所述种子节点精确位置计算过程如下：
由于各个接收机的均有独立的时钟偏差t b和粗时间偏差t c，并选中了N个节点，每个节点贡献q i个原始观测量；那么种子节点的偏移量为
Figure PCTCN2019124204-appb-000007
Figure PCTCN2019124204-appb-000008
矩阵形式为:
δM＝H·δp
Figure PCTCN2019124204-appb-000009
使用最小二乘法求解上述矩阵，可以得到种子节点的精确位置。
作为一种优选方式，所述步骤“选择最优卫星伪距信息”中，选择出符合要求的卫星需要彼此足够分隔开，具有有良好的几何分布。
一种协作定位装置，包括：
多个卫星信号采集模块，用以获取多个接收机节点独立采集的卫星信号，所述卫星信号包括卫星伪距、卫星定位精度、卫星信号强度和卫星时钟偏差信息；
映射模块，将其中定位精度最好的接收机节点作为种子节点，将其他接收机节点采集的卫星信号映射到种子节点，形成原始观测量信息集；
信息选择模块，根据原始观测量信息集通过迭代选择最优卫星伪距信息、卫星定位精度信息、卫星信号强度信息；
异步CTN定位模块，根据待定位节点的三维位置、节点的时钟偏差、节点的粗定位时间偏差利用最小二乘法通过迭代方式得到符合要求的位置迭代增量；再进一步根据时钟偏差和粗时间偏差使用最小二乘法得到种子节点的精确位置；最后利用各个节点之间的几何关系计算出其他节点的精度位置。
一种计算机设备，具有处理器和存储器，所述存储器存储有计算机程序，所述计算机程序被所述处理器执行时，使得所述处理器执行上述任一实施例的协作定位方法的步骤。
一种计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器执行时，使得所述处理器执行上述任一实施例的协作定位方法的步骤。
本发明一种协作定位方法与装置、计算机设备、存储介质，针对多个节点的时差误差问题，提出一种异步CTN定位方法；本专利不需要辅助传感器(如惯导等)，也不需要3D地图等先验知识，也不需要事先获取一个比较准确的初始位置而且能在可见卫星较少的场合下，也能完成位置计算，从而解决复杂城市环境下的定位问题协，利用本发明技术方案可以将定位精度较现有定位精度提升2-3倍。
附图说明
图1是本发明一种协作定位方法的流程示意图；
图2是本发明一种协作定位装置的模块结构示意图；
图3是本发明原始观测量的映射示意图；
图4是本发明CTN方法从位置P到位置P′的迭代过程示意图；
图5是实施例中各个节点的位置分布示意图；
图6是三种方法的定位精度对比示意图。
具体实施方式
以下结合图1-6具体说明本发明提供的一种协作定位方法与装置、计算机设备、存储介质。
如图1所示，本发明提供一种协作定位方法，包括如下步骤：
S1、获取多个接收机节点独立采集的卫星信号，所述卫星信号包括卫星伪距、卫星定位精度、卫星信号强度和卫星时钟偏差信息；
S2、原始观测量的映射；将其中定位精度最好的接收机节点作为种子节点，将其他接收机节点采集的卫星信号映射到种子节点，形成原始观测量信息集；
在不同位置各有一个卫星接收机，多个接收机均独立采集卫星信号。为了实现高精度定位，我们先选中一个定位精度较好的接收机，然后将其他卫星接收机的信号都映射到这个接收机。
映射的方式为根据种子节点的卫星伪距，利用映射节点与种子节点的距离和方向，得到映射节点的卫星伪距。具体的，假设有K个接收机节点，各个 节点之间的距离和方向已经事先测量得到。节点集合为V＝{B 1,B 2,...,B K}，节点B i和B j之间的单位方向方向为e ij。每个节点均有一个卫星接收机，节点B i可以观察到z i个卫星信号，每个卫星卫星均对应于一个原始观测量，因此节点B i的卫星信号原始观测量集合为
Figure PCTCN2019124204-appb-000010
节点B i的卫星定位精度为DOP(B i)。
在原始观测量映射前，首先要选择一个具有代表性的节点，即：种子节点。种子节点具有最大的定位精度DOP(B i)，然后将其他节点的原始观测量都映射到种子节点B l。
如图3所示是卫星原始观测量映射的图示。假设节点B 2能观察到卫星S，但节点B 1不能直接观察到卫星S(例如，被建筑物挡住了)，我们希望将节点B 2的原始观测量映射到B 1。也就是说，现在已知B 2到卫星S的伪距m 2S，也知道B 1和B 2之间的距离和方向，需要求解出B 1到卫星S的伪距m 1S。
考虑到卫星到节点的伪距m大约是几十万千米，要远大于节点之间的距离|B 1B 2|(通常仅几十米、或者几百米)。从图3可以近似得到
Figure PCTCN2019124204-appb-000011
