An air-ground cooperative positioning method suitable for low-altitude vehicle networking technology

Abstract

The application provides a kind of air-ground cooperative positioning method suitable for low-altitude vehicle network connection technology, comprehensively utilizes the advantages of vehicle networking and low-altitude intelligent networking technology, in the complex traffic environment such as city viaduct, city canyon, positioning signal is shielded, target vehicle carries out information interaction with surrounding vehicles and low-altitude aircraft through wireless transmission, based on the fusion of GPS / Beidou positioning, intelligent network connection wireless ranging information, the position information of vehicle is estimated in real time through intelligent algorithm, the three-dimensional position information is positioned to enhance, provides continuous positioning information and improves positioning accuracy, realizes the function of continuous accurate positioning when vehicle positioning signal is shielded.The application simultaneously adopts low-cost positioning and ranging module, compared with the existing multi-sensor fusion positioning technology such as vehicle-mounted laser radar, the cost is lower, has better application prospect, can provide technical support for accurate continuous positioning of vehicle in future intelligent network connection three-dimensional traffic environment.

Description

Technical Field

[0001] This invention belongs to the fields of intelligent connected transportation and low-altitude intelligent network technology, specifically relating to an air-ground cooperative positioning method applicable to low-altitude vehicle network technology. Background Technology

[0002] With the continuous development of technologies such as GPS / BeiDou satellite navigation and positioning, vehicle-to-everything (V2X) networks, and low-altitude intelligent networks, the demand for accurate and continuous vehicle positioning in future three-dimensional transportation environments is becoming increasingly urgent. In an intelligent connected environment, vehicles and low-altitude aircraft can more easily perceive and acquire their respective position and relative distance information, providing technical support for air-ground cooperative positioning.

[0003] Currently, vehicle positioning mainly employs methods such as GPS / BeiDou satellite positioning or satellite / inertial navigation combined positioning. However, in actual driving environments, vehicle-mounted satellite positioning is susceptible to interference from complex environments, resulting in errors from multiple sources and requiring improvement in positioning accuracy. While satellite / inertial navigation combined positioning can improve accuracy to some extent, inertial navigation suffers from cumulative error drift, making it difficult to continuously and effectively correct positioning errors. In complex urban traffic environments, when vehicle positioning signals are obstructed by elevated bridges, urban canyons, or other environmental factors, existing satellite and combined positioning methods still struggle to guarantee accurate and continuous vehicle positioning. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide an air-ground cooperative positioning method applicable to low-altitude vehicle network technology, which is used for continuous and accurate positioning when the vehicle positioning signal is blocked.

[0005] The technical solution adopted by this invention to solve the above-mentioned technical problems is as follows: an air-ground cooperative positioning method applicable to low-altitude vehicle network technology, comprising the following steps:

[0006] S1: Real-time location information of intelligent connected vehicles and cooperative positioning unmanned aerial vehicles;

[0007] S2: Measure and calculate the angle and straight-line distance of the intelligent connected vehicle to the cooperatively positioned unmanned aerial vehicle;

[0008] S3: The continuous positioning error is optimized by using a signal estimation algorithm, and the cooperative positioning error is made to meet or approximate the application requirements by using the Gauss-Newton iterative method.

[0009] According to the above scheme, step S1 specifically involves: obtaining location information via sensors including GPS or BeiDou positioning modules; and obtaining the coordinates of the intelligent connected vehicle. The coordinates of the cooperative positioning unmanned aerial vehicle are

[0010] According to the above scheme, in step S2, the yaw angle α of the intelligent connected vehicle relative to the cooperative positioning unmanned aerial vehicle i is measured by ultra-wideband (UWB) signal. i The pitch angle is β i The straight-line distance is D t .

