Rapid fire control solution method and system

Abstract

The present application discloses a rapid fire control solution method and system, which relates to the field of attitude solution. Based on the shell setting signal, detection instructions are sent to various sensor devices on the system equipment; the system working state and setting information and target position coordinates are determined according to the monitoring data sent back by all sensor devices; the historical shell data in the firing table are obtained, and the trajectory solution is performed according to the historical shell data, setting information and target position coordinates to determine the trajectory solution offset, and a trajectory correction compensation model is established to determine the trajectory correction offset; the trajectory trajectory is jointly corrected according to the trajectory solution offset and the trajectory correction offset to determine the impact point coordinates. The solution uses FPGA as a fire control solution chip to realize parallel calculation of large amounts of data and improve the real-time performance of the solution; an automatic intelligent statistical model is used to learn the correction offset of each live ammunition to realize intelligent correction of the impact point.

Description

Technical Field

[0001] The present application relates to the field of attitude solution, and in particular to a rapid fire control solution method and system. Background Art

[0002] Fire control solution technology mainly realizes the measurement of meteorological and ballistic conditions, the calculation and setting of weapon firing parameters, and the solution of bullet impact points. It is an important support for battlefield firepower strike systems and is widely used in light weapons, heavy weapons and armored fire control systems. In the past, various detection equipment in fire control systems operated independently and had poor integration. The shooting accuracy of weapons often depended on the shooter's proficiency and shooting level in the use of rangefinders, meteorological instruments, ballistic solution terminals, and sights. The shooting process was cumbersome, the skill training cycle was long, the firepower response time was long, and the hit rate was low. In the face of the development needs of multi-functionality, miniaturization, and integration, the new generation of fire control solution technology is gradually developing in the direction of multi-sensor collaborative detection, information fusion, real-time, and intelligence, providing solutions for realizing integrated reconnaissance and strike and intelligent control of ammunition.

[0003] The main process of fire control solution is: after receiving the setting signal, the current target position, target distance, ballistic conditions, environmental parameters, correction offset and other data are immediately transmitted to the solution center for calculation. The solution center will solve the impact point based on the prior firing table of the current type of ammunition. The shooter can aim at the target at the impact point and shoot to hit the target.

[0004] Among the related technologies, the mainstream fire control solution technology has the following shortcomings: (1) It is mostly implemented using platforms such as MCU and DSP, the control program follows a sequential execution mechanism, lacks data parallel processing capabilities, and has a slow solution speed; (2) It only supports a single type of projectile, and the compatibility between projectiles and guns is poor; (3) The impact point correction is a fixed correction, and it does not have statistical learning capabilities, and the degree of intelligence is low; (4) The firing table update process is cumbersome, requiring technicians to re-modify the software and burn the program. Summary of the invention

[0005] The embodiments of the present application provide a rapid fire control solution method and system to solve the problems of slow solution speed and intelligence in the related art.

[0006] In one aspect, the present application discloses a rapid fire control solution method, the method comprising:

[0007] In response to receiving the shell setting signal, it sends detection instructions to various sensor devices installed on the system equipment, and waits for the sensor devices to send back monitoring data;

[0008] Determine the system working status based on the monitoring data sent back by all sensor devices, and determine the installation information and target position coordinates based on the monitoring data;

[0009] Acquire historical shell data in the firing table, perform trajectory calculation based on the historical shell data, various set information and target position coordinates, and determine the trajectory calculation offset; and establish a trajectory correction compensation model based on the historical shell data, various set information and target position coordinates, and determine the trajectory correction offset;

[0010] The ballistic trajectory is corrected jointly according to the trajectory solution offset and the trajectory correction offset to determine the coordinates of the impact point.

[0011] Specifically, the sensing device receiving the detection instruction includes at least a rangefinder, a temperature and pressure sensor, a wind speed sensor and an angle sensor, which are respectively used to measure the distance between the launch point and the target, the current temperature and pressure data, the wind speed data and the azimuth data.

