A 6-DOF dead reckoning system and method for distributed simulation

Abstract

The present invention discloses a 6-DOF dead reckoning system and method for distributed simulation, the system comprises a plurality of dead reckoning nodes, each dead reckoning node is connected with a local simulation node and a distributed simulation system network, the dead reckoning node comprises a dead reckoning coordinate calculation unit, a preliminary dead reckoning attitude matrix calculation unit, a revised dead reckoning attitude matrix calculation unit, a local simulation entity state basic data judgment and sending unit and a non-local simulation entity state basic data calculation and sending unit, the dead reckoning node calculates the 6-DOF track of the local simulation entity, if it exceeds a set threshold, the latest state basic data of the local simulation entity is sent to the distributed simulation system network; at the same time, the 6-DOF track of the non-local simulation entity is calculated and sent to the local simulation node. The present invention can effectively reduce the calculation amount of each dead reckoning node for performing 6-DOF dead reckoning of multiple simulation entities.

Description

Technical Field

[0001] The present invention belongs to the technical field of distributed simulation, and in particular relates to a 6-DOF dead reckoning system and method for distributed simulation. Background Art

[0002] Distributed simulation technology can make full use of existing simulation resources, integrate existing facilities, achievements, models and tools, supplement simulation elements, and realize highly complex simulation scenarios at low cost. In order to ensure the authenticity of entity movement and confrontation in complex scenarios, it is necessary to achieve accurate synchronization of entity position and posture. Each simulation node needs to send entity information frequently. As simulation scenarios become richer, the number of simulation nodes increases on a large scale, and the amount of data increases significantly, resulting in network congestion and increased transmission delays. Ultimately, data synchronization between simulation nodes is difficult to achieve, affecting system operation.

[0003] Dead Reckoning (DR) is usually used to reduce the amount of network transmission data while ensuring the synchronization of the entity's position and attitude. The dead reckoning node of each simulation node sends its own basic state data (position, attitude, etc.) at a lower frequency, and at the same time, it calculates the basic state data of other simulation nodes at a higher frequency based on the low-frequency basic state data received from other dead reckoning nodes.

[0004] When using the dead reckoning algorithm in a distributed simulation system, a simulation node generates basic state data of the simulation entity in real time and at a high frequency. The dead reckoning node connected to it is both the source of the basic state data of the local simulation entity and the receiver of the basic state data of the simulation entity running on other simulation nodes. In such a relationship, a dead reckoning node needs to perform dead reckoning calculations for multiple simulation entities, so the computational complexity of the dead reckoning method is the focus of this type of method.

[0005] For aircraft targets, it is necessary to perform track calculation on 6 degrees of freedom information (3 position parameters, 3 attitude parameters, usually Euler angles), which is more than the calculation amount of 2-3 degrees of freedom for ground and sea targets. Since the 3 Euler angles cannot usually be directly added and multiplied, the conventional method is complex and has high computational overhead when calculating the 3 attitude parameters, especially in the application of distributed simulation for large-scale simulation nodes. The conventional method consumes a lot of computing resources to process the 3 attitude parameters, which easily causes attitude calculation jams and simulation distortion. Summary of the invention

[0006] The object of the present invention is to provide a 6-DOF dead reckoning system and method for distributed simulation, which can effectively reduce the amount of calculation of 6-DOF dead reckoning of multiple simulation entities by each dead reckoning node.

[0007] In order to achieve the above-mentioned object, one aspect of the present invention provides a 6-DOF dead reckoning system for distributed simulation, comprising a plurality of dead reckoning nodes, each of which is connected to a local simulation node and a distributed simulation system network, and is used to receive basic state data of a local simulation entity from the local simulation node, and receive basic state data of a non-local simulation entity from the distributed simulation system network, and to calculate the 6-DOF trajectory of each simulation entity, wherein the basic state data includes a timestamp, location information of a centroid feature point, velocity information, and attitude Euler angles, and the dead reckoning node includes:

[0008] The estimated coordinate calculation unit calculates the estimated coordinates of the centroid feature point and the non-centroid feature point of the simulation entity at the current moment according to the speed information in the state basic data;

[0009] A preliminary estimated attitude matrix calculation unit, which calculates a preliminary estimated attitude matrix according to the estimated coordinates of the centroid feature point and the non-centroid feature point at the current moment;

