A method for calibrating shafting parameters of a shipborne tracking and control antenna of a UAV

Abstract

This application relates to a method for calibrating the axis system parameters of a shipborne telemetry and control antenna for tracking unmanned aerial vehicles (UAVs). The method establishes a double-difference observation model, synchronously records raw observations using airborne and shipborne GNSS equipment, and combines inertial navigation attitude data and deformation measurement data to calculate high-precision relative positioning results and comparison reference data. A direct electrical axis parameter calibration model is also established. Based on the relative positioning results, comparison reference data, and the direct electrical axis parameter calibration model, the calibration results of the shipborne telemetry and control antenna axis system parameters for UAV tracking are obtained. This method, by using a telemetry and control frequency beacon mounted on the UAV, can achieve direct calibration of the axis system parameters at the telemetry and control frequency, improving calibration efficiency while reducing calibration costs.

Description

Technical Field

[0001] This application relates to the field of aerospace telemetry and control technology, and in particular to a method for calibrating the axis parameters of a shipborne telemetry and control antenna for tracking unmanned aerial vehicles. Background Technology

[0002] Due to factors such as installation errors, structural deformation, and signal frequency variations, the angle directly obtained by the axial angle encoder will deviate from the actual antenna pointing direction. To achieve high-precision target tracking and measurement at sea, this deviation needs to be corrected. At sea, in the early days, because the electrical axis parameters of the antenna were difficult to calibrate directly, the optical axis of the low-light television fixed to the antenna was typically used as a reference (axis system parameters include six parameters: azimuth zero value, elevation zero value, optomechanical deviation, azimuth and elevation non-orthogonality, disk non-horizontal value, and disk non-horizontal angle). This was then combined with photoelectric deviation to correct the electrical axis pointing deviation. The optical axis system parameters were calibrated in the dock and used as fixed parameters, while the photoelectric deviation was calibrated before each measurement and control operation using a beacon sphere at the sea tracking and control frequency point. Due to factors such as temperature, humidity, and ship rolling, the optical axis parameters can actually change to some extent. Currently, there are two main methods for calibration. One method uses the optical axis as an intermediate quantity, calibrating the photoelectric deviation by tracking a beacon sphere, and then calibrating the optical axis system parameters of low-light television by synchronously measuring stars, using a theodolite as a reference. The other method uses tracking and calibration targets with precise orbits to directly calibrate the optical axis system parameters. However, to adapt to the central computer parameter binding mode, this method uses the photoelectric deviation as a known transition quantity to calculate the optical axis parameters; therefore, this method is also called the equivalent axis system parameter calibration method. The first method is easily affected by weather factors and cannot be calibrated in cloudy weather. The second method requires multiple tracking cycles over several days to cover different azimuth and elevation angles to obtain effective calibration results, and the frequency of the calibration target cannot be switched. Therefore, this method cannot directly calibrate the axis system parameters for the telemetry and control frequency. Summary of the Invention

[0003] Therefore, it is necessary to provide a method for calibrating the axis parameters of a shipborne telemetry and control antenna for tracking unmanned aerial vehicles (UAVs) to address the aforementioned technical problems.

[0004] A method for calibrating the axis parameters of a shipborne telemetry and control antenna for tracking unmanned aerial vehicles, the method comprising:

[0005] Based on the data recorded by the central computer, the effective tracking measurement data of USB is extracted to obtain each self-tracking moment and the corresponding azimuth and elevation observation values.

[0006] Based on a set of raw measurement data simultaneously observed by airborne and shipborne GNSS equipment, the linearized double-difference observation equation is solved using the mixed integer least squares method to obtain the relative positioning result of the phase center of the airborne GNSS antenna relative to the phase center of the shipborne GNSS antenna.

[0007] Based on the relative positioning results of the phase center of the airborne GNSS antenna relative to the phase center of the shipborne GNSS antenna, the coordinates of the beacon antenna relative to the phase center of the airborne GNSS antenna in the body coordinate system, the attitude of the UAV, the coordinates of the phase center of the shipborne GNSS antenna relative to the three-axis center of the USB in the inertial navigation deck system, and the attitude and deformation data of the measuring ship, the coordinates of the UAV beacon antenna relative to the three-axis center of the USB antenna in the inertial navigation horizontal coordinate system are obtained.

[0008] Based on the ship's rocking and deformation data, the coordinates of the UAV beacon antenna relative to the three-axis center inertial navigation horizon system of the USB antenna are transformed. Based on the obtained coordinate transformation results and atmospheric refraction correction values, the pitch angle and azimuth angle after axis system error correction are obtained.

[0009] Based on the pitch and azimuth angles after the shaft system error correction, the azimuth observation value, and the pitch observation value, a set of shaft system parameter calculation equations is established and solved using the least squares method to obtain the calibration results of the shipborne telemetry and control antenna shaft system parameters.

[0010] The aforementioned method for calibrating the axis system parameters of the shipborne telemetry and control antenna for tracking UAVs involves establishing a double-difference observation model, synchronously recording raw observations using airborne and shipborne GNSS equipment, and combining inertial navigation attitude data and deformation measurement data to calculate high-precision relative positioning results and comparison benchmark data. A direct electrical axis parameter calibration model is also established. Based on the relative positioning results, comparison benchmark data, and the direct electrical axis parameter calibration model, the calibration results of the shipborne telemetry and control antenna axis system parameters for UAV tracking are obtained. This method, by using a telemetry and control frequency beacon mounted on the UAV, can achieve direct calibration of the axis system parameters at the telemetry and control frequency, improving calibration efficiency while reducing calibration costs. Attached Figure Description

[0011] Figure 1 This is a flowchart illustrating a method for calibrating the axis parameters of a shipborne telemetry and control antenna for tracking a UAV in one embodiment.

