WO2018121361A1 - 智能反向寻车方法 - Google Patents

智能反向寻车方法 Download PDF

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WO2018121361A1
WO2018121361A1 PCT/CN2017/117276 CN2017117276W WO2018121361A1 WO 2018121361 A1 WO2018121361 A1 WO 2018121361A1 CN 2017117276 W CN2017117276 W CN 2017117276W WO 2018121361 A1 WO2018121361 A1 WO 2018121361A1
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car
vehicle
value
rssi
broadcast frame
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PCT/CN2017/117276
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French (fr)
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赖建文
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上海蔚来汽车有限公司
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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
    • G01S11/00—Systems for determining distance or velocity not using reflection or reradiation
    • G01S11/02—Systems for determining distance or velocity not using reflection or reradiation using radio waves
    • G01S11/06—Systems for determining distance or velocity not using reflection or reradiation using radio waves using intensity measurements
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/123—Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams
    • H04W4/046—

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  • the invention relates to the field of intelligent positioning of vehicles, in particular to a smart reverse car-seeking method.
  • the present invention proposes an intelligent reverse car finder method, which improves the accuracy of distance estimation.
  • the invention provides an intelligent reverse car finder method, which comprises the following steps:
  • Step 1 transmitting a broadcast frame to the surroundings by a wireless signal broadcasting device disposed in the searched vehicle;
  • Step 2 When the wireless signal receiving module in the car-searching device receives the broadcast frame, calculate a distance between the searched vehicle and the car-seeking device according to the broadcast frame signal strength.
  • the calculating the distance between the searched vehicle and the car-seeking device according to the broadcast frame signal strength specifically: the signal strength of the broadcast frame transmitted according to the wireless signal broadcasting device in the searched vehicle, and the car-seeking device
  • the signal strength of the broadcast frame received by the wireless signal receiving module determines the distance between the car finder and the vehicle being sought.
  • the signal strength indication value RSSI Reference Signal Strength Indicator
  • the indication value RSSI is corrected by an adaptive filter based on the accelerations in the three directions of the x, y, and z axes of the gyroscope in the car-hunting device, and the updated indication value RSSI new is obtained .
  • the adaptive filter is used to correct the indication value RSSI, which specifically includes:
  • Step 21 Filter according to the acceleration value of the gyroscope in the x-axis direction of the car-seeking device, and the formula is as follows:
  • e(n) represents the RSSI value after the x-axis correction
  • x x (n) represents the acceleration value of the x-axis acquired by the gyroscope at the nth time
  • w 1 (n) represents the finite length of the length L+1 Digital filter vector
  • y(n) represents the vector of the RSSI value collected from nL time to the nth time, the length is L+1
  • b and ⁇ are constant, and are adjusted according to actual performance requirements
  • step 22 e(n) is taken as an input, and filtering is performed according to the acceleration value of the gyro y-axis direction, and the formula is as follows:
  • f(n) represents the RSSI value after the y-axis correction
  • x y (n) represents the acceleration value of the y-axis acquired by the gyroscope at the nth time
  • w 2 (n) represents the finite length of the length L+1 Digital filter vector
  • step 23 f(n) is taken as an input, and filtering is performed according to the acceleration value of the gyroscope in the z-axis direction, and the formula is as follows:
  • g(n) represents the RSSI value after the z-axis correction
  • x z (n) represents the acceleration value of the z-axis acquired by the gyroscope at the nth time
  • w 3 (n) represents the finite length of the length L+1 Digital filter vector
  • step 24 g(n) is subjected to three-point smoothing filtering to obtain the processed RSSI value, and the formula is as follows:
  • RSSI new (n) ⁇ g(n-1)+ ⁇ g(n)+ ⁇ g(n+1),
  • the specific method is:
  • d is the calculated distance between the searched vehicle and the car-seeking device
  • ⁇ is the fading factor of the wireless environment
  • r 1 is the received signal strength at 1 meter
  • the unit is dBm
  • d 0 is the preset ranging Correction value.
  • the RSSI new value is the corrected signal strength indication value obtained by iteratively performing the two steps 21 to 24.