[0010] A corrected dead reckoning attitude matrix calculation unit determines the uncertainty coefficient of the non-centroid feature point in the dead reckoning process according to the coordinates of the non-centroid feature point relative to the centroid feature point, and calculates the deviation value of the angle between the non-centroid feature point and the centroid feature point relative to 90°, determines the corrected rotation matrix according to the uncertainty coefficient and the deviation value, and obtains the corrected dead reckoning attitude matrix according to the corrected rotation matrix and the preliminary dead reckoning attitude matrix;

[0011] The local simulation entity state basic data judgment and sending unit obtains the corrected estimated coordinates of the non-center-of-mass feature points according to the corrected estimated posture matrix, calculates the real coordinates of the non-center-of-mass feature points at the current moment according to the position information of the center-of-mass feature points in the state basic data and the posture Euler angle, calculates whether the difference between the real coordinates of the center-of-mass feature points and the estimated coordinates of the center-of-mass feature points or the difference between the corrected estimated coordinates of the non-center-of-mass feature points and the real coordinates exceeds a threshold value, and if it exceeds the threshold value, sends the latest state basic data of the local simulation entity to the distributed simulation system network;

[0012] The non-local simulation entity state basic data calculation and sending unit calculates the non-local simulation entity's current attitude Euler angle according to the corrected estimated attitude matrix, and combines the non-local simulation entity's center of mass feature point estimated coordinates and the current attitude Euler angle with the speed information and timestamp in the received state basic data to form the non-local simulation entity's current state basic data, which are sent to the local simulation node.

[0013] Another aspect of the present invention provides a 6-DOF dead reckoning method for distributed simulation, using the above system to perform 6-DOF dead reckoning, comprising:

[0014] The estimated coordinate calculation step is to calculate the estimated coordinates of the centroid feature point and the non-centroid feature point of the simulation entity at the current moment according to the speed information in the state basic data;

[0015] A preliminary estimated attitude matrix calculation step, calculating the preliminary estimated attitude matrix according to the estimated coordinates of the centroid feature point and the non-centroid feature point at the current moment;

[0016] The step of calculating the corrected dead reckoning attitude matrix is ​​to determine the uncertainty coefficient of the non-centroid feature point in the dead reckoning process according to the coordinates of the non-centroid feature point relative to the centroid feature point, and calculate the deviation value of the angle between the non-centroid feature point and the centroid feature point relative to 90°, determine the corrected rotation matrix according to the uncertainty coefficient and the deviation value, and obtain the corrected dead reckoning attitude matrix according to the corrected rotation matrix and the preliminary dead reckoning attitude matrix;

[0017] The local simulation entity state basic data judgment and sending step obtains the corrected estimated coordinates of the non-center-of-mass feature points according to the corrected estimated posture matrix, calculates the real coordinates of the non-center-of-mass feature points at the current moment according to the position information of the center-of-mass feature points and the posture Euler angles in the state basic data, calculates whether the difference between the position information of the center-of-mass feature points and the estimated coordinates of the center-of-mass feature points or the difference between the corrected estimated coordinates of the non-center-of-mass feature points and the real coordinates exceeds a threshold value, and if it exceeds the threshold value, sends the latest state basic data of the local simulation entity to the distributed simulation system network;

[0018] The step of calculating and sending the basic state data of the non-local simulation entity is to calculate the Euler angle of the current state of the non-local simulation entity according to the corrected estimated attitude matrix, and to combine the estimated coordinates of the center of mass feature point of the non-local simulation entity and the Euler angle of the current state of the non-local simulation entity with the speed information and timestamp in the received basic state data to form the basic state data of the non-local simulation entity at the current moment, and send it to the local simulation node.

[0019] The 6-DOF dead reckoning system and method for distributed simulation according to the above aspects of the present invention can effectively reduce the amount of calculation required by each dead reckoning node to perform 6-DOF dead reckoning on multiple simulation entities. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings used in the description of the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work:

[0021] Figure 1 It is a connection diagram of a 6-DOF dead reckoning system for distributed simulation according to an embodiment of the present invention;

[0022] Figure 2 It is a flow chart of a 6-DOF dead reckoning method for distributed simulation according to an embodiment of the present invention;