[0012] Figure 2 This is a data preprocessing procedure in another embodiment;

[0013] Figure 3 This is a flowchart for calculating the three-axis center position of the drone beacon antenna relative to the USB antenna in another embodiment. Detailed Implementation

[0014] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0015] With the development of UAV technology, the cost of UAVs is continuously decreasing, their operability and functionality are constantly being upgraded, and their applications are continuously expanding. Through preliminary research, the takeoff and safe recovery of fixed-wing UAVs on measurement vessels have been successfully achieved. A digital guidance system, a remote frequency modification system, and dynamic route planning technology for tracking UAVs have been completed, and these technologies have been successfully applied to phase checks and photoelectric deviation calibration during the telemetry and control process, improving calibration efficiency while reducing calibration costs. Similarly, by equipping UAVs with telemetry and control frequency beacons, the shaft system parameters of direct telemetry and control frequencies can be calibrated.

[0016] In one embodiment, such as Figure 1 As shown, a method for calibrating the axis parameters of a shipborne telemetry and control antenna for tracking unmanned aerial vehicles is provided. The method includes the following steps:

[0017] Step 100: Extract effective USB tracking measurement data based on the data recorded by the central unit, and obtain the azimuth and elevation observation values ​​for each self-tracking moment.

[0018] Step 102: Based on a set of raw measurement data simultaneously observed by airborne and shipborne GNSS equipment, the linearized double-difference observation equation is solved using the mixed integer least squares method to obtain the relative positioning result of the phase center of the airborne GNSS antenna relative to the phase center of the shipborne GNSS antenna.

[0019] Specifically, by equipping UAVs with telemetry and control frequency beacons, it is possible to directly calibrate the axis parameters of the telemetry and control frequencies. Airborne GNSS equipment refers to GNSS equipment mounted on the UAV.

[0020] The original measurement information was observed and recorded simultaneously using airborne GNSS equipment and shipborne GNSS equipment, with the shipborne GNSS equipment serving as a mobile reference station.

[0021] Based on a set of original measurement data, the linearized double-difference observation equations were solved using the mixed integer least squares method to obtain the relative positioning results of the airborne GNSS phase center relative to the shipborne GNSS antenna phase center.

[0022] Step 104: Based on the relative positioning results of the phase center of the airborne GNSS antenna relative to the phase center of the shipborne GNSS antenna, the coordinates of the beacon antenna relative to the phase center of the airborne GNSS antenna in the body coordinate system, the attitude of the UAV, the coordinates of the phase center of the shipborne GNSS antenna relative to the three-axis center of the USB in the inertial navigation deck system, and the attitude and deformation data of the measuring ship, obtain the coordinates of the UAV beacon antenna relative to the three-axis center of the USB antenna in the inertial navigation horizontal coordinate system.

[0023] Step 106: Based on the ship's rocking and deformation data, perform coordinate transformation on the UAV beacon antenna relative to the three-axis center inertial navigation horizon coordinates of the USB antenna, and obtain the pitch angle and azimuth angle after axis error correction based on the obtained coordinate transformation results and atmospheric refraction correction values.

[0024] Step 108: Based on the pitch and azimuth angles after shaft system error correction, the azimuth observation value, and the pitch observation value, establish a set of shaft system parameter calculation equations, and solve them using the least squares method to obtain the calibration results of the shipborne telemetry and control antenna shaft system parameters.

[0025] The above-described method for calibrating the axis system parameters of the shipborne telemetry and control antenna for tracking UAVs involves establishing a double-difference observation model, synchronously recording raw observations using airborne and shipborne GNSS equipment, and combining inertial navigation attitude data and deformation measurement data to calculate high-precision relative positioning results and comparison benchmark data. A direct electrical axis parameter calibration model is also established. Based on the relative positioning results, comparison benchmark data, and the direct electrical axis parameter calibration model, the calibration results of the shipborne telemetry and control antenna axis system parameters for UAV tracking are obtained. This method, by using a telemetry and control frequency beacon mounted on the UAV, can achieve direct calibration of the axis system parameters at the telemetry and control frequency, improving calibration efficiency while reducing calibration costs.

[0026] In one embodiment, step 100 includes: extracting raw USB tracking strategy data from the central computer's disk data; and, based on the status codes of the extracted data, selecting only the data whose status codes represent the corresponding time periods of self-tracking to obtain the i-th self-tracking time T. i And the corresponding azimuth and elevation observations, where i = 1, 2, ..., N, and N is the number of valid data.

[0027] In one embodiment, step 102 includes: constructing a double-difference observation equation and linearizing the double-difference observation equation to obtain the linearized double-difference observation equation as follows:

[0028]

[0029] Where v is the residual, X and N are the parameters to be estimated, representing the non-ambiguity parameter and the ambiguity parameter, respectively; the superscripts n and m represent the dimensions of the non-ambiguity parameter and the ambiguity parameter, respectively; A and B are the corresponding submatrices of the non-ambiguity parameter X and the ambiguity parameter N in the double-difference observation equation design matrix, respectively; l = LF(X 0 N 0 ); L represents double-difference observations.