  • the wireless signal is a Bluetooth signal or a WiFi signal
  • the signal strength of the broadcast frame sent by the wireless signal broadcasting device in the searched vehicle is a signal strength r 1 received at a distance of 1 meter from the broadcast device.
  • the wireless signal broadcasting device transmits a broadcast frame according to a preset interval.
  • the broadcast frame includes the license plate number of the sought vehicle and the owner information; the car finder may parse the information contained in the broadcast frame for finding the corresponding vehicle.
  • the range of ⁇ is [0.05, 0.2], the range of ⁇ is [0.4, 0.6], and the range of ⁇ is [0.1, 0.3].
  • the invention is based on the acceleration of the x, y, and z axes of the gyroscope in the car finder, and corrects the RSSI value, and further eliminates the RSSI jitter caused by the movement of the car finder by the iterative manner of steps 21 to 24. In this way, the distance between the vehicle being searched and the car-seeking device can be calculated more accurately; the formula with the highest universal distance is used to avoid the need to reconstruct the distance calculation formula due to different scenes.
  • Fig. 1 is a flow chart of this embodiment.
  • the invention proposes an intelligent reverse car finder method, as shown in FIG. 1 , comprising the following steps:
  • Step 1 transmitting a broadcast frame to the surroundings by a wireless signal broadcasting device disposed in the searched vehicle;
  • Step 2 When the wireless signal receiving module in the car finding device receives the broadcast frame, calculate a distance between the searched vehicle and the car finder according to the broadcast frame signal strength.
  • the car finder device comprises a wireless signal receiving module, a gyroscope and a gyroscope acceleration collecting module.
  • the distance between the searched vehicle and the car-seeking device is calculated according to the broadcast frame signal strength, specifically: the signal strength of the broadcast frame sent according to the wireless signal broadcast device in the searched vehicle, and the search
  • the signal strength of the broadcast frame received by the wireless signal receiving module in the vehicle device calculates the distance between the car finder and the vehicle being sought.
  • the signal strength indication value RSSI of the received broadcast frame is iteratively modified by using an adaptive filter, specifically:
  • the indication value RSSI is corrected by an adaptive filter based on the accelerations in the three directions of the x, y, and z axes of the gyroscope in the car-hunting device, and the updated indication value RSSI new is obtained .
  • the adaptive filter is used to modify the indication value RSSI, which specifically includes:
  • Step 21 Filter according to the acceleration value of the gyroscope in the x-axis direction of the car-seeking device, as shown in formula (1):
  • e(n) represents the RSSI value after the x-axis correction
  • x x (n) represents the acceleration value of the x-axis acquired by the gyroscope at the nth time
  • w 1 (n) represents the finite length of the length L+1 Digital filter vector
  • y(n) represents the vector of the RSSI value collected from nL time to the nth time, the length is L+1
  • b and ⁇ are constant, and are adjusted according to actual performance requirements
  • step 22 e(n) is taken as an input, and filtering is performed according to the acceleration value in the y-axis direction of the gyroscope, as shown in the formula (3):
  • f(n) represents the RSSI value after the y-axis correction
  • x y (n) represents the acceleration value of the y-axis acquired by the gyroscope at the nth time
  • w 2 (n) represents the finite length of the length L+1 Digital filter vector
  • step 23 f(n) is taken as an input, and filtering is performed according to the acceleration value of the gyroscope in the z-axis direction, as shown in the formula (5):
  • g(n) represents the RSSI value after the z-axis correction
  • x z (n) represents the acceleration value of the z-axis acquired by the gyroscope at the nth time
  • w 3 (n) represents the finite length of the length L+1 Digital filter vector
  • step 24 g(n) is subjected to three-point smoothing filtering to obtain the processed RSSI value, as shown in formula (7):
  • RSSI new (n) ⁇ g(n-1)+ ⁇ g(n)+ ⁇ g(n+1) (7)
  • the distance between the searched vehicle and the car-seeking device is calculated, and the specific method is as shown in formula (8):
  • d is the calculated distance between the searched vehicle and the car-seeking device
  • ⁇ is the fading factor of the wireless environment
  • r 1 is the received signal strength at 1 meter
  • the unit is dBm
  • d 0 is the preset ranging Correction value.