因此，
Figure PCTCN2019124204-appb-000012
S3、根据原始观测量信息集通过迭代选择最优卫星伪距信息、卫星定位精度信息、卫星信号强度信息；
所述“选择最优卫星伪距信息、卫星定位精度信息、卫星信号强度信息”步骤具体包括，通过设定距离阈值、信噪比阈值、定位贡献阈值初步选择出符合要求的信息集合，进一步通过迭代方式从信息集合中选择出最优卫星伪距信息、卫星定位精度信息、卫星信号强度信息。
由于经过映射后，该接收机有很多原始观测量信息，需要从中选择定位效果较好的一部分原始观测量，具体包括：假设所有K个节点的原始观测量集合为W，算法每次选中一个原始观测量集合
Figure PCTCN2019124204-appb-000013
并加入到已选中的原始观测量集合Q。集合U的选择过程要考虑卫星的几何分布、卫星信号强度、卫星的定位质量，分别对应于卫星距离、信噪比、定位精度这三个指标。
卫星距离
选中的卫星需要彼此足够分隔开，保证有良好的几何分布。本专利使用卫星两两之间的平均距离，来衡量几何分布。在具体实现中，已选中的卫星集合为Q，需要计算待选卫星集合W-Q中的每一个卫星到Q中的卫星的距离，即：
Figure PCTCN2019124204-appb-000014
B i∈W-Q,B j∈Q
如果d＞δ d，则认为选中卫星与Q足够分隔开，其中δ d为距离阈值。
卫星信号强度
假设每个原始观测量m的信噪比为SNR(m)，如果信噪比足够高，则认为卫星信号较为可靠。如果SNR(m)＞δ S，则认为选中卫星信噪比足够高，其中δ S为信噪比阈值。
卫星定位精度
每个原始观测量的定位贡献应该足够强，保证能用于定位计算。如果DOP(m)＞δ P，则认为选中卫星的定位贡献足够高，其中δ P为定位贡献阈值。
如果集合W-Q中的某个卫星同时满足d＞δ d，SNR(m)＞δ S，DOP(m)＞δ P的三个条件，则加入到选中卫星的集合Q。其中，三个阈值参数δ d、δ S、δ P在选择过程中会逐步迭代，保证每次仅有一个最优的卫星(对应于一个最优的卫星原始观测量)加入到集合Q。
S4、利用异步CTN定位方式计算待定位节点的精确位置信息；所述异步CTN定位方式包括：
S41、根据待定位节点的三维位置、节点的时钟偏差、节点的粗定位时间偏差利用最小二乘法通过迭代方式得到符合要求的位置迭代增量；
如图4所示，具体位置迭代增量计算过程如下：
预设节点B 1的位置p＝[x,y,z,t b,t c] T，每个迭代的位置增量δp＝[δx,δy,δz,δt b,δt c] T；首先初始化p＝[0,0,0,0,0] T；
已知位置p后，就可以更新原始观测量集合
Figure PCTCN2019124204-appb-000015
其中
Figure PCTCN2019124204-appb-000016
是节点B 1和卫星S j的距离；从而，可以更新原始观测量的增量
Figure PCTCN2019124204-appb-000017
使用δM 1来更新位置增量δp；
节点B 1的位置增量δp xyz来远小于伪距M 1，因此
Figure PCTCN2019124204-appb-000018
因此，δM 1和δp的关系可以综合如下：
Figure PCTCN2019124204-appb-000019
矩阵形式为：
δM 1＝H·δp
Figure PCTCN2019124204-appb-000020
使用最小二乘法求解上面的矩阵δM 1＝H·δp，得到δp＝(H TH) -1H TδM 1；
重复步骤上述直至位置迭代增量小于预设数值。
S42、再进一步根据时钟偏差和粗时间偏差使用最小二乘法得到种子节点的精确位置；
具体的，所述种子节点精确位置计算过程如下：
由于各个接收机的均有独立的时钟偏差t b和粗时间偏差t c，并选中了N个节点，每个节点贡献q i个原始观测量；那么种子节点的偏移量为
Figure PCTCN2019124204-appb-000021
Figure PCTCN2019124204-appb-000022
矩阵形式为:
δM＝H·δp
Figure PCTCN2019124204-appb-000023
使用最小二乘法求解上述矩阵，可以得到种子节点的精确位置。
S43、最后利用各个节点之间的几何关系计算出其他节点的精度位置。
如图2所示，一种协作定位装置100，包括：
多个卫星信号采集模块110，用以获取多个接收机节点独立采集的卫星信号，所述卫星信号包括卫星伪距、卫星定位精度、卫星信号强度和卫星时钟偏差信息；