[0030] Based on a set of raw measurement data simultaneously observed by airborne and shipborne GNSS equipment, the linearized double-difference observation equation is solved using the mixed integer least squares method to obtain the coordinates of the phase center of the airborne GNSS antenna relative to the phase center of the shipborne GNSS antenna in the inertial navigation horizon system.

[0031] Specifically, traditional GPS positioning results are obtained directly from pseudorange, offering fast positioning speed, good real-time performance, and ease of use. However, it is easily affected by propagation errors and clock biases, resulting in relatively low positioning accuracy, on the order of meters. When using satellite tracking for axis system parameter calibration, the calibration distance is several hundred to several thousand kilometers. The meter-level positioning error, after being converted into an angle error, is on the order of arcseconds, which is sufficient for axis system parameter calibration. Due to the limitations of UAV performance, the relative distance is shorter (several kilometers). The meter-level positioning accuracy, after being converted into angles, results in an error of tens of arcseconds, making it difficult to meet the accuracy requirements for axis system parameter calibration. Therefore, higher positioning accuracy is needed to meet the accuracy requirements for axis system parameter calibration. Traditional carrier phase differential GPS uses a more accurate carrier phase as the observation value and eliminates some of the error influence through differential methods, significantly improving positioning accuracy. However, it requires a fixed base station with a known precise location, which is unavailable at sea. Since the axis system parameter calibration reference is a relative quantity, namely the angle (position) of the target relative to the three-axis center of the antenna, the calculation does not require obtaining the precise single-point position of the UAV (surveying vessel), but only the precise relative position. Therefore, to achieve axis system parameter calibration for tracking UAVs, it is necessary to solve the problem of high-precision relative position calculation under dynamic conditions.

[0032] During the acquisition and measurement of satellite signals, GNSS receivers generally generate two basic raw observations: pseudorange observations and carrier phase observations, which are shown below:

[0033]

[0034]

[0035] In the above formula, P and L represent pseudorange observation and carrier phase observation (unit: m), respectively; the superscript s represents the observation satellite; r represents the receiver; and i represents the frequency of the observation signal. dt represents the geometric distance between the satellite and the receiver (unit: m); r (t r ) and dT s (t s These represent receiver clock bias and satellite clock bias (unit: m), respectively. Expressed as ionospheric delay (unit: m), α is a constant, TEC is the total electron density along the signal propagation path, and f i The frequency of the observed signal; Expressed as tropospheric delay (unit: m); and The multipath effect errors of pseudorange and carrier phase observations are represented respectively (unit: m); The ambiguity parameter represents the carrier phase observation (unit: cycle); c represents the speed of light in a vacuum (unit: m / s); ε p and ε L The observation noise (unit: m) represents the pseudorange observation and the carrier phase observation, respectively.

[0036] By subtracting the single-difference observations between two satellites at the same observation epoch or the single-difference observations between two stations, we obtain double-difference observations based on two satellites and two stations.

[0037] Assuming that satellites j and k are observed synchronously at points A and B, the following conventions are introduced:

[0038]

[0039] In the above equation, * can be replaced by L or P. In the double difference equation, these symbols can be specifically expressed as:

[0040]

[0041]

[0042] Since double-difference observables eliminate the influence of satellite clock errors and receiver clock errors, they effectively reduce tropospheric and ionospheric delay errors in the signal, thus achieving higher computational accuracy in relative positioning.

[0043] The GNSS relative positioning observation equation can be expressed as:

[0044]

[0045] In the above formula, X i X k These are the location information for the receiver and the satellite, respectively; δt i δt k These are receiver clock bias and satellite clock bias, respectively; δ ion δtrop δ tide and δ rel These are the ionosphere, troposphere, tides, and relativistic effects, with tidal effects including Earth tides and ocean load tidal effects. For ambiguity parameters; δ rel_f Let O be the relativistic effect frequency correction. O represents the observed quantity, and F is the implicit function. Therefore, GNSS observations are the state vectors of the station and satellite, a function of several physical effects and ambiguity parameters. In principle, all parameters to be estimated can be solved using GNSS observations. Clearly, the above equations are nonlinear. Using the coordinates obtained from single-point positioning through pseudorange observations as approximations, a first-order Taylor series expansion of the GNSS carrier phase and pseudorange observation equations can be performed. After neglecting higher-order terms, the nonlinear function can be linearized, and the relative position can be obtained using the sampling least squares estimation method.

[0046] The nonlinear multivariable function of equation (7) is expressed as follows:

[0047] O = F(Y) = F(y1, y2, ... y n (8)

[0048] In the formula, Y is an n-dimensional vector, and linearization is achieved using a first-order Taylor series expansion.

[0049]

[0050] in,

[0051]

[0052] In the formula, the symbol Represents partial derivatives In Y = Y 0 The value of Y is given by ε, where ε is the truncation error, which is a function of the second-order partial derivative and dY. 0 It is the initial vector. Then equation (9) can be transformed into

[0053]

[0054] In the formula, C = F(Y) 0 The observation error and truncation error are denoted by v, OC by l, and partial derivatives... Then equation (11) can be transformed into:

[0055]

[0056] In the formula, l represents the adjustment observations, j and i are the subscripts of the unknown parameters and the observed quantities, and equation (12) is only a linear error equation. The linear error equation composed of a set of GNSS observations is:

[0057]

[0058] Equation (13) can be expressed in matrix form.