[0012] Specifically, the system working state is determined according to the monitoring data sent back by all the sensor devices, and the parameter information and target position coordinates are determined according to the monitoring data, including:

[0013] In response to receiving the monitoring data sent back by all the sensor devices within the preset time, the target position coordinates and set parameter information at the current moment are generated; in response to not receiving the monitoring data sent back by all the sensor devices within the preset time, it is determined that the system data is abnormal.

[0014] Specifically, performing trajectory calculation according to the historical shell data, the set element information and the target position coordinates to determine the trajectory calculation offset includes:

[0015] Obtain at least three sets of continuous historical shell data about the target object closest to the current moment in the firing table, and calculate the trajectory solution offset of the target object based on the set element information and the Lagrange difference formula , which is expressed as follows:

[0016]

[0017] Among them Represent three sets of historical shell data respectively; independent variable Indicates the setting of various meta information.

[0018] Specifically, the process of establishing a trajectory correction compensation model according to the historical shell data, the set element information and the target position coordinates to determine the trajectory correction offset includes:

[0019] Obtain the historical shell data and construct a data point set P according to the time sequence of the data;

[0020] Perform regression analysis based on polynomials to correct the offset and construct a coefficient matrix A of a k-order polynomial;

[0021] The square sum loss function is used to characterize the square sum error L between the function value and the true value, and the least squares method is used to solve the parameter matrix;

[0022] The trajectory correction compensation model is updated based on the parameter matrix, and the trajectory correction offset is calculated by inputting the set parameter information and the target position coordinates.

[0023] Specifically, the data point set ;

[0024] The k-order polynomial function is expressed as follows:

[0025] ;

[0026] Convert k-order polynomial function into matrix expression ;

[0027]

[0028] The matrix X represents the k-order polynomial matrix of the transformation, and Y represents the position matrix in the point set P;

[0029] The sum of squared errors L is expressed as:

[0030]

[0031] When solving the parameter matrix, the derivative function is obtained based on the derivative calculation of matrix A as follows:

[0032]

[0033] Let the derivative function be 0, and the obtained parameter matrix is ​​expressed as:

[0034] .

[0035] On the other hand, the present application provides a rapid fire control solution system, which is applied to a rapid fire control solution method, including an FPGA, a storage module and an external sensor device, wherein the sensor device includes a laser rangefinder, a temperature and pressure sensor, a wind speed sensor and an angle sensor; the FPGA is connected to the sensor device via an external interface;

[0036] The FPGA includes a perception module, a soft core processor and a solution module, and the modules are interconnected through an AXI bus; the storage module is connected to the AXI bus through an API interface;

[0037] The perception module is connected to the sensor device through an external interface to obtain monitoring data; the soft-core processor controls the operation of the system, controls data storage and parameter reading; the solution module performs fire control trajectory solution and trajectory correction compensation, and calculates the trajectory solution offset and trajectory correction offset.

[0038] Specifically, the sensing module includes a UART transceiver circuit and an I2C transceiver circuit, which are responsible for real-time detection of temperature, air pressure, distance, wind speed and angle and receiving meter data.

[0039] Specifically, the storage module stores the main control software, the firing table and the variable parameters, and receives the monitoring data collected by the perception module through the SPI interface and the AXI bus.

[0040] Specifically, the AXI bus is also connected to an external interface via a GPIO interface, and the soft-core processor receives terminal instructions and external control signals via the AXI bus and the GPIO interface, and sends solution data to the outside.

[0041] The beneficial effects brought by the technical solution provided by the embodiment of the present application include at least:

[0042] (1) Using FPGA as the fire control solution chip, fully utilizing its data parallel processing capability, realizing parallel computing of large amounts of data, and improving the real-time performance of the solution;

[0043] (2) A multi-projectile type calculation mode has been developed, which can store multiple firing tables and support multiple projectile type selections such as light, heavy, and armored weapons;

[0044] (3) In actual shooting, the target hit rate will be affected by many factors such as the shooter's shooting habits and the actual ballistic conditions. An automatic intelligent statistical model is used to learn the offset correction for each live ammunition shot, and the optimal offset of the impact point in the current state is calculated based on the model to achieve intelligent correction of the impact point.