[0023] Figure 3 It is a schematic diagram of the structure of a 6-DOF dead reckoning system for distributed simulation according to an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] An embodiment of the present invention provides a 6-DOF dead reckoning system for distributed simulation, such as Figure 1 As shown, the 6-DOF dead reckoning system of the embodiment of the present invention includes multiple dead reckoning nodes (dead reckoning nodes 1-n), each of which is connected to a local simulation node and a distributed simulation system network, receives basic state data of a local simulation entity sent at a high frequency by the local simulation node interconnected therewith, and deduces the 6-DOF track of the local simulation entity. If the data exceeds a set threshold, the latest basic state data of the local simulation entity is sent to the distributed simulation system network. At the same time, the dead reckoning node receives low-frequency basic state data of simulation entities (hereinafter referred to as non-local simulation entities) running on other simulation nodes from the distributed simulation system network, and deduces the 6-DOF track of the non-local simulation entity for simulation calculation or visual display of the local simulation node.

[0026] In the implementation manner of the present invention, the simulation nodes can be real aircraft (real people operating real aircraft), simulators (real people operating aircraft simulation models), computationally generated forces (AI operating aircraft simulation models) and situation display systems (real-time display of all entities in the distributed simulation system); simulation entities can be real aircraft and aircraft simulation models.

[0027] The dead reckoning node receives the basic status data sent by the local simulation node in real time, including timestamp (1 degree of freedom), position information (3 degrees of freedom), speed information (3 degrees of freedom), and attitude information (3 degrees of freedom). When the position and attitude 6 degrees of freedom information exceeds the threshold, the latest basic status data is sent to the distributed simulation system network.

[0028] At the same time, the dead reckoning node receives the basic state data sent by other simulation nodes in the distributed simulation system network in real time, and calculates the current position, attitude and 6-DOF information of the non-local simulation entity based on the basic state data of other simulation nodes. Together with the speed information in the latest package of basic state data of the simulation entity received by the dead reckoning node from the distributed simulation system network and the simulation logic timestamp corresponding to the basic state data, the basic state data of the simulation entity is composed and sent by the dead reckoning node to the local simulation node.

[0029] In the basic state data of local simulation entities sent by the local simulation node to the dead reckoning node and all basic state data sent and received between the dead reckoning node and the distributed simulation system network, the position information, velocity information and attitude Euler angles are all real data, and the timestamp is the simulation logic time of the basic state data; in the basic state data of non-local simulation entities sent by the dead reckoning node to the local simulation node, the position information and attitude Euler angles are calculated data, the velocity information is the real data received, and the timestamp is the simulation logic time of the basic state data.

[0030] The embodiment of the present invention further provides a 6-DOF dead reckoning method for distributed simulation, which uses the above-mentioned 6-DOF dead reckoning system to perform 6-DOF dead reckoning. Figure 2 As shown, the 6-DOF dead reckoning method according to the embodiment of the present invention includes steps S1 to S5.

[0031] Step S1 is a preliminary step for calculating the attitude matrix. In step S1, the estimated coordinates of the centroid feature point and the non-centroid feature point at the current moment are calculated based on the speed information in the state basic data. The acquisition of speed information is based on the most recent and second most recent two packets of state basic data sent by the dead reckoning node to the distributed simulation system network, as well as the relative coordinates of the non-centroid feature point and the centroid feature point.

[0032] In one embodiment, three feature points of the simulation entity are selected to describe the aircraft attitude. The aircraft attitude estimation is carried out based on the three feature points. The feature points are points fixed on the simulation entity. The three feature points are not collinear. Considering the computational efficiency, one feature point is the center of mass (the position estimation is carried out for the center of mass), and the lines connecting the other two non-center of mass feature points and the center of mass feature point are mutually orthogonal. For ease of understanding, in one embodiment, one feature point is set in front of the simulation entity, and the line connecting it with the center of mass can be used as the x-axis of the aircraft coordinate system. One feature point is set on the right side of the simulation entity, and the line connecting it with the center of mass can be used as the y-axis of the aircraft coordinate system. Compared with the traditional aircraft attitude estimation method based on Euler angles, the computational complexity is lower and the computational efficiency is higher.

[0033] In this embodiment, step S1 further includes steps S11 to S13.

[0034] Step S11, calculate the estimated coordinates of the centroid feature point at the current moment :

[0035]

[0036] The subscript 0 represents the most recent information (the most recent packet of state basic data sent by the dead reckoning node to or received from the distributed simulation system network), the subscript t represents dead reckoning, and the subscript c represents the centroid. Indicates the velocity information at the most recent moment (3 degrees of freedom), Indicates the centroid coordinates (position information) at the most recent moment, Indicates the difference between the most recent timestamp and the current time. The value is a positive number.