[0059]

[0060] In the formula, m is the dimension of the observation. In this paper, the solution X of the equation is the relative position difference between the phase centers of the two GNSS antennas, which is a 3-dimensional vector, i.e., n = 3.

[0061] To obtain high-precision relative positions, the observations are calculated using carrier phase observations. Each carrier phase observation contains unknown integer ambiguity parameters, while the linear equation solution obtained by the least squares method is a real-number solution. Therefore, it is necessary to solve for the ambiguity to obtain integer solutions, which can be achieved using the mixed-integer least squares method.

[0062] In the process of finding the real solution of the ambiguity, after linearizing the double-difference observation equation, it can be written as:

[0063]

[0064] In the formula, v is the residual, X and N are the parameters to be estimated, representing the non-ambiguity parameter and the ambiguity parameter, respectively; the superscripts n and m represent the dimensions of the non-ambiguity parameter and the ambiguity parameter, respectively; A and B are the corresponding submatrices of the non-ambiguity parameter X and the ambiguity parameter N in the double-difference observation equation design matrix, respectively.

[0065] l = LF(X) 0 N 0 L is a double-difference observation, F is a functional model of the observation L, and X... 0 N 0 These are approximate values ​​for the parameters to be estimated.

[0066] Solving equation (15) according to the least squares criterion, the objective function is:

[0067]

[0068] In the formula, Q L Let be the covariance matrix of the observations. It can be seen that, due to the constraint N∈Z on the ambiguity parameter... m Therefore, equation (16) is actually a mixed integer minimization problem. In the calculation process, the ambiguity parameter is usually solved as a real number to obtain its floating-point solution, transforming the equation into:

[0069]

[0070] Equation (17) can be simplified as follows:

[0071]

[0072] in, Given the weight matrix of the observations, solving equation (18) yields the real solutions to X and N and their covariance matrix:

[0073]

[0074]

[0075]

[0076]

[0077]

[0078] Then, the ambiguity floating-point solution is obtained using the following formula. Fixed as integer solutions

[0079]

[0080] Obtain a fixed solution for the ambiguity parameters. Then, the non-fuzziness parameters and their covariance matrix are calculated.

[0081]

[0082]

[0083] In the formula, This is the solution after the ambiguity is fixed. From equations (25) and (26), it can be seen that after the floating-point solution for the ambiguity parameter is fixed, the accuracy of the solution for the non-ambiguity parameter will also improve accordingly. Furthermore, fixing the ambiguity parameter reduces the number of parameters to be estimated in the observation equation to some extent, leading to more stable solution results. The solution obtained here... This represents the relative positioning result of the airborne GNSS phase center relative to the shipborne GNSS antenna phase center.

[0084] In one embodiment, step 104 includes the following steps:

[0085] Step 200: Perform coordinate transformation based on the relative positioning results of the airborne GNSS phase center and the shipborne GNSS antenna phase center to obtain the inertial navigation horizon coordinates of the airborne GNSS phase center and the shipborne GNSS antenna phase center.

[0086] Step 202: Based on the coordinates of the phase center of the beacon antenna relative to the airborne GNSS antenna in the airframe coordinate system and the attitude of the UAV, obtain the coordinates of the phase center of the beacon antenna relative to the airborne GNSS antenna in the inertial navigation horizon system.

[0087] Step 204: Based on the coordinates of the shipborne GNSS antenna phase center relative to the USB triaxial center in the inertial navigation deck system and the attitude and deformation data of the measuring ship, obtain the coordinates of the shipborne GNSS antenna phase center relative to the USB triaxial center in the inertial navigation horizon system.

[0088] Step 206: Add the inertial navigation horizon coordinates of the phase center of the airborne GNSS antenna relative to the phase center of the shipborne GNSS antenna, the inertial navigation horizon coordinates of the beacon antenna relative to the phase center of the airborne GNSS antenna, and the inertial navigation horizon coordinates of the phase center of the shipborne GNSS antenna relative to the three-axis center of the USB antenna to obtain the inertial navigation horizon coordinates of the UAV beacon antenna relative to the three-axis center of the USB antenna.

[0089] In one embodiment, step 202 includes: obtaining the coordinates of the beacon antenna relative to the airborne GNSS antenna phase center in the airframe coordinate system and the UAV attitude, as follows:

[0090] x2=B(c2)x 30 (27)

[0091] Where x2 is the phase center coordinate of the beacon antenna relative to the airborne GNSS antenna in the inertial navigation horizon system, and B(c2) is the transformation matrix from the UAV body coordinates to the inertial navigation horizon system. 30 The coordinates in the airframe coordinate system represent the phase center position of the UAV beacon antenna relative to the airborne GNSS antenna.

[0092] In one embodiment, step 204 includes: obtaining the coordinates of the shipborne GNSS antenna phase center relative to the USB triaxial center in the inertial navigation deck system based on the coordinates of the shipborne GNSS antenna phase center relative to the USB triaxial center in the inertial navigation deck system and the attitude and deformation data of the measured ship.

[0093] x1=B(c1)(x 20 -x 10 (28)

[0094] Where x1 is the coordinate of the phase center of the shipborne GNSS antenna relative to the three-axis center of the USB in the inertial navigation horizon frame, and B(c1) is the transformation matrix from the inertial navigation deck frame to the inertial navigation horizon frame. 20 x is the deck coordinate system coordinate of the phase center of the shipborne GNSS antenna relative to the three-axis center of the theodolite. 10 The coordinates of the antenna's three-axis center relative to the theodolite's three-axis center are in the deck system.