[0045] (4) Added a new shooting table update module to support online shooting table update. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is a system schematic diagram of a rapid fire control solution system provided in an embodiment of the present application;

[0047] Figure 2 It is a workflow diagram of the main control software provided in the embodiment of the present application;

[0048] Figure 3 is a flow chart of a rapid fire control solution method provided by an embodiment of the present application;

[0049] Figure 4 It is the algorithm flow chart of the rapid fire control solution method;

[0050] Figure 5 A comparison diagram of the traditional method and the real-time updating of the firing table is shown;

[0051] Figure 6 The principle flow chart of online updating of the shooting table of the present application is disclosed. DETAILED DESCRIPTION

[0052] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0053] The term "multiple" as used herein refers to two or more than two. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the related objects are in an "or" relationship.

[0054] Figure 1 This is a system diagram of a rapid fire control solution system provided in an embodiment of the present application, including an FPGA, a storage module and an external sensor device, wherein the sensor device includes a laser rangefinder, a temperature and pressure sensor, a wind speed sensor and an angle sensor, etc. In an example of the present application, the FPGA uses the XC7A50T of the Xilinx Artix-7 series, and the FLASH memory uses the N25Q128 of Micron. The FPGA is connected to the sensor device through an external interface.

[0055] The FPGA is divided according to functions and adopts the AXI bus architecture design. The AXI bus is used to connect all modules to realize parallel data interaction. Specifically, it includes the perception module, soft-core processor and solution module. The modules are interconnected through the AXI bus, and the storage module is connected to the AXI bus through the API interface. The perception module connects to the sensor equipment through the external interface to obtain monitoring data. The soft-core processor controls the operation of the system, controls data storage and parameter reading; the solution module performs fire control trajectory solution and trajectory correction compensation, and calculates the trajectory solution offset and trajectory correction offset. When the fire control solution module receives the power-on signal, the crystal oscillator starts working, and the FPGA loads and starts the main control software from the memory.

[0056] The perception module includes UART transceiver circuit and I2C transceiver circuit, which are responsible for real-time detection of temperature, air pressure, distance, wind speed and angle parameters and receiving data from the shooting table. The storage module stores the main control software, shooting table and variable parameters, and receives the monitoring data collected by the perception module through the SPI interface and AXI bus. The AXI bus also connects to the external interface through the GPIO interface. The soft-core processor receives terminal instructions and external control signals through the AXI bus and GPIO interface, and sends solution data to the outside.

[0057] like Figure 2 As shown in the figure, the main control software workflow is roughly summarized as follows:

[0058] Step 1: The soft core processor reads register parameters from the memory to complete the master control software parameter initialization;

[0059] Step 2: The main control software updates the bullet type and firing table data online through the serial port and stores them in the memory;

[0060] Step 3: The main control software communicates with various sensing devices through the perception module to achieve real-time detection of the set parameters, update the trajectory correction compensation model and calculate the trajectory correction offset; the trajectory correction compensation model here is specifically based on the collected parameters, coordinate data and historical artillery data to determine the trajectory correction offset. Because the main control software will calculate the trajectory and determine the trajectory solution offset according to the target, and the simple trajectory solution offset cannot meet the requirements in terms of real-time and accuracy, this application continues to use historical artillery data to further establish an intelligent learning model, and compensate for secondary corrections based on trajectory trends.

[0061] Step 4: The main control software detects the setting signal in real time through the external interface, and executes the setting of various parameters after receiving the setting signal;

[0062] Step 5: The main control software controls the FPGA to perform ballistic calculation based on the current bullet type shooting table, and calculates the optimal offset of the impact point in the current state based on the trajectory correction compensation model;

[0063] Step 6: The main control software outputs the impact point information through the external interface.

