A target observation-based angle sensor bias estimation method

Abstract

The application discloses a kind of angle sensor deviation estimation methods based on target observation, comprising the following steps: S1, unmanned aerial vehicle is to own attitude and is measured to target position by sensor carried by unmanned aerial vehicle, obtains measurement;S2, the target position is measured, and accurate position of target is obtained;S3, compares measurement and accurate position of target, and obtains angle sensor deviation.The angle sensor deviation estimation method based on target observation disclosed in the application is high in deviation estimation accuracy, easy to operate and low in cost.

Description

Technical Field

[0001] This invention relates to an angle sensor bias estimation method based on target observation, belonging to the field of sensor bias estimation. Background Technology

[0002] Target localization by drones is a common reconnaissance method, and the accuracy of the localization results directly determines the quality of the reconnaissance mission.

[0003] With significant advancements in low-cost, lightweight drone manufacturing technology, it has become possible to use low-cost drones for reconnaissance.

[0004] Angle differences between drone angle sensors due to insufficient manufacturing and installation precision can reduce the drone's positioning accuracy, such as the difference between the drone's electro-optical pod and its own inertial navigation system.

[0005] Finding the right method to estimate and compensate for angular deviations between sensors has become crucial for improving the positioning accuracy of drones.

[0006] For this type of angular deviation, direct measurement is difficult and requires high-precision measuring instruments, which is time-consuming and labor-intensive.

[0007] The aerial optical axis reference measurement and correction method requires the UAV to locate the target in a specific attitude and position, which is not easy to operate and may introduce errors caused by human operation.

[0008] For the reasons mentioned above, it is necessary to propose an angle sensor deviation estimation method to solve the above problems. Summary of the Invention

[0009] To overcome the above problems, the inventors conducted intensive research and designed an angle sensor bias estimation method based on target observation, comprising the following steps:

[0010] S1. The UAV measures its own attitude and the target position using sensors on board the UAV to obtain measurement data.

[0011] S2. Measure the target position to obtain the precise target position;

[0012] S3. By comparing the measurement of the target's precise position, the angle sensor deviation is obtained.

[0013] In a preferred embodiment, in S1, the obtained quantity z is:

[0014]

[0015] Where, x u y u z uThe three-dimensional coordinates of the UAV obtained by measurement are α and β, which are the line-of-sight angles of the electro-optical pod, φ, θ, and ψ are the roll, pitch, and yaw attitude angles of the aircraft, and L is the laser ranging value.

[0016] In a preferred embodiment, the relationship between the target coordinates and the UAV coordinates in S3 is expressed as follows:

[0017] X T =f(zv,x)=f(y,x)

[0018] Where f is a nonlinear function representing the relationship between the measured value, the installation angle, and the target position, x represents the sensor angle deviation in the three directions of roll, pitch, and yaw, z represents the measured value, and v represents the measurement noise.

[0019] In a preferred embodiment, the relationship between the target coordinates and the UAV coordinates is transformed into a linear estimate, which is then solved using the weighted least squares method to obtain the angle sensor deviation estimate.

[0020] In a preferred embodiment, the relationship between the target coordinates and the UAV coordinates is performed using a Taylor expansion:

[0021]

[0022] The transformation yields:

[0023]

[0024] Integrate into matrix form:

[0025]

[0026] Among them, X T The measured values ​​representing the target location, z1~z N Let V represent the measurement values ​​from the 1st to the Nth time, and let V represent the measurement covariance matrix.

[0027] In a preferred embodiment, the weighted least squares method is used to solve the matrix relationship between the target coordinates and the UAV coordinates, where x is the unknown quantity. Represented as:

[0028]

[0029] in, The Jacobian matrix obtained by taking the partial derivative of f with respect to the quantity is given.

[0030] The Jacobian matrix is ​​obtained by taking the partial derivative of f with respect to the installation angle.

[0031] The beneficial effects of this invention include:

[0032] (1) The angle sensor deviation estimation method based on target observation provided by the present invention has high deviation estimation accuracy;

[0033] (2) The angle sensor deviation estimation method based on target observation provided by the present invention has higher estimation accuracy and is easier to operate compared with the airborne optical axis reference measurement and correction method.

[0034] (3) The angle sensor deviation estimation method based on target observation provided by the present invention is low in cost and requires no additional investment. Attached Figure Description

[0035] Figure 1 This diagram illustrates a flow chart of an angle sensor bias estimation method based on target observation according to a preferred embodiment of the present invention.

[0036] Figure 2 This shows a top view of the UAV measurement position in Example 1;

[0037] Figure 3 This shows a three-dimensional view of the UAV measurement position in Example 1;

[0038] Figure 4 The results of yaw direction sensor bias estimation in Example 1 are shown;

[0039] Figure 5 The results of pitch direction sensor deviation estimation in Example 1 are shown;

[0040] Figure 6 The results of the roll direction sensor deviation estimation in Example 1 are shown;

[0041] Figure 7 The result of compensating for the drone positioning in Example 1 is shown. Detailed Implementation

[0042] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Through these descriptions, the features and advantages of the present invention will become clearer and more apparent.

[0043] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments. Although various aspects of embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless specifically indicated otherwise.

[0044] According to the present invention, an angle sensor bias estimation method based on target observation is provided, such as... Figure 1 As shown, it includes the following steps:

[0045] S1. The UAV measures its own attitude and the target position using sensors on board the UAV to obtain measurement data.

[0046] S2. Measure the target position to obtain the precise target position;

[0047] S3. By comparing the measurement of the target's precise position, the angle sensor deviation is obtained.