[0095] Specifically, the inertial deck coordinate system is a coordinate system established with the plane of the inertial deck as the basic plane and the center of the three inertial axes as the origin.

[0096] The inertial horizontal coordinate system is a coordinate system established with the local horizontal plane as the reference plane and the center of the three inertial navigation axes as the origin.

[0097] In one embodiment, the transformation matrix is:

[0098]

[0099]

[0100]

[0101]

[0102] Where B(j), j = b, c1, c2 represent the rotation matrices of the equivalent Euler angles for deformation, inertial navigation ship attitude, and UAV attitude, respectively, and K bi , and θ bi T respectively i The measured values ​​of the bow deformation angle, pitch deformation angle and roll deformation angle at any time.

[0103] In one embodiment, step 106 includes: performing coordinate transformation on the UAV beacon antenna relative to the three-axis center inertial navigation horizon coordinates of the USB antenna based on the ship's rocking and deformation data, to obtain the relative coordinates of the beacon antenna relative to the antenna's three-axis center in the USB antenna measurement coordinate system as follows:

[0104] x = B T (b)B T (c1)(x0+x1+x2) (33)

[0105] Where x is the relative coordinate of the beacon antenna to the antenna's three-axis center in the USB antenna measurement coordinate system, and x0 is the inertial navigation horizon coordinate of the airborne GNSS phase center to the shipborne GNSS antenna phase center (x0 is derived from the relative positioning result of the airborne GNSS phase center to the shipborne GNSS antenna phase center). After coordinate transformation (converted to ship inertial navigation horizon coordinates), x1 is the coordinate of the phase center of the shipborne GNSS antenna relative to the three-axis center of the USB in the inertial navigation horizon, x2 is the coordinate of the beacon antenna relative to the phase center of the airborne GNSS antenna in the inertial navigation horizon, (x0+x1+x2) is the coordinate of the three-axis center of the beacon antenna relative to the USB antenna in the inertial navigation horizon, B(b) is the transformation matrix from the USB antenna to the theodolite, and B(c1) is the transformation matrix from the inertial navigation deck frame to the inertial navigation horizon.

[0106] Based on the azimuth and elevation observations at each self-tracking moment, the corresponding refraction correction values ​​are selected from the atmospheric grid refraction data. The elevation and azimuth angles after axis error correction are calculated based on the relative coordinates of the beacon antenna to the antenna's three-axis center in the USB antenna measurement coordinate system and the refraction correction values.

[0107] Specifically, compared with existing axis system parameter calibration methods, the method of tracking UAVs, due to their relatively short distance, cannot ignore the relative positional relationship between the beacon and the antenna of the airborne GNSS equipment. It is necessary to obtain high-precision beacon positions based on the attitude information of the UAV and the relative position of the beacon and GPS. This makes it impossible to directly apply the existing axis system calibration data processing methods for tracking satellites and other precision-orbit targets. This application proposes a data processing method for UAV calibration.

[0108] For the GNSS observation data processing results, the UAV attitude measurement results and the observation data from the survey vessel equipment are time-aligned. The telemetry and control equipment uses a time synchronization system synchronized with GPS, and the time stamp in the GNSS relative positioning results also uses a time synchronized with GPS. After preprocessing such as effective tracking measurement data extraction, the theoretical relative position relationship between the USB ("Unified S-band") device's time beacon antenna and the USB's three-axis center during the self-tracking segment is obtained. This yields effective measurement data for axis parameter calibration. The data preprocessing flow is as follows: Figure 2 As shown, the calculation process for the three-axis center position of the UAV beacon antenna relative to the USB antenna is as follows: Figure 3 As shown.

[0109] Figure 2 USB valid self-tracking data segment extraction: Based on the status code of the data, only the data corresponding to the self-tracking time period represented by the status code is selected to obtain the i-th self-tracking time T. i and the corresponding A i E i angle,

[0110] (i = 1, 2, ..., N) N is the number of valid data.

[0111] Atmospheric refraction correction: the i-th self-tracking time T i and the corresponding A i E i Angle, select the corresponding refraction correction value ΔE from the atmospheric grid refraction data. i .

[0112] Coordinate transformation: The coordinate transformation process requires ship roll and deformation data. The specific calculation process is as follows:

[0113] Let the bow roll angle K be... bi pitch deformation angle Roll deformation angle θ bi For T i The measured value at time K b'i , θ b'i For equivalent Euler angles, then:

[0114]

[0115]

[0116] θ b'i =sin -1 (bcosα)-α (36)

[0117] in,

[0118] Euler angle rotation matrices are extensively used when transforming between the ship's internal coordinate system and the UAV's coordinate system.

[0119] set up Where j = b, c1, c2 represent the rotation matrices of the equivalent Euler angles for deformation, inertial navigation ship attitude, and UAV attitude, respectively. Their expressions are shown in equations (29) to (32). B(j) and B -1 (j) and B T The relation for (j) is:

[0120]

[0121] Assume the deck coordinate system coordinates of the antenna's three-axis center relative to the theodolite's three-axis center are x. 10 The phase center of the shipborne GNSS antenna relative to the three-axis center of the theodolite in the deck system coordinates is x. 20 The body coordinates of the phase center position of the UAV beacon antenna relative to the airborne GNSS antenna are x. 30 After solving the double difference model, the relative coordinates of the airborne GNSS phase center with respect to the shipborne GNSS antenna phase center in the shipborne inertial navigation horizon system are x0. Then, the relative coordinates of the beacon antenna with respect to the antenna triaxial center in the USB antenna measurement coordinate system are as shown in equation (33).