[0064] Based on the above-mentioned rapid fire control solution system, the present application also provides a rapid fire control solution method in an embodiment, see Figure 3 As shown, the specific steps include:

[0065] S1, in response to receiving the shell setting signal, sending detection instructions to various sensor devices installed on the system equipment, and waiting for the sensor devices to return monitoring data;

[0066] Reference Figure 1 In the system architecture shown, when the system receives an external setting signal in the idle state, the soft-core processor will start the main control software and send relevant instructions to all sensor devices through the external interface via the AXI bus and GPIO interface. Including but not limited to range finders, temperature and pressure sensors, wind speed sensors and angle sensors, these sensor devices are used to measure the distance between the launch point and the target, the current temperature and pressure data, wind speed data and azimuth data, etc.

[0067] S2, determine the system working status according to the monitoring data sent back by all sensor devices, and determine the set element information and target position coordinates according to the monitoring data;

[0068] The system working state mentioned in this embodiment is used to determine the state of the sensor device, because the accuracy of the set information has a great impact on the target hit rate. Therefore, if at least one sensor device is abnormal, such as a sensor device failure or no response, the set information generated is incomplete. If used directly, it may not be able to accurately hit. In addition, when the sensor device takes too long to send back, even if the FPGA receives the data, the hit accuracy will be reduced due to timeliness.

[0069] Based on this, in order to ensure the timeliness and integrity of the system, this application sets the preset time for receiving the returned data through FPGA. Figure 4 The algorithm flow chart of the rapid fire control solution method shown in the figure shows that when the FPGA (soft core processor) receives the monitoring data sent back by all sensor devices within the preset time, it determines that the system function is complete and generates the target position coordinates (x0, y0) and the set element information at the current moment in time. If the FPGA does not receive the monitoring data sent back by all sensor devices within the preset time, it determines that the system data is abnormal, and can selectively discard the data or trigger an alarm.

[0070] It should be noted that the firing table function may need to be updated before executing the trajectory solution. This step is mainly determined based on the actual situation. The traditional firing table requires the operator to update it manually, and the real-time performance cannot be guaranteed. Figure 5 The diagram shows the comparison between the traditional method and the real-time update of the shooting table. Method 1 is the traditional method of updating the shooting table, and method 2 is the method of updating the shooting table using the developed online storage function. Method 1 requires the software developer to modify the software, regenerate and download the solidification file. This method requires the board software to be updated to complete the addition; while method 2 reduces the usage threshold and simplifies the update steps. Any user can complete the online update of the shooting table.

[0071] Figure 6 The principle flow chart of the online update of the firing table of the present application is disclosed. When the serial port module responds to the external firing table data input, the memory on the FPGA will open up storage space to receive the serial port data. The main control program reads, analyzes and processes the data in the storage space through the AXI bus, sorts out the new data and adds it to the original firing table group. After the data processing is completed, the main control software accesses the FLASH through the SPI interface, stores the updated firing table group, and completes the online update of the firing table.

[0072] S3, obtaining historical shell data in the firing table, performing trajectory calculation based on the historical shell data, the set information and the target position coordinates, and determining the trajectory calculation offset; and establishing a trajectory correction compensation model based on the historical shell data, the set information and the target position coordinates, and determining the trajectory correction offset;

[0073] This phase is divided into two parts: the conventional ballistic solution and the calculation of the ballistic solution offset based on the currently collected set parameter information. The other part is determined by the correction offset input from the outside. When the correction offset is clearly present, the ballistic correction compensation model is enabled for additional correction compensation.

[0074] For the trajectory calculation process, the commonly used trajectory calculation method is the interpolation calculation method based on the firing table, including Lagrange interpolation, Newton interpolation, Gauss interpolation, etc. In order to simplify the calculation complexity and improve the calculation timeliness, this application uses the Lagrange interpolation method to solve the offset Specifically, obtain at least three sets of continuous historical shell data about the target object closest to the current moment in the firing table, and calculate the trajectory solution offset of the target object based on the set element information and the Lagrange difference formula. , that is, find the point to be found in the shooting table The three closest known points , the calculation is completed based on the following Lagrange interpolation formula, expressed as follows:

[0075]

[0076] The independent variable in the above formula is Indicates the set of metadata, such as temperature, distance, wind speed and other data, that is, each sensor data type is established separately , and add them up to finally get the trajectory solution offset (Δx1, Δy1).