  • the RSSI new value is the corrected signal strength indication value obtained by iteratively performing the two steps 21 to 24.
  • the wireless signal is a Bluetooth signal or a WiFi signal
  • the signal strength of the broadcast frame sent by the wireless signal broadcasting device in the searched vehicle is a signal strength r 1 received at a distance of 1 meter from the broadcast device.
  • the wireless signal broadcasting device transmits a broadcast frame according to a preset interval, and the wireless broadcast device in the searched vehicle transmits the wireless broadcast frame every 100 ms.
  • the broadcast frame includes the license plate number of the sought vehicle and the owner information; the car finder may parse the information contained in the broadcast frame for finding the corresponding vehicle.
  • the range of ⁇ is [0.05, 0.2]
  • the range of ⁇ is [0.4, 0.6]
  • the range of ⁇ is [0.1, 0.3].
  • the Bluetooth signal broadcasting device is adopted, and the vehicle to be searched can be effectively positioned in the range of 50-100 m. It is also possible to use a WiFi signal broadcasting device to achieve effective positioning in a wider range, which is determined by the transmission environment and the power of the WiFi signal broadcasting device.

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Abstract

一种智能反向寻车方法，由设置于被寻找车辆内的无线信号广播设备每隔一定时间向周围发送广播帧；寻车装置接收到广播帧后，将广播帧的信号强度指示值RSSI，根据陀螺仪在x、y、z轴三个方向的加速度值进行修正，然后再进行三点平滑滤波；为了更好地消除RSSI的抖动，还对根据陀螺仪加速度值修正和三点平滑滤波的过程进行迭代处理；最后根据修正后的信号强度指示值RSSI new计算出被寻车辆与寻车装置之间的距离。依据该智能反向寻车方法，提高了车辆的定位精度。

Description

智能反向寻车方法 技术领域
本发明涉及车辆的智能定位领域，具体涉及一种智能反向寻车方法。
背景技术
当车辆需要代驾、拖车、更换电池等服务时，工作人员在到达驾驶员指定的大致位置后，经常因为周边车辆众多，并不能快速准确地找到需要服务的车辆。
发明内容
为了解决现有技术中的上述问题，本发明提出了一种智能反向寻车方法，提高了距离估算的精确度。
本发明提出了一种智能反向寻车方法，包括以下步骤：
步骤1，由设置于被寻找车辆内的无线信号广播设备向周围发送广播帧；
步骤2，当寻车装置中的无线信号接收模块接收到上述广播帧时，并根据广播帧信号强度计算所述被寻找车辆与寻车装置之间的距离。