[0037] Step S12: Calculate the estimated coordinates of the feature point in front at the current moment :

[0038]

[0039] in, , represents the estimated speed of the feature point ahead at the current moment, the subscript -1 represents the information at the next most recent moment (the next most recent packet of state basic data sent by the dead reckoning node to the distributed simulation system network (used to estimate local simulation node information) or received from the distributed simulation system network (used to estimate non-local node information)), the estimated coordinates of the feature point ahead at the latest moment , the estimated coordinates of the feature point in front of the next closest moment , , , They represent the estimated coordinates of the front feature point at the next closest moment, the coordinates of the centroid feature point, and the rotation matrix, respectively. Indicates the difference between the most recent time and the next most recent time, and the value is a positive number.

[0040] in Represents the rotation matrix corresponding to the attitude Euler angle in the latest packet of state basic data sent by the dead reckoning node to or received from the distributed simulation system network.

[0041]

[0042] in The Euler angles of yaw, pitch, and roll; Represents a 3*1 vector, which indicates the coordinates of the feature point in front (x direction) relative to the center of mass feature point in the aircraft's own coordinate system.

[0043] Step S13, calculate the estimated coordinates of the right feature point at the current moment :

[0044]

[0045] in , represents the estimated speed of the right feature point at the current moment, the subscript 0 and -1 represent the values ​​corresponding to the most recent and second most recent moments in the sent information, and the estimated coordinates of the right feature point at the most recent moment ,in It is a 3*1 vector, which indicates the coordinates of the feature point on the right (y direction) relative to the center of mass in the aircraft's own coordinate system. The coordinates of the feature point on the right at the next closest moment are calculated. .

[0046] Step S2 is a preliminary estimated posture matrix calculation step. In step S2, the preliminary estimated posture matrix at the current moment is calculated based on the estimated coordinates of the centroid feature point and the non-centroid feature point at the current moment. During the calculation process, since the lines connecting the two non-centroid feature points and the centroid feature point cannot always remain orthogonal, orthogonal processing is required.

[0047] In this embodiment, step S2 further includes steps S21 to S23.

[0048] Step S21, calculate the first column of the matrix:

[0049]

[0050] Step S22, calculate the second column of the matrix:

[0051] ,in represents the vector inner product,

[0052]

[0053] Step S23, calculate the third column of the matrix:

[0054]

[0055] Step S3 is a step of calculating the corrected estimated attitude matrix. In step S3, the corrected estimated attitude matrix at the current moment is calculated. The orthogonal processing in step S2 is performed based on one of the non-centroid feature points (such as the feature point in front of the x-axis), but this feature point may also deviate during the track calculation process. For this, a deviation correction method based on uncertainty allocation is adopted, that is, the uncertainty coefficient q in the track calculation process is determined according to the positions of the two non-centroid feature points. After each track calculation, the deviation value of the angle between the two non-centroid feature points and the centroid feature point relative to 90° is calculated. , according to the uncertainty coefficient q and the deviation value Determine the corrected rotation matrix , the rotation matrix will be corrected Acting on the preliminary estimated attitude matrix The corrected estimated attitude matrix is ​​obtained .

[0056] In this embodiment, step S3 further includes steps S31 to S34.

[0057] Step S31, calculate the uncertainty allocation coefficient (This value is a system constant and does not change over time):

[0058]

[0059] Step S32, calculating the deviation angle :

[0060]

[0061] Step S33, calculate the corrected rotation matrix :

[0062]

[0063] Step S34, calculate the corrected estimated attitude matrix at the current moment :

[0064]

[0065] Step S4 is a step of judging and sending the basic data of the local simulation entity state. In step S4, the corrected estimated coordinates of the feature point at the current moment are calculated. , , according to the corrected estimated attitude matrix , we can get the corrected estimated coordinates of the feature points in front and on the right; calculate the real coordinates of the feature points at the current moment , According to the Euler angles in the state basic data sent by the local simulation node, the real coordinates of the feature points on the simulation entity can be obtained; the difference between the corrected estimated coordinates and the real coordinates of the feature points is calculated to determine whether it exceeds the threshold. If it exceeds the threshold, the state basic data of the local simulation entity is sent to the distributed simulation system network.

[0066] In this embodiment, step S4 further includes steps S41 to S43.