[0077] As for the process of calculating the trajectory correction offset, this application adopts the following steps to implement it:

[0078] 1. Obtain historical shell data and construct a data point set P according to the time sequence of the data;

[0079] 2. Perform regression analysis based on the polynomial to correct the offset and construct the coefficient matrix A of the k-order polynomial;

[0080] 3. Use the sum-of-squares loss function to characterize the sum-of-squares error L between the function value and the true value, and use the least squares method to solve the parameter matrix;

[0081] 4. Update the trajectory correction compensation model based on the parameter matrix, input the set parameter information and target position coordinates to calculate the trajectory correction offset.

[0082] The core of this solution is to establish an intelligent statistical learning model, perform regression analysis on the correction offset from the trend presented by historical shell data, and establish a trajectory correction compensation model. When the correction offset is input, the trajectory correction compensation model is enabled and combined with historical shell data for correction. Data point set ; The k-order polynomial function is expressed as follows:

[0083] ;

[0084] Because it is point set data, if you want to find relevant information in the data set, you can use matrix polarity solution, that is, convert the k-order polynomial function into a matrix expression ;

[0085]

[0086] The matrix X represents the k-order polynomial matrix of the transformation, and Y represents the position matrix in the point set P;

[0087] Construct the sum of squared error L, expressed as:

[0088]

[0089] When using the least squares method to solve the parameter matrix, the derivative function is obtained based on the derivative calculation of matrix A as follows:

[0090]

[0091] Let the derivative function be 0, and the obtained parameter matrix is ​​expressed as:

[0092] .

[0093] Substituting the solved coefficients into the polynomial function is the final model. Each time the model receives a new offset input, it will automatically update according to the historical shell data to achieve real-time updates.

[0094] For this step, after calculating the parameter matrix After that, the model is updated immediately, and then the information of various elements and the target position coordinates (x0, y0) are substituted to obtain the trajectory correction offset (Δx2, Δy2). In general, the model can record and learn the correction offset of each input. Its essence is a collection of probability models based on prior correction offsets. It inputs fixed elements and outputs the optimal offset (Δx2, Δy2) based on the prior correction offset.

[0095] S4. Correct the ballistic trajectory according to the ballistic solution offset and the ballistic correction offset to determine the coordinates of the impact point.

[0096] Set the impact point coordinates (x', y'), then based on the cumulative sum of the above two offset data, x'=x0+Δx1+Δx2, y'=y0+Δy1+Δy2.

[0097] In summary, this solution has the following advantages over traditional technical solutions:

[0098] (1) Using FPGA as the fire control solution chip, fully utilizing its data parallel processing capability, realizing parallel computing of large amounts of data, and improving the real-time performance of the solution;

[0099] (2) A multi-projectile type calculation mode has been developed, which can store multiple firing tables and support multiple projectile type selections such as light, heavy, and armored weapons;

[0100] (3) In actual shooting, the target hit rate will be affected by many factors such as the shooter's shooting habits and the actual ballistic conditions. An automatic intelligent statistical model is used to learn the offset correction for each live ammunition shot, and the optimal offset of the impact point in the current state is calculated based on the model to achieve intelligent correction of the impact point.

[0101] (4) Added a new shooting table update module to support online shooting table update.

[0102] This specific embodiment is merely an explanation of the present invention and is not a limitation of the present invention. After reading this specification, those skilled in the art may make non-creative modifications to the present embodiment as needed. However, as long as they are within the scope of the claims of the present invention, they are protected by the patent law.