[0048] Furthermore, in S1, an electro-optical ball capable of identifying and locking onto targets and outputting the target's angle information relative to the drone is installed on the drone; a GPS system and an inertial navigation system capable of outputting the drone's own position coordinates and attitude angles are also installed; and a laser rangefinder capable of outputting the distance information between the target and the drone is installed to obtain a measurement, the obtained measurement z being:

[0049]

[0050] Where, x u y u z u The three-dimensional coordinates of the UAV obtained by measurement are α and β, which are the line-of-sight angles of the electro-optical pod, φ, θ, and ψ are the roll, pitch, and yaw attitude angles of the aircraft, and L is the laser ranging value.

[0051] In S2, preferably, a handheld GPS is used to measure the target location, and the average value of multiple measurements is taken as the true coordinates of the target.

[0052] In S3, the relationship between the target coordinates and the UAV coordinates is expressed as follows:

[0053] X T =f(zv,x)=f(y,x)

[0054] Where f is a nonlinear function representing the relationship between the measured value, the installation angle, and the target position, x represents the sensor angle deviation in the three directions of roll, pitch, and yaw, y represents the measured value after noise removal, and v represents the measurement noise.

[0055] In a preferred embodiment, the relationship between the target coordinates and the UAV coordinates is transformed into a linear estimate, which is then solved using the weighted least squares method to obtain the angle sensor deviation estimate.

[0056] In a preferred embodiment, the relationship between the target coordinates and the UAV coordinates is performed using a Taylor expansion:

[0057]

[0058] The transformation yields:

[0059]

[0060] Integrate into matrix form:

[0061]

[0062] Among them, X T The measured values ​​representing the target location, z1~z N Let V represent the measurement values ​​from the 1st to the Nth time, and let V represent the measurement covariance matrix.

[0063] In a preferred embodiment, the weighted least squares method is used to solve the matrix relationship between the target coordinates and the UAV coordinates, where x is the unknown quantity. Represented as:

[0064]

[0065] in, The Jacobian matrix obtained by taking the partial derivative of f with respect to the quantity is given.

[0066] The Jacobian matrix is ​​obtained by taking the partial derivative of f with respect to the installation angle.

[0067] Example

[0068] Example 1

[0069] The simulation experiment, based on the angle sensor bias estimation method for target observation, includes the following steps:

[0070] S1. The UAV measures its own attitude and the target position using sensors on board the UAV to obtain measurement data.

[0071] S2. Measure the target position to obtain the precise target position;

[0072] S3. By comparing the measurement of the target's precise position, the angle sensor deviation is obtained.

[0073] The location of the drone and the target location are as follows Figure 2 , 3 As shown, a top view of the UAV's measurement position is displayed. Figure 3 A 3D view of the UAV measurement location is shown.

[0074] In S3, the relationship between the target coordinates and the UAV coordinates is expressed as follows:

[0075] X T =f(zv,x)=f(y,x)

[0076] The relationship between the target coordinates and the UAV coordinates is expanded using Taylor series:

[0077]

[0078] The transformation yields:

[0079]

[0080] Integrate into matrix form:

[0081]

[0082] The weighted least squares method is used to solve the matrix relationship between the target coordinates and the UAV coordinates, where the unknown quantity is... Represented as:

[0083]

[0084] After solving, the obtained yaw direction sensor bias estimation result is as follows: Figure 4 As shown, the pitch direction sensor bias estimation results are as follows: Figure 5 As shown, the roll direction sensor bias estimation results are as follows: Figure 6 As shown.

[0085] Based on the deviation estimation results, the result after compensating for the UAV positioning is as follows: Figure 7 As shown, the positioning error is significantly reduced.

[0086] In the description of this invention, it should be noted that the terms "upper," "lower," "inner," "outer," "front," and "rear," etc., indicate the orientation or positional relationship based on the orientation or positional relationship in the working state of this invention, and are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention. Furthermore, the terms "first," "second," "third," and "fourth" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0087] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0088] The present invention has been described above with reference to preferred embodiments; however, these embodiments are merely exemplary and illustrative. Various substitutions and modifications can be made to the present invention based on these embodiments, all of which fall within the scope of protection of the present invention.

Claims

1. A method for estimating angle sensor bias based on target observation, characterized in that, Includes the following steps: S1. The UAV measures its own attitude and the target position using sensors on board the UAV to obtain measurement data. S2. Measure the target position to obtain the precise target position; S3. By comparing the measured value and the precise position of the target, the angle sensor deviation is obtained. In S3, the relationship between the target coordinates and the UAV coordinates is expressed as follows: in It is a nonlinear function, representing the relationship between the measured value, the installation angle, and the target position. This indicates the sensor angle deviation in the three directions of roll, pitch, and yaw. This indicates the measurement after noise removal. Indicates measurement noise. Indicative measurement; The relationship between the target coordinates and the UAV coordinates is transformed into a linear estimate, which is then solved using the weighted least squares method to obtain the angle sensor bias estimate. The relationship between the target coordinates and the UAV coordinates is expanded using Taylor series: The transformation yields: Integrate into matrix form: in, The measured value representing the target location. This represents the measurement values ​​from the 1st to the Nth time. This represents the measurement covariance matrix.

2. The angle sensor bias estimation method based on target observation according to claim 1, characterized in that, In S1, the obtained quantity measurement for: in, , , The three-dimensional coordinates of the UAV obtained from the measurement, 、 For the line-of-sight angle of the optoelectronic pod, , , For the roll, pitch, and yaw attitude angles of the aircraft, This is the laser ranging value.

3. The angle sensor bias estimation method based on target observation according to claim 1, characterized in that, The matrix relationship between the target coordinates and the UAV coordinates is solved using the weighted least squares method, where The quantity to be estimated Represented as: in, for The Jacobian matrix obtained by taking the partial derivative with respect to the quantity. for The Jacobian matrix is ​​obtained by taking the partial derivative with respect to the installation angle.

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