[0067] Step S41, calculate the corrected coordinates of the front feature point at the current moment :

[0068]

[0069] Calculate the corrected coordinates of the right feature point at the current moment :

[0070]

[0071] Step S42: Calculate the real coordinates of the feature point in front at the current moment :

[0072]

[0073] The subscript n indicates the true value, Represents the rotation matrix corresponding to the attitude Euler angle in the state basic data sent by the local simulation node. Represents the real coordinates of the centroid feature point, corresponding to the position information in the state basic data.

[0074] Calculate the real coordinates of the right feature point at the current moment :

[0075]

[0076] Step S43, judging whether it is necessary to update and send the latest state basic data, the criterion is whether the deviation between the corrected estimated coordinates of the feature point and the current real coordinates of the feature point exceeds a threshold, that is:

[0077]

[0078] in represents the two-norm, Indicates the deviation threshold of the centroid, front feature point, and right feature point

[0079] If all the above three inequalities are true, there is no need to update and send the latest state basic data. Otherwise, that is, any one of the above three inequalities is not true, the dead reckoning node needs to send the latest state basic data of the local simulation entity to the distributed simulation system network.

[0080] The above steps S1 to S4 are the process of the dead reckoning node calculating the 6-DOF trajectory of the local simulation entity and sending the latest state basic data to the distributed simulation system network. In step S5, the dead reckoning node also pushes the 6-DOF trajectory of the non-local simulation entity based on the last packet of state basic data of the non-local simulation entity received from the distributed simulation system network and sends it to the local simulation node. It should be specially noted that the execution order of step S4 and step S5 is not limited to the order of front and back, and the two can be executed at the same time. The two steps are divided into two steps only to facilitate the explanation of the different processes of local simulation node information calculation and non-local simulation node information calculation.

[0081] Step S5 is a step of calculating and sending the basic data of the state of the non-local simulation entity. In step S5, the Euler angle of the attitude of the non-local simulation entity at the current moment is calculated, and the corrected attitude matrix obtained in step S3 is calculated. The Euler angle of the current posture of the simulation entity can be obtained. The coordinates of the centroid feature point in step S1 are calculated That is, the current position information, the speed information in the latest package of state basic data of the simulation entity received by the track calculation node from the distributed simulation system network, and the simulation logical time (timestamp) corresponding to the state basic data, which constitute the state basic data of the simulation entity and are sent by the track calculation node to the local simulation node.

[0082] In step S5, the Euler angle of the posture of the non-local simulation entity at the current moment is calculated as follows:

[0083]

[0084] in, , , The current moment The Euler angles of yaw, pitch, and roll. The basic state data has been generated, including the current time (1 parameter), current position information (3 parameters), current speed information (3 parameters), and current posture Euler angle (3 parameters).

[0085] Corresponding to the various steps of the 6-DOF dead reckoning method of the embodiment of the present invention, each dead reckoning node of the 6-DOF dead reckoning system of the embodiment of the present invention is as follows: Figure 3 Shown include:

[0086] The estimated coordinate calculation unit 101 calculates the estimated coordinates of the centroid feature point and the non-centroid feature point of the simulation entity at the current moment according to the speed information in the state basic data;

[0087] A preliminary estimated posture matrix calculation unit 102 calculates a preliminary estimated posture matrix according to the estimated coordinates of the centroid feature point and the non-centroid feature point at the current moment;

[0088] The corrected dead reckoning attitude matrix calculation unit 103 determines the uncertainty coefficient of the non-centroid feature point in the dead reckoning process according to the coordinates of the non-centroid feature point relative to the centroid feature point, and calculates the deviation value of the angle between the non-centroid feature point and the centroid feature point relative to 90°, determines the corrected rotation matrix according to the uncertainty coefficient and the deviation value, and obtains the corrected dead reckoning attitude matrix according to the corrected rotation matrix and the preliminary dead reckoning attitude matrix;

[0089] The local simulation entity state basic data judgment and sending unit 104 obtains the corrected estimated coordinates of the non-center-of-mass feature points according to the corrected estimated posture matrix, calculates the real coordinates of the non-center-of-mass feature points at the current moment according to the position information of the center-of-mass feature points and the posture Euler angles in the state basic data, calculates whether the difference between the real coordinates of the center-of-mass feature points and the estimated coordinates of the center-of-mass feature points or the difference between the corrected estimated coordinates of the non-center-of-mass feature points and the real coordinates exceeds a threshold value, and if it exceeds the threshold value, sends the latest state basic data of the local simulation entity to the distributed simulation system network;

[0090] The non-local simulation entity state basic data calculation and sending unit 105 calculates the posture Euler angle of the non-local simulation entity at the current moment according to the corrected estimated posture matrix, and combines the estimated coordinates of the center of mass feature point of the non-local simulation entity and the posture Euler angle of the current moment with the speed information and timestamp in the received state basic data to form the state basic data of the non-local simulation entity, and sends it to the local simulation node.