优选的，所述根据广播帧信号强度计算所述被寻找车辆与寻车装置之间的距离，具体为：依据被寻找车辆内的无线信号广播设备发送的广播帧的信号强度、以及寻车装置中的无线信号接收模块所接收到的广播帧的信号强度，计算出寻车装置与被寻找车辆之间的距离。
优选的，在计算寻车装置与被寻找车辆的距离过程中，采用自适应滤波器的方式来迭代修正接收到的广播帧的信号强度指示值RSSI(Reference Signal Strength Indicator)，具体为：
在寻车装置移动时，基于寻车装置中陀螺仪的x、y、z轴三个方向的加速度，采用自适应滤波器对指示值RSSI进行修正，得到更新后的指示值RSSI new。
优选的，所述采用自适应滤波器对指示值RSSI进行修正，具 体包括：
步骤21，根据寻车装置中陀螺仪x轴方向的加速度值进行滤波，公式如下：
Figure PCTCN2017117276-appb-000001
Figure PCTCN2017117276-appb-000002
其中，e(n)表示经过x轴修正后的RSSI值；x x(n)表示第n个时刻陀螺仪采集的x轴的加速度值；w 1(n)表示长度为L+1的有限长数字滤波器向量；y(n)表示从n-L个时刻到第n个时刻采集的RSSI值的向量，长度为L+1；b和μ为常数，根据实际性能需求调整；
步骤22，将e(n)作为输入，根据陀螺仪y轴方向的加速度值进行滤波，公式如下：
Figure PCTCN2017117276-appb-000003
Figure PCTCN2017117276-appb-000004
其中，f(n)表示经过y轴修正后的RSSI值；x y(n)表示第n个时刻陀螺仪采集的y轴的加速度值；w 2(n)表示长度为L+1的有限长数字滤波器向量；
步骤23，将f(n)作为输入，根据陀螺仪z轴方向的加速度值进行滤波，公式如下：
Figure PCTCN2017117276-appb-000005
Figure PCTCN2017117276-appb-000006
其中，g(n)表示经过z轴修正后的RSSI值；x z(n)表示第n个时刻陀螺仪采集的z轴的加速度值；w 3(n)表示长度为L+1的有限长数字滤波器向量；
步骤24，将g(n)进行三点平滑滤波得到处理后的RSSI值，公式如下：
RSSI new(n)＝αg(n-1)+βg(n)+γg(n+1)，
其中α、β、γ为预设的权重系数；
优选的，计算所述被寻找车辆与寻车装置之间的距离，具体方法为：
Figure PCTCN2017117276-appb-000007
其中，d为计算出的被寻找车辆与寻车装置之间的距离，δ为无线环境的衰落因子，r 1为1米处接收到的信号强度，单位dBm，d 0为预设的测距修正值。
优选的，被寻找车辆与寻车装置之间距离d的计算公式中，RSSI new值为迭代执行两次步骤21至步骤24所得到的修正后的信号强度指示值。
优选的，所述无线信号为蓝牙信号或WiFi信号；所述被寻找车辆内的无线信号广播设备发送的广播帧的信号强度，是在距离广播设备1米处接收到的信号强度r 1。
优选的，所述无线信号广播设备按照预设的间隔发送广播帧。
优选的，广播帧中包含被寻车辆的车牌号、车主信息；所述寻车装置可以解析广播帧中所包含的信息用于寻找相应车辆。
优选的，α取值范围为[0.05,0.2]、β取值范围为[0.4,0.6]、γ取值范围为[0.1,0.3]。
本发明基于寻车装置中陀螺仪的x、y、z轴三个方向的加速度，对RSSI值进行修正，通过步骤21～步骤24的迭代方式进一步消除寻车装置移动所带来的RSSI的抖动，这样能够更加精确地计算出被寻车辆与寻车装置之间的距离；采用普适性最高的距离计算公式，避免了由于场景不同需要重构距离计算公式。
附图说明
图1是本实施例的流程图。
具体实施方式
下面参照附图来描述本发明的优选实施方式。本领域技术人员应当理解的是，这些实施方式仅仅用于解释本发明的技术原理，并非旨在限制本发明的保护范围。
本发明提出了一种智能反向寻车方法，如图1所示，包括以下步骤：
步骤1，由设置于被寻找车辆内的无线信号广播设备向周围发送广播帧；
步骤2，当寻车装置中的无线信号接收模块接收到上述广播 帧时，并根据广播帧信号强度计算所述被寻找车辆与寻车装置之间的距离。
所述寻车装置包括无线信号接收模块、陀螺仪和陀螺仪加速度采集模块。
本实施例中，所述根据广播帧信号强度计算所述被寻找车辆与寻车装置之间的距离，具体为：依据被寻找车辆内的无线信号广播设备发送的广播帧的信号强度、以及寻车装置中的无线信号接收模块所接收到的广播帧的信号强度，计算出寻车装置与被寻找车辆之间的距离。