[0011] According to the above scheme, in step S2, the coordinate position of the intelligent connected vehicle is calculated based on the geometric relationship and cooperative position of the unmanned aerial vehicle and the intelligent connected vehicle. for:

[0012]

[0013] According to the above scheme, in step S3,

[0014] The cooperative localization observation vector is represented as:

[0015] O=[α i ,β i D ij ] T ;

[0016] The estimated value of the measurement considering error is:

[0017]

[0018] Will Represented as the location V of the intelligent connected vehicle t function

[0019]

[0020] set up The transition matrix is ​​H, and the measurement error is... Represented as:

[0021] δ=H·dV t .

[0022] Furthermore, in step S3, the transition matrix H is represented as a Jacobian matrix.

[0023] Furthermore, in step S3, let n be the iteration number, ΔV t (t) is the vehicle position at time t. Increment; Iterative calculation error Set an iteration threshold T. If δ < T, stop the iteration. Allow the error to approach the minimum value. Calculate the optimized vehicle position at time t as follows:

[0024]

[0025] (ΔV t (t+1)) n =(V t (t)) n +(ΔV t (t)) n .

[0026] An air-ground cooperative positioning system for low-altitude vehicle connectivity technology is disclosed. The system includes a processor and a memory. The memory stores computer instructions, and the processor executes the computer instructions stored in the memory. When the computer instructions are executed by the processor, the system implements the steps of an air-ground cooperative positioning method for low-altitude vehicle connectivity technology.

[0027] Furthermore, this includes intelligent connected vehicles, collaborative positioning unmanned aerial vehicles, and satellite positioning systems.

[0028] A computer storage medium storing a computer program executable by a computer processor, the computer program executing an air-ground cooperative positioning method applicable to low-altitude vehicle network technology.

[0029] The beneficial effects of this invention are as follows:

[0030] 1. The present invention provides an air-ground cooperative positioning method applicable to low-altitude vehicle network technology, which comprehensively utilizes the advantages of vehicle network and low-altitude intelligent network technologies. In complex traffic environments such as urban overpasses and urban canyons where positioning signals are blocked, the method performs cooperative positioning calculations on the target vehicle by integrating the position and distance information of the low-altitude aircraft through information interaction between the low-altitude aircraft and the vehicle, enhances the three-dimensional position information, provides continuous positioning information and improves positioning accuracy, and realizes the function of continuous and accurate positioning when vehicle positioning signals are blocked.

[0031] 2. In an intelligent connected environment, the present invention provides a collaborative positioning method and system in which the target vehicle interacts with surrounding vehicles and low-altitude aircraft (drones, flying cars, etc.) via wireless transmission. Based on the fusion of information such as GPS / BeiDou positioning and intelligent connected wireless ranging, the system uses intelligent algorithms to estimate the vehicle's position information in real time, thereby improving the positioning accuracy when vehicle positioning signals are obscured in complex urban traffic environments.

[0032] 3. This invention employs low-cost positioning and ranging modules, which are lower in cost and have better application prospects compared with existing multi-sensor fusion positioning technologies such as vehicle-mounted LiDAR. It can provide technical support for accurate and continuous vehicle positioning in future intelligent connected three-dimensional transportation environments. Attached Figure Description

[0033] Figure 1This is a schematic diagram of an embodiment of the present invention.

[0034] Figure 2 This is a flowchart of an embodiment of the present invention. Detailed Implementation

[0035] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0036] See Figure 1 and Figure 2 The embodiments of the present invention include the following steps:

[0037] S1: Real-time location information of intelligent connected vehicles and collaborative positioning unmanned aerial vehicles is obtained through GPS / BeiDou positioning modules, such as... Figure 1 As shown, the coordinates of the intelligent connected vehicle are represented as follows:

[0038]

[0039] The position of a cooperatively localized unmanned aerial vehicle is represented as follows:

[0040]

[0041] S2: Obtain the yaw angle α of the intelligent connected vehicle relative to the cooperatively positioned unmanned aerial vehicle i based on UWB signal measurement and calculation. i Pitch angle β i and straight-line distance D t ;

[0042] When the vehicle's positioning signal is blocked, the location information of the unblocked UAV at low altitude is used to perform cooperative position calculation of the intelligent connected vehicle based on the geometric relationship between the UAV and the target vehicle.