[0091] The specific embodiment of the 6-DOF dead reckoning system of this embodiment can refer to the definition of the 6-DOF dead reckoning method above, which will not be repeated here. Each unit in the above 6-DOF dead reckoning system can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above units can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above units.

[0092] In summary, in the 6-DOF dead reckoning system and method for distributed simulation of the embodiment of the present invention, each dead reckoning node applies the 6-DOF dead reckoning method to estimate the position and attitude of the local simulation entity, and determines whether to send the basic state data of the local simulation entity. At the same time, based on the low-frequency basic state data received from other dead reckoning nodes, the position and attitude of other simulation entities are estimated to generate high-frequency basic state data. Compared with other methods, the present invention has advantages in the integrity of the target 6-DOF information (3 position information parameters, 3 attitude Euler angle parameters) and the computational complexity of attitude information (compared with conventional attitude parameter calculation methods, such as quaternions, complex matrix operations, etc.).

[0093] The above description is only by way of illustration of certain exemplary embodiments of the present invention. It is undoubted that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A 6-DOF dead reckoning system for distributed simulation, characterized in that: The invention comprises a plurality of dead reckoning nodes, each of which is connected to a local simulation node and a distributed simulation system network, and is used to receive basic state data of a local simulation entity from the local simulation node, and receive basic state data of a non-local simulation entity from the distributed simulation system, and to calculate a 6-DOF track of each simulation entity, wherein the basic state data comprises a timestamp, position information of a centroid feature point, velocity information, and attitude Euler angles, and the dead reckoning node comprises: The estimated coordinate calculation unit calculates the estimated coordinates of the centroid feature point and the non-centroid feature point of the simulation entity at the current moment according to the speed information in the state basic data; A preliminary estimated attitude matrix calculation unit, which calculates a preliminary estimated attitude matrix according to the estimated coordinates of the centroid feature point and the non-centroid feature point at the current moment; A corrected dead reckoning attitude matrix calculation unit determines the uncertainty coefficient of the non-centroid feature point in the dead reckoning process according to the coordinates of the non-centroid feature point relative to the centroid feature point, and calculates the deviation value of the angle between the non-centroid feature point and the centroid feature point relative to 90°, determines the corrected rotation matrix according to the uncertainty coefficient and the deviation value, and obtains the corrected dead reckoning attitude matrix according to the corrected rotation matrix and the preliminary dead reckoning attitude matrix; The local simulation entity state basic data judgment and sending unit obtains the corrected estimated coordinates of the non-center-of-mass feature points according to the corrected estimated posture matrix, calculates the real coordinates of the non-center-of-mass feature points at the current moment according to the position information of the center-of-mass feature points in the state basic data and the posture Euler angle, calculates whether the difference between the real coordinates of the center-of-mass feature points and the estimated coordinates of the center-of-mass feature points or the difference between the corrected estimated coordinates of the non-center-of-mass feature points and the real coordinates exceeds a threshold value, and if it exceeds the threshold value, sends the latest state basic data of the local simulation entity to the distributed simulation system network; The non-local simulation entity state basic data calculation and sending unit calculates the non-local simulation entity's current attitude Euler angle according to the corrected estimated attitude matrix, and combines the non-local simulation entity's center of mass feature point estimated coordinates and the current attitude Euler angle with the speed information and timestamp in the received state basic data to form the non-local simulation entity's current state basic data, which are sent to the local simulation node.