本实施例中，在计算寻车装置与被寻找车辆的距离过程中，采用自适应滤波器的方式来迭代修正接收到的广播帧的信号强度指示值RSSI，具体为：
在寻车装置移动时，基于寻车装置中陀螺仪的x、y、z轴三个方向的加速度，采用自适应滤波器对指示值RSSI进行修正，得到更新后的指示值RSSI new。
本实施例中，所述采用自适应滤波器对指示值RSSI进行修正，具体包括：
步骤21，根据寻车装置中陀螺仪x轴方向的加速度值进行滤波，如公式(1)所示：
Figure PCTCN2017117276-appb-000008
Figure PCTCN2017117276-appb-000009
其中，e(n)表示经过x轴修正后的RSSI值；x x(n)表示第n个时刻陀螺仪采集的x轴的加速度值；w 1(n)表示长度为L+1的有限长数字滤波器向量；y(n)表示从n-L个时刻到第n个时刻采集的RSSI值的向量，长度为L+1；b和μ为常数，根据实际性能需求调整；
步骤22，将e(n)作为输入，根据陀螺仪y轴方向的加速度值进行滤波，如公式(3)所示：
Figure PCTCN2017117276-appb-000010
Figure PCTCN2017117276-appb-000011
其中，f(n)表示经过y轴修正后的RSSI值；x y(n)表示第n个时刻陀螺仪采集的y轴的加速度值；w 2(n)表示长度为L+1的有限长数字滤波器向量；
步骤23，将f(n)作为输入，根据陀螺仪z轴方向的加速度值进行滤波，如公式(5)所示：
Figure PCTCN2017117276-appb-000012
Figure PCTCN2017117276-appb-000013
其中，g(n)表示经过z轴修正后的RSSI值；x z(n)表示第n个时刻陀螺仪采集的z轴的加速度值；w 3(n)表示长度为L+1的有限长数字滤波器向量；
步骤24，将g(n)进行三点平滑滤波得到处理后的RSSI值，如公式(7)所示：
RSSI new(n)＝αg(n-1)+βg(n)+γg(n+1)     (7)
其中α、β、γ为预设的权重系数；
本实施例中，计算所述被寻找车辆与寻车装置之间的距离，具体方法如公式(8)所示：
Figure PCTCN2017117276-appb-000014
其中，d为计算出的被寻找车辆与寻车装置之间的距离，δ为无线环境的衰落因子，r 1为1米处接收到的信号强度，单位dBm，d 0为预设的测距修正值。
本实施例中，被寻找车辆与寻车装置之间距离d的计算公式中，RSSI new值为迭代执行两次步骤21至步骤24所得到的修正后的信号强度指示值。
本实施例中，所述无线信号为蓝牙信号或WiFi信号；所述被寻找车辆内的无线信号广播设备发送的广播帧的信号强度，是在距离广播设备1米处接收到的信号强度r 1。
本实施例中，所述无线信号广播设备按照预设的间隔发送广播帧，被寻找车辆内的无线广播设备每隔100ms发送一次无线广播帧。
本实施例中，广播帧中包含被寻车辆的车牌号、车主信息；所述寻车装置可以解析广播帧中所包含的信息用于寻找相应车辆。
本实施例中，α取值范围为[0.05,0.2]、β取值范围为[0.4,0.6]、γ取值范围为[0.1,0.3]。
本实施例中，采用蓝牙信号广播设备，能够在50-100m范围内有效定位被寻车辆。还可以采用WiFi信号广播设备，以实现更大范围 内的有效定位，具体范围大小由传输环境和WiFi信号广播设备的功率所决定。
本领域技术人员应该能够意识到，结合本文中所公开的实施例描述的各示例的方法步骤，能够以电子硬件、计算机软件或者二者的结合来实现，为了清楚地说明电子硬件和软件的可互换性，在上述说明中已经按照功能一般性地描述了各示例的组成及步骤。这些功能究竟以电子硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。本领域技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本发明的范围。
至此，已经结合附图所示的优选实施方式描述了本发明的技术方案，但是，本领域技术人员容易理解的是，本发明的保护范围显然不局限于这些具体实施方式。在不偏离本发明的原理的前提下，本领域技术人员可以对相关技术特征作出等同的更改或替换，这些更改或替换之后的技术方案都将落入本发明的保护范围之内。