[0122] The theoretical angle E' is calculated based on the relative coordinates of the beacon antenna with respect to the antenna's three-axis center in the USB antenna measurement coordinate system. i A' i .

[0123] In one embodiment, step 108 includes: establishing a set of equations for calculating shaft system parameters based on the pitch and azimuth angles after shaft system error correction, the azimuth observation value, and the pitch observation value:

[0124] Dx=l (38)

[0125]

[0126] x=(A 01 E 01 x1 x2 δ m S b1 )' (40)

[0127]

[0128] Where E is the elevation observation value; E 01 E is the pitch axis zero value. 01 =E0+C e E0 is the zero value of the pitch optical axis, C e The antenna's photoelectric axis is mismatched longitudinally; A is the azimuth observation value; A 01 E′ is the zero value of the azimuth electric axis; E′ is the pitch angle after axis system error correction; A′ is the azimuth angle after axis system error correction; ΔA Z The azimuth dynamic lag is ΔE. Z For pitch dynamic hysteresis; ΔE g δ is the amount of downward tilt due to gravity. m The pitch and azimuth axes are not orthogonal; S b1 S represents the deviation of the electric shaft relative to the mechanical shaft. b1 =S b +C s S b C represents the deviation of the optical axis from the mechanical axis. S The antenna's photoelectric axis is mismatched laterally; x1 = β m ·cos(A m ),x2=β m ·sin(A m ), β m The maximum non-horizontal slope of the market, A m This represents the direction of maximum tilt of the market index.

[0129] The least squares method was used to calculate the equations for the shaft system parameters, and A was obtained. 01 E01 x1, x2, δ m S b1 Six parameter values; the maximum tilt of the disk and the maximum tilt azimuth of the disk are calculated based on the values ​​of x1 and x2; the zero value of the pitch electric axis and the zero value of the pitch optical axis are obtained based on the relationship between the zero value of the pitch electric axis and the zero value of the pitch optical axis, the relationship between the deviation of the electric axis relative to the mechanical axis and the deviation of the optical axis relative to the mechanical axis, and the photoelectric deviation value.

[0130] Specifically, a set of equations for calculating shaft system parameters is established. Using effective observation data, the shaft system parameters are solved. Based on the correction formula for angular shaft system parameters, the shaft system parameters are calibrated using a UAV. This allows for direct calibration without relying on photoelectric deviation, yielding the angular correction expression.

[0131] E′=EE 01 -β m ·cos(AA m )-ΔE Z -ΔE g ·cosE (42)

[0132] A′=AA 01 -β m ·tanE·sin(AA m )-δ m ·tanE-S b1 ·secE-ΔA Z ·secE (43)

[0133] In the formula, E′ is the pitch angle after correction for shaft system error, E is the observed pitch value, and E 01 Let A' be the zero value of the pitch electrical axis, A' be the azimuth angle after axis system error correction, and A be the azimuth observation value. 01 β is the zero value of the azimuth electric axis. m The maximum non-horizontal slope of the market, A m The maximum tilt of the market index; ΔA Z As the azimuth dynamic lag, ΔE Z For pitch dynamic hysteresis, ΔE g δ is the amount of downward tilt due to gravity. m Because the pitch axis and azimuth axis are not orthogonal, S b1 The above parameters are the deviations of the electric shaft from the mechanical shaft.

[0134] To facilitate comparison with the existing equivalent axis parameter method that includes photoelectric deviation parameters, the angle measurement error equation containing photoelectric deviation parameters is given below.

[0135] E′=E-E0-β m ·cos(AA m )-Ce -ΔE Z -ΔE g ·cosE (44)

[0136] A′=A-A0-β m ·tanE·sin(AA m )-δ m ·tanE-S b ·secE-C S ·secE-ΔA Z ·secE (45)

[0137] Where E0 is the zero value of the elevation optical axis, A0 is the zero value of the azimuth optical axis, and C... S For the lateral mismatch of the antenna's opto-axis, C e For antenna photoelectric axis longitudinal mismatch, ΔA Z As the azimuth dynamic lag, ΔE Z For pitch dynamic hysteresis, here S b The above axis parameters refer to the deviation of the optical axis from the mechanical axis.

[0138] Comparing equations (30) and (32), it can be seen that...

[0139] E 01 =E0+C e (46)

[0140] Comparing equations (31) and (33), it can be seen that...

[0141] S b1 =S b +C s (47)

[0142] All other parameters are consistent. It can also be seen from the above equations that the equivalent axis parameter model is based on the optical axis parameters, converting the optical axis direction into the electrical axis direction through the photoelectric deviation parameter. When the photoelectric deviation is known, the solution methods for both are consistent. When C... e =0, C s When = 0, the values ​​of the optical axis parameter and the electrical axis parameter are also the same.

[0143] Let x1 = β m ·cos(A m ),x2=β m ·sin(A m Substituting into equations (42) and (43), it can be further expressed as shown in equations (38) to (41).