[0043]

[0044] S3: The continuous positioning error is optimized by using a signal estimation algorithm, and the cooperative positioning error is made to meet or approximate the application requirements by using the Gauss-Newton iterative method.

[0045] The cooperative localization observation vector can be represented as:

[0046] 0 = [α] i ,β i D ij ] T ;

[0047] The estimated value of the measurement considering error is:

[0048]

[0049] Will Represented as the location V of the connected vehicle t function

[0050]

[0051] Measurement error It can be represented as:

[0052] δ=H·dV t ;

[0053] in, The transition matrix H can be represented as a Jacobian matrix.

[0054] Iterative calculation error Set an iteration threshold T (based on positioning accuracy requirements and empirical values). If δ < T, stop the iteration to minimize the error. The optimized vehicle position at time t can then be calculated.

[0055]

[0056] (ΔV t (t+1)) n =(V t (t)) n +(ΔV t (t)) n ;

[0057] Where n is the number of iterations, ΔV t (t) is the vehicle position at time t. The increment.

[0058] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0059] The above embodiments are only used to illustrate the design concept and features of the present invention, and their purpose is to enable those skilled in the art to understand the content of the present invention and implement it accordingly. The protection scope of the present invention is not limited to the above embodiments. Therefore, all equivalent changes or modifications made based on the principles and design ideas disclosed in the present invention are within the protection scope of the present invention.

Claims

1. A method for air-ground cooperative positioning applicable to low-altitude vehicle network technology, characterized in that: The method comprises the following steps: S1: Real-time acquisition of real-time position information of intelligent networked vehicles and cooperatively positioned unmanned aerial vehicles; The sensor for acquiring the position information includes a GPS or Beidou positioning module; the coordinate position of the intelligent connected vehicle is , and the coordinate position of the cooperative positioning unmanned aerial vehicle is . S2: Measurement and calculation of the angle and straight-line distance of the intelligent networked vehicle to the cooperatively positioned unmanned aerial vehicle; The yaw angle of the intelligent networked vehicle to the cooperative positioning unmanned aerial vehicle i is measured by the ultra-wideband signal UWB as , the pitch angle is , and the straight-line distance is ; Coordinating a coordinate position of a smart connected vehicle based on geometric relationships between the smart connected vehicle and an unmanned aerial vehicle To: ； S3: Signal estimation algorithm is used to optimize the continuous positioning error, and the cooperatively positioned error is made to meet or approach the application requirements through the Gauss-Newton iterative method; The cooperatively positioned observation vector is expressed as: ； The measurement value considering the error is estimated as: ； Will Represented as the location of intelligent connected vehicles function : ； Let , the transfer matrix is H, the measurement error is represented as: ； The transfer matrix H is expressed as a Jacobian matrix : ； Let n be the iteration number, be the iteration error, t be the vehicle position at time t, be the increment of the vehicle position; the iteration error is calculated Set the iteration threshold T, if stop the iteration, make the error approach the minimum value, and calculate t the optimized vehicle position at time t as ， ， 。 2. An air-ground cooperative positioning system suitable for low-altitude vehicle networking technology, the system comprising a processor and a memory, characterized in that: The memory stores computer instructions, and the processor is used to execute the computer instructions stored in the memory, and when the computer instructions are executed by the processor, the system implements the steps of the air-ground cooperative positioning method suitable for low-altitude vehicle networking technology according to claim 1.

3. The air-ground cooperative positioning system suitable for low-altitude vehicle networking technology according to claim 2, characterized in that: The system comprises intelligent networked vehicles, cooperatively positioned unmanned aerial vehicles and satellite positioning systems.

4. A computer storage medium, characterized by: The memory stores computer programs executable by the computer processor, and the computer programs execute the air-ground cooperative positioning method suitable for low-altitude vehicle networking technology according to claim 1.

Images