Claims (10)

  1. 一种智能反向寻车方法，其特征在于，包括以下步骤：
    步骤1，由设置于被寻找车辆内的无线信号广播设备向周围发送广播帧；
    步骤2，当寻车装置中的无线信号接收模块接收到上述广播帧时，并根据广播帧信号强度计算所述被寻找车辆与寻车装置之间的距离。
  2. 根据权利要求1所述的方法，其特征在于，所述根据广播帧信号强度计算所述被寻找车辆与寻车装置之间的距离，具体为：依据被寻找车辆内的无线信号广播设备发送的广播帧的信号强度、以及寻车装置中的无线信号接收模块所接收到的广播帧的信号强度，计算出寻车装置与被寻找车辆之间的距离。
  3. 根据权利要求2所述的方法，其特征在于，在计算寻车装置与被寻找车辆的距离过程中，采用自适应滤波器的方式来迭代修正接收到的广播帧的信号强度指示值RSSI，具体为：
    在寻车装置移动时，基于寻车装置中陀螺仪的x、y、z轴三个方向的加速度，采用自适应滤波器对指示值RSSI进行修正，得到更新后的指示值RSSI new。
  4. 根据权利要求3所述的方法，其特征在于，所述采用自适应滤波器对指示值RSSI进行修正，具体包括：
    步骤21，根据寻车装置中陀螺仪x轴方向的加速度值进行滤波，公式如下：
    Figure PCTCN2017117276-appb-100001
    Figure PCTCN2017117276-appb-100002
    其中，e(n)表示经过x轴修正后的RSSI值；x x(n)表示第n个时刻陀螺仪采集的x轴的加速度值；w 1(n)表示长度为L+1的有限长数字滤波器向量；y(n)表示从n-L个时刻到第n个时刻采集的RSSI值的向量，长度为L+1；b和μ为常数，根据实际性能需求调整；
    步骤22，将e(n)作为输入，根据陀螺仪y轴方向的加速度值进行滤波， 公式如下：
    Figure PCTCN2017117276-appb-100003
    Figure PCTCN2017117276-appb-100004
    其中，f(n)表示经过y轴修正后的RSSI值；x y(n)表示第n个时刻陀螺仪采集的y轴的加速度值；w 2(n)表示长度为L+1的有限长数字滤波器向量；
    步骤23，将f(n)作为输入，根据陀螺仪z轴方向的加速度值进行滤波，公式如下：
    Figure PCTCN2017117276-appb-100005
    Figure PCTCN2017117276-appb-100006
    其中，g(n)表示经过z轴修正后的RSSI值；x z(n)表示第n个时刻陀螺仪采集的z轴的加速度值；w 3(n)表示长度为L+1的有限长数字滤波器向量；
    步骤24，将g(n)进行三点平滑滤波得到处理后的RSSI值，公式如下：
    RSSI new(n)＝αg(n-1)+βg(n)+γg(n+1)，
    其中α、β、γ为预设的权重系数；
  5. 根据权利要求4所述的方法，其特征在于，计算所述被寻找车辆与寻车装置之间的距离，具体方法为：
    Figure PCTCN2017117276-appb-100007
    其中，d为计算出的被寻找车辆与寻车装置之间的距离，δ为无线环境的衰落因子，r 1为1米处接收到的信号强度，单位dBm，d 0为预设的测距修正值。
  6. 根据权利要求5所述的方法，其特征在于，被寻找车辆与寻车装置之间距离d的计算公式中，RSSI new值为迭代执行两次步骤21至步骤24所得到的修正后的信号强度指示值。
  7. 根据权利要求2或5所述的方法，其特征在于，所述无线信号为蓝 牙信号或WiFi信号；所述被寻找车辆内的无线信号广播设备发送的广播帧的信号强度，是在距离广播设备1米处接收到的信号强度r 1。
  8. 根据权利要求1～6中任一项所述的方法，其特征在于，所述无线信号广播设备按照预设的间隔发送广播帧。
  9. 根据权利要求1～6中任一项所述的方法，其特征在于，广播帧中包含被寻车辆的车牌号、车主信息；所述寻车装置可以解析广播帧中所包含的信息用于寻找相应车辆。
  10. 根据权利要求1～6中任一项所述的方法，其特征在于，α取值范围为[0.05,0.2]、β取值范围为[0.4,0.6]、γ取值范围为[0.1,0.3]。
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