[0144] Using the relative position of the beacon antenna to the three-axis center of the USB antenna as the corrected azimuth and elevation angles, and combining them with the actual measured angles, a system of equations is established using equation (38) and the measured data. The least squares method can then be used to calculate x. Thus, A can be directly obtained. 01 E 01 x1, x2, δ m S b1 The six parameter values ​​can be used to calculate β based on the values ​​of x1 and x2. m and A m Combining equations (46) and (47) with the photoelectric deviation value, the equivalent optical axis parameters E0,S can be obtained. b .

[0145] It should be understood that, although Figure 1 The steps in the flowchart are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order in which these steps are executed, and they can be performed in other orders. Figure 1 At least some of the steps in the process may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0146] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0147] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for calibrating the axis parameters of a shipborne telemetry and control antenna for tracking unmanned aerial vehicles, characterized in that, The method includes: Based on the data recorded by the central computer, the effective USB tracking measurement data is extracted to obtain each self-tracking moment and the corresponding azimuth and elevation observation values. Based on a set of raw measurement data simultaneously observed by airborne and shipborne GNSS equipment, the linearized double-difference observation equation is solved using the mixed integer least squares method to obtain the relative positioning result of the phase center of the airborne GNSS antenna relative to the phase center of the shipborne GNSS antenna. Based on the relative positioning results of the phase center of the airborne GNSS antenna relative to the phase center of the shipborne GNSS antenna, the coordinates of the beacon antenna relative to the phase center of the airborne GNSS antenna in the body coordinate system, the attitude of the UAV, the coordinates of the phase center of the shipborne GNSS antenna relative to the three-axis center of the USB in the inertial navigation deck system, and the attitude and deformation data of the measuring ship, the coordinates of the UAV beacon antenna relative to the three-axis center of the USB antenna in the inertial navigation horizontal coordinate system are obtained. Based on the ship's rocking and deformation data, the coordinate transformation of the UAV beacon antenna relative to the three-axis center inertial navigation horizon coordinates of the USB antenna is performed. Based on the obtained coordinate transformation results and atmospheric refraction correction values, the pitch angle and azimuth angle after axis error correction are obtained. Based on the pitch and azimuth angles after the shaft system error correction, the azimuth observation value, and the pitch observation value, a set of shaft system parameter calculation equations is established and solved using the least squares method to obtain the calibration results of the shipborne telemetry and control antenna shaft system parameters. Among them, based on the coordinates of the phase center of the beacon antenna relative to the airborne GNSS antenna in the airframe coordinate system and the attitude of the UAV, the coordinates of the phase center of the beacon antenna relative to the airborne GNSS antenna in the inertial navigation horizon system are obtained as follows: in, The coordinates of the phase center of the beacon antenna relative to the airborne GNSS antenna in the inertial navigation horizon system are: This is the transformation matrix from the UAV's body coordinates to the inertial navigation horizon frame. The coordinates in the body coordinate system represent the phase center position of the UAV beacon antenna relative to the airborne GNSS antenna. Based on the coordinates of the shipborne GNSS antenna phase center relative to the USB triaxial center in the inertial navigation deck system and the attitude and deformation data of the measuring ship, the coordinates of the shipborne GNSS antenna phase center relative to the USB triaxial center in the inertial navigation horizon system are obtained as follows: in, The coordinates of the phase center of the shipborne GNSS antenna relative to the three-axis center of the USB in the inertial navigation horizon frame. The transformation matrix is ​​given by the inertial navigation deck frame to the inertial navigation horizon frame. The coordinates of the shipborne GNSS antenna phase center relative to the three-axis center of the theodolite are in the deck system. The coordinates of the antenna's three-axis center relative to the theodolite's three-axis center are in the deck system.

2. The method according to claim 1, characterized in that, Based on the data recorded by the central computer, effective USB tracking measurement data is extracted to obtain the azimuth and elevation observations for each self-tracking moment, including: The raw USB tracking strategy data is extracted from the central computer's disk data. Based on the status codes of the extracted data, only the data corresponding to the self-tracking time period represented by the status codes is selected to obtain the first... i Self-tracking time and the corresponding azimuth and elevation observations, among which, i =1,2,..., N , N The number of valid data.

3. The method according to claim 1, characterized in that, Based on a set of raw measurement data simultaneously observed by airborne and shipborne GNSS equipment, the linearized double-difference observation equations were solved using the mixed integer least squares method to obtain the coordinates of the airborne GNSS antenna phase center relative to the shipborne GNSS antenna phase center in the inertial navigation horizon system, including: Construct a double-difference observation equation and linearize it to obtain the linearized double-difference observation equation: in, For residuals, Here are the parameters to be estimated, representing the non-fuzzy parameter and the fuzzy parameter, respectively; superscript n and m These represent the dimensions of the non-fuzzy parameter and the fuzzy parameter, respectively. These are represented as the corresponding submatrices of the non-ambiguity parameter X and the ambiguity parameter N in the design matrix of the double-difference observation equation; ; It is a double-difference observation; Based on a set of raw measurement data simultaneously observed by airborne and shipborne GNSS equipment, the linearized double-difference observation equation is solved using the mixed integer least squares method to obtain the coordinates of the phase center of the airborne GNSS antenna relative to the phase center of the shipborne GNSS antenna in the inertial navigation horizon system.