映射模块120，将其中定位精度最好的接收机节点作为种子节点，将其他接收机节点采集的卫星信号映射到种子节点，形成原始观测量信息集；
信息选择模块130，根据原始观测量信息集通过迭代选择最优卫星伪距信息、卫星定位精度信息、卫星信号强度信息；
异步CTN定位模块140，根据待定位节点的三维位置、节点的时钟偏差、节点的粗定位时间偏差利用最小二乘法通过迭代方式得到符合要求的位置迭代增量；再进一步根据时钟偏差和粗时间偏差使用最小二乘法得到种子节点的精确位置；最后利用各个节点之间的几何关系计算出其他节点的精度位置。
一种计算机设备，具有处理器和存储器，所述存储器存储有计算机程序，所述计算机程序被所述处理器执行时，使得所述处理器执行上述任一实施例的协作定位方法的步骤。
一种计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器执行时，使得所述处理器执行上述任一实施例的协作定位方法的步骤。
本发明在一个典型城市环境下进行了实验验证。实验场景在一个高楼密集的城市小区，实验面积为650×300平方米。实验过程随机布置12个卫星接收机节点，各节点分布如图5所示。
每个节点均连续采样5分钟卫星数据，并进行卫星定位计算。结果发现，只有节点4、5、7、10能够独立完成定位。与真实位置对比，定位误差分别为76.1米，86.4米，36.0米，43.2米。其中，真实位置是通过记录当前位置，再查找谷歌地球来获取的。其余8个节点的可见卫星过少、或者信号偏移误差太大，无法独立计算出自己的位置。也就是说，这12个节点的定位精度为(如表1)：
表1
Figure PCTCN2019124204-appb-000024
为了实现本专利的方法，我们先用计步器和磁传感器来测量各个节点之间的距离和方向。然后选择定位精度较好的节点7作为种子节点，并将其他11个节点的原始观测量都映射到节点7。按照上述专利方法，选择合适的原始观测量，进行异步CTN定位。最后，利用各个节点之间的距离、方向关系，计算出其他11个节点的位置。经过计算，这12个节点的定位精度如表2：
表2
Figure PCTCN2019124204-appb-000025
可以看出，经过原始观测量级的协同定位后，节点7的定位精度从36.0米提高到15.2米，其余节点也相应获取了高精度定位位置。
对比发现，本专利的定位均优于各个节点的独立定位。在具体数值上，独立定位方法的4个节点的平均定位精度为60.4米，本专利方法的平均定位精度为20.4米，定位精度提高2.96倍。
此外，本专利使用了各个节点的距离和方向。如果有了这些约束条件，其实也可以将能独立定位的节点4、5、7、10的位置传递到其他8个节点。这种方法被称为定位级的协作。作为区别，本专利是原始观测量级的卫星协作，已经深入到节点定位内部，两者有本质的区别。
我们也实现了定位级协作方法，利用距离和方向关系计算其他节点的位置，这12个节点的定位精度如下表，12个节点的平均定位精度为41.2米。经过计算，本专利方法的定位精度比定位级协作方法提高了2.02倍。
如图6所示，对比了本专利方法、定位级协作方法、独立卫星定位方法的定位精度。可以发现，本专利的定位结果更好，提高2.02～2.96倍。
表3
Figure PCTCN2019124204-appb-000026
本发明一种协作定位方法与装置、计算机设备、存储介质，针对多个节点的时差误差问题，提出一种异步CTN定位方法；本专利不需要辅助传感器(如惯导等)，也不需要3D地图等先验知识，也不需要事先获取一个比较准确的初始位置而且能在可见卫星较少的场合下，也能完成位置计算，从而解决复杂城市环境下的定位问题协，利用本发明技术方案可以将定位精度较现有定位精度提升2-3倍。
以上所述仅为本发明的实施方式，并非因此限制本发明的专利范围，凡是利用本发明说明书及附图内容所作的等效结构或等效流程变换，或直接或间接运用在其他相关的技术领域，均同理包括在本发明的专利保护范围内。

Claims (10)

  1. 一种协作定位方法，其特征在于，包括如下步骤：
    利用异步CTN定位方式计算待定位节点的精确位置信息；所述异步CTN定位方式包括：
    根据待定位节点的三维位置、节点的时钟偏差、节点的粗定位时间偏差利用最小二乘法通过迭代方式得到符合要求的位置迭代增量；
    再进一步根据时钟偏差和粗时间偏差使用最小二乘法得到种子节点的精确位置；
    最后利用各个节点之间的几何关系计算出其他节点的精度位置。
  2. 如权利要求1所述的协作定位方法，其特征在于，在利用异步CTN定位方式之前还包括步骤：
    获取多个接收机节点独立采集的卫星信号，所述卫星信号包括卫星伪距、卫星定位精度、卫星信号强度和卫星时钟偏差信息；