Claims

1. A rapid fire control solution method, characterized in that: The method comprises: In response to receiving the shell setting signal, it sends detection instructions to various sensor devices installed on the system equipment, and waits for the sensor devices to send back monitoring data; Determine the system working status based on the monitoring data sent back by all sensor devices, and determine the installation information and target position coordinates based on the monitoring data; Obtain historical shell data in the firing table, perform trajectory calculation based on the historical shell data, set element information and target position coordinates, and determine the trajectory calculation offset; specifically: Obtain at least three sets of continuous historical shell data about the target object closest to the current moment in the firing table, and calculate the trajectory solution offset of the target object based on the set element information and the Lagrange difference formula , which is expressed as follows: Among them Represent three sets of historical shell data respectively; independent variable Indicates the information of various elements; Establishing a trajectory correction compensation model based on the historical shell data, the set parameter information and the target position coordinates to determine the trajectory correction offset; The ballistic trajectory is corrected jointly according to the trajectory solution offset and the trajectory correction offset to determine the coordinates of the impact point.

2. The method according to claim 1, characterized in that The sensing device receiving the detection instruction includes at least a rangefinder, a temperature and pressure sensor, a wind speed sensor and an angle sensor, which are used to measure the distance between the launch point and the target, the current temperature and pressure data, the wind speed data and the azimuth data respectively.

3. The method according to claim 2, characterized in that The system working state is determined according to the monitoring data sent back by all the sensor devices, and the monitoring data is used to determine the set element information and the target position coordinates, including: In response to receiving the monitoring data sent back by all the sensor devices within the preset time, the target position coordinates and set parameter information at the current moment are generated; in response to not receiving the monitoring data sent back by all the sensor devices within the preset time, it is determined that the system data is abnormal.

4. The method according to any one of claims 1 to 3, characterized in that: The method of establishing a trajectory correction compensation model according to the historical shell data, the set element information and the target position coordinates to determine the trajectory correction offset includes: Obtain the historical shell data and construct a data point set P according to the time sequence of the data; Perform regression analysis based on polynomials to correct the offset and construct a coefficient matrix A of a k-order polynomial; The square sum loss function is used to characterize the square sum error L between the function value and the true value, and the least squares method is used to solve the parameter matrix; The trajectory correction compensation model is updated based on the parameter matrix, and the trajectory correction offset is calculated by inputting the set parameter information and the target position coordinates.

5. The method according to claim 4, characterized in that Data point set ; The k-order polynomial function is expressed as follows: ； Convert k-order polynomial function into matrix expression ; The matrix X represents the k-order polynomial matrix of the transformation, and Y represents the position matrix in the point set P; The sum of squared errors L is expressed as: When solving the parameter matrix, the derivative function is obtained based on the derivative calculation of matrix A as follows: Let the derivative function be 0, and the obtained parameter matrix is ​​expressed as: 。 6. A rapid fire control solution system, characterized in that: The rapid fire control solution method applied to any one of claims 1 to 5 comprises an FPGA, a storage module and an external sensor device, wherein the sensor device comprises a laser rangefinder, a temperature and pressure sensor, a wind speed sensor and an angle sensor; the FPGA is connected to the sensor device via an external interface; The FPGA includes a perception module, a soft core processor and a solution module, and the modules are interconnected through an AXI bus; the storage module is connected to the AXI bus through an API interface; The perception module is connected to the sensor device through an external interface to obtain monitoring data; the soft-core processor controls the operation of the system, controls data storage and parameter reading; the solution module performs fire control trajectory solution and trajectory correction compensation, and calculates the trajectory solution offset and trajectory correction offset.

7. The rapid fire control solution system according to claim 6, characterized in that: The sensing module includes a UART transceiver circuit and an I2C transceiver circuit, which are responsible for real-time detection of temperature, air pressure, distance, wind speed and angle setting parameters and reception of radiometer data.

8. The rapid fire control solution system according to claim 7, characterized in that: The storage module stores the main control software, the shooting table and the variable parameters, and receives the monitoring data collected by the perception module through the SPI interface and the AXI bus.

9. The rapid fire control solution system according to claim 8, characterized in that: The AXI bus is also connected to an external interface via a GPIO interface, and the soft-core processor receives terminal instructions and external control signals via the AXI bus and the GPIO interface, and sends solution data to the outside.

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