4. The method according to claim 1, characterized in that, Based on the relative positioning results of the airborne GNSS antenna phase center with respect to the shipborne GNSS antenna phase center, the coordinates of the beacon antenna relative to the airborne GNSS antenna phase center in the airframe coordinate system, the UAV attitude, the coordinates of the shipborne GNSS antenna phase center relative to the USB three-axis center in the inertial navigation deck system, and the attitude and deformation data of the measuring ship, the coordinates of the UAV beacon antenna relative to the USB antenna three-axis center in the inertial navigation horizontal coordinate system are obtained, including: Based on the relative positioning results of the phase center of the airborne GNSS antenna with respect to the phase center of the shipborne GNSS antenna, coordinate transformation is performed to obtain the inertial navigation horizon coordinates of the phase center of the airborne GNSS antenna with respect to the phase center of the shipborne GNSS antenna. Based on the coordinates of the phase center of the beacon antenna relative to the airborne GNSS antenna in the body coordinate system and the attitude of the UAV, the coordinates of the phase center of the beacon antenna relative to the airborne GNSS antenna in the inertial navigation horizon system are obtained; Based on the coordinates of the phase center of the shipborne GNSS antenna relative to the three-axis center of the USB in the inertial navigation deck system and the attitude and deformation data of the measuring ship, the coordinates of the phase center of the shipborne GNSS antenna relative to the three-axis center of the USB in the inertial navigation horizon system are obtained. The coordinates of the UAV beacon antenna relative to the phase center of the airborne GNSS antenna in the inertial navigation horizontal system, the coordinates of the beacon antenna relative to the phase center of the airborne GNSS antenna in the inertial navigation horizontal system, and the coordinates of the phase center of the shipborne GNSS antenna relative to the three-axis center of the USB antenna in the inertial navigation horizontal system are added together to obtain the coordinates of the UAV beacon antenna relative to the three-axis center of the USB antenna in the inertial navigation horizontal system.

5. The method according to claim 1, characterized in that, The transformation matrix is: in, Let represent the rotation matrices for the equivalent Euler angles of the deformed, inertial navigation ship attitude, and UAV attitude, respectively. , and They are respectively The measured values ​​of the bow deformation angle, pitch deformation angle and roll deformation angle at any time.

6. The method according to claim 1, characterized in that, Based on the ship's rolling and deformation data, a coordinate transformation is performed on the three-axis center inertial navigation horizon coordinates of the UAV beacon antenna relative to the USB antenna. Based on the obtained coordinate transformation results and atmospheric refraction correction values, the pitch and azimuth angles after axis error correction are obtained, including: Based on the ship's rocking and deformation data, a coordinate transformation was performed on the inertial navigation horizon coordinates of the UAV beacon antenna relative to the three-axis center of the USB antenna to obtain the relative coordinates of the beacon antenna relative to the antenna's three-axis center in the USB antenna measurement coordinate system: in, The relative coordinates of the beacon antenna with respect to the antenna's three-axis center in the USB antenna measurement coordinate system. The coordinates of the phase center of the airborne GNSS antenna relative to the phase center of the shipborne GNSS antenna are in the inertial navigation horizon coordinates. The coordinates of the phase center of the shipborne GNSS antenna relative to the three-axis center of the USB in the inertial navigation horizon frame. The coordinates of the phase center of the beacon antenna relative to the airborne GNSS antenna in the inertial navigation horizon frame. The coordinates of the beacon antenna relative to the three-axis center of the USB antenna in the inertial navigation horizon frame are given. This is the transformation matrix from USB antenna to theodolite. This is the transformation matrix from the inertial navigation deck frame to the inertial navigation horizon frame; Based on the azimuth and elevation observations at each self-tracking moment, the corresponding refraction correction value is selected from the atmospheric grid refraction data; The elevation and azimuth angles after axis error correction are calculated based on the relative coordinates of the beacon antenna with respect to the antenna's three-axis center in the USB antenna measurement coordinate system and the refraction correction value.

7. The method according to claim 1, characterized in that, Based on the pitch and azimuth angles after shaft system error correction, the azimuth observation value, and the pitch observation value, a set of shaft system parameter calculation equations is established and solved using the least squares method to obtain the calibration results of the shipborne telemetry and control antenna shaft system parameters, including: Based on the pitch and azimuth angles after shaft system error correction, the azimuth observation value, and the pitch observation value, the following set of equations for shaft system parameter calculation is established: in, These are elevation observations; The pitch axis is zero. , The pitch optical axis is zero. The problem stems from a longitudinal mismatch between the antenna's photoelectric axis; These are azimuth observations; The azimuth electrical axis is zero. The pitch angle after correction for shaft system errors; This is the azimuth angle after correction for shaft system errors; The location is dynamically lagging. For pitch dynamic lag; This is the amount of downward pressure due to gravity. The pitch and azimuth axes are not orthogonal; This refers to the deviation of the electric shaft relative to the mechanical shaft. , This represents the deviation of the optical axis relative to the mechanical axis. The problem stems from a lateral mismatch in the antenna's opto-axis. , , This represents the maximum inclination of the overall market when it is not horizontal. This represents the direction of maximum horizontal tilt of the overall market. The least squares method was used to calculate the equations for the shaft system parameters, and the results were obtained. Six parameter values; according to The values ​​are used to calculate the maximum non-horizontal tilt of the large disk and the maximum non-horizontal tilt direction of the large disk. Based on the relationship between the zero value of the pitch electrical axis and the zero value of the pitch optical axis, the relationship between the deviation of the electrical axis relative to the mechanical axis and the deviation of the optical axis relative to the mechanical axis, and the photoelectric deviation value, the zero value of the pitch optical axis and the deviation of the optical axis relative to the mechanical axis are obtained.

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