    将其中定位精度最好的接收机节点作为种子节点，将其他接收机节点采集的卫星信号映射到种子节点，形成原始观测量信息集；
    根据原始观测量信息集通过迭代选择最优卫星伪距信息、卫星定位精度信息、卫星信号强度信息。
  3. 如权利要求2所述的协作定位方法，其特征在于，所述映射方法为：根据种子节点的卫星伪距，利用映射节点与种子节点的距离和方向，得到映射节点的卫星伪距。
  4. 如权利要求2所述的协作定位方法，其特征在于，所述“选择最优卫星伪距信息、卫星定位精度信息、卫星信号强度信息”步骤具体包括，通过设定 距离阈值、信噪比阈值、定位贡献阈值初步选择出符合要求的信息集合，进一步通过迭代方式从信息集合中选择出最优卫星伪距信息、卫星定位精度信息、卫星信号强度信息。
  5. 如权利要求1所述的协作定位方法，其特征在于，位置迭代增量计算过程如下：
    预设节点B 1的位置p＝[x,y,z,t b,t c] T，每个迭代的位置增量δp＝[δx,δy,δz,δt b,δt c] T；首先初始化p＝[0,0,0,0,0] T；
    已知位置p后，就可以更新原始观测量集合
    Figure PCTCN2019124204-appb-100001
    其中
    Figure PCTCN2019124204-appb-100002
    是节点B 1和卫星S j的距离；从而，可以更新原始观测量的增量
    Figure PCTCN2019124204-appb-100003
    Figure PCTCN2019124204-appb-100004
    使用δM 1来更新位置增量δp；
    节点B 1的位置增量δp xyz来远小于伪距M 1，因此
    Figure PCTCN2019124204-appb-100005
    因此，δM 1和δp的关系可以综合如下：
    Figure PCTCN2019124204-appb-100006
    矩阵形式为：
    δM 1＝H·δp
    Figure PCTCN2019124204-appb-100007
    使用最小二乘法求解上面的矩阵δM 1＝H·δp，得到δp＝(H TH) -1H TδM 1；
    重复步骤上述直至位置迭代增量小于预设数值。
  6. 如权利要求1所述的协作定位方法，其特征在于，所述种子节点精确位置计算过程如下：
    由于各个接收机的均有独立的时钟偏差t b和粗时间偏差t c，并选中了N个节点，每个节点贡献q i个原始观测量；那么种子节点的偏移量为
    Figure PCTCN2019124204-appb-100008
    Figure PCTCN2019124204-appb-100009
    矩阵形式为:
    δM＝H·δp
    Figure PCTCN2019124204-appb-100010
    使用最小二乘法求解上述矩阵，可以得到种子节点的精确位置。
  7. 如权利要求4所述的协作定位方法，其特征在于，所述步骤“选择最优卫星伪距信息”中，选择出符合要求的卫星需要彼此足够分隔开，具有有良好的几何分布。
  8. 一种协作定位装置，其特征在于，包括：
    多个卫星信号采集模块，用以获取多个接收机节点独立采集的卫星信号，所述卫星信号包括卫星伪距、卫星定位精度、卫星信号强度和卫星时钟偏差信息；
    映射模块，将其中定位精度最好的接收机节点作为种子节点，将其他接收机节点采集的卫星信号映射到种子节点，形成原始观测量信息集；
    信息选择模块，根据原始观测量信息集通过迭代选择最优卫星伪距信息、 卫星定位精度信息、卫星信号强度信息；
    异步CTN定位模块，根据待定位节点的三维位置、节点的时钟偏差、节点的粗定位时间偏差利用最小二乘法通过迭代方式得到符合要求的位置迭代增量；再进一步根据时钟偏差和粗时间偏差使用最小二乘法得到种子节点的精确位置；最后利用各个节点之间的几何关系计算出其他节点的精度位置。
  9. 一种计算机设备，其特征在于，具有处理器和存储器，所述存储器存储有计算机程序，所述计算机程序被所述处理器执行时，使得所述处理器执行如权利要求1～7任一项所述的协作定位方法的步骤。
  10. 一种计算机可读存储介质，其上存储有计算机程序，其特征在于，所述计算机程序被处理器执行时，使得所述处理器执行如权利要求1～7任一项所述的协作定位方法的步骤。
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