2. A 6-DOF dead reckoning method for distributed simulation, characterized in that: Using the system of claim 1 to perform 6-DOF dead reckoning, comprising: The estimated coordinate calculation step is to calculate the estimated coordinates of the centroid feature point and the non-centroid feature point of the simulation entity at the current moment according to the speed information in the state basic data; A preliminary estimated attitude matrix calculation step, calculating the preliminary estimated attitude matrix according to the estimated coordinates of the centroid feature point and the non-centroid feature point at the current moment; The step of calculating the corrected dead reckoning attitude matrix is ​​to determine the uncertainty coefficient of the non-centroid feature point in the dead reckoning process according to the coordinates of the non-centroid feature point relative to the centroid feature point, and calculate the deviation value of the angle between the non-centroid feature point and the centroid feature point relative to 90°, determine the corrected rotation matrix according to the uncertainty coefficient and the deviation value, and obtain the corrected dead reckoning attitude matrix according to the corrected rotation matrix and the preliminary dead reckoning attitude matrix; The local simulation entity state basic data judgment and sending step obtains the corrected estimated coordinates of the non-center-of-mass feature points according to the corrected estimated posture matrix, calculates the real coordinates of the non-center-of-mass feature points at the current moment according to the position information of the center-of-mass feature points and the posture Euler angles in the state basic data, calculates whether the difference between the position information of the center-of-mass feature points and the estimated coordinates of the center-of-mass feature points or the difference between the corrected estimated coordinates of the non-center-of-mass feature points and the real coordinates exceeds a threshold value, and if it exceeds the threshold value, sends the latest state basic data of the local simulation entity to the distributed simulation system network; The step of calculating and sending the basic state data of the non-local simulation entity is to calculate the Euler angle of the current state of the non-local simulation entity according to the corrected estimated attitude matrix, and to combine the estimated coordinates of the center of mass feature point of the non-local simulation entity and the Euler angle of the current state of the non-local simulation entity with the speed information and timestamp in the received basic state data to form the basic state data of the non-local simulation entity at the current moment, and send it to the local simulation node.

3. The method according to claim 2, characterized in that The non-centroid feature points include a front feature point set in front of the simulation entity and a right feature point set on the right side of the simulation entity. The line connecting the front feature point and the centroid feature point serves as the x-axis of the aircraft coordinate system, and the line connecting the right feature point and the centroid feature point serves as the y-axis of the aircraft coordinate system.

4. The method according to claim 3, characterized in that The step of calculating the estimated coordinates comprises: Calculate the estimated coordinates of the centroid feature point at the current moment : ， in, It indicates the speed information in the latest packet of state basic data sent by the dead reckoning node to or received from the distributed simulation system network. Represents the coordinates of the centroid feature point in the basic data of this state, Indicates the difference between the timestamp in the basic data of the state and the current time; Calculate the estimated coordinates of the feature point in front at the current moment : ， in, , , , Indicates the estimated speed of the feature point ahead at the current moment. Represents the rotation matrix corresponding to the attitude Euler angle in the latest packet of state basic data sent by the dead reckoning node to or received from the distributed simulation system network. Indicates the estimated coordinates of the feature point in front at the most recent time. It is a 3*1 vector, which indicates the coordinates of the front feature point relative to the center of mass feature point in the aircraft coordinate system. , , They represent the estimated coordinates of the front feature point at the next closest moment, the coordinates of the centroid feature point, and the rotation matrix, respectively. Indicates the difference between the most recent time and the next most recent time; Calculate the estimated coordinates of the feature point on the right at the current moment : ， in , , , Indicates the estimated speed of the feature point on the right at the current moment, Indicates the estimated coordinates of the right feature point at the most recent time. It is a 3*1 vector, which indicates the coordinates of the right feature point relative to the center of mass feature point in the aircraft coordinate system. Indicates the estimated coordinates of the right feature point at the next closest time.

5. The method according to claim 4, characterized in that The preliminary estimation posture matrix calculation step comprises: Calculate the initial estimated attitude matrix Column 1: ； Calculate the initial estimated attitude matrix Column 2: ,in represents the vector inner product, ； Calculate the initial estimated attitude matrix Column 3: 。 6. The method according to claim 5, characterized in that The step of calculating the corrected and estimated attitude matrix comprises: Calculate the uncertainty allocation coefficient : Calculate the deviation angle : Calculate the corrected rotation matrix : Calculate the corrected dead reckoning attitude matrix at the current moment : 。 7. The method according to claim 6, characterized in that The local simulation entity state basic data judgment and sending steps include: Calculate the corrected coordinates of the feature point in front at the current moment : ， Calculate the corrected coordinates of the right feature point at the current moment : ； Calculate the real coordinates of the feature point in front at the current moment : ， in, Represents the rotation matrix corresponding to the attitude Euler angle in the state basic data sent by the local simulation node. Represents the real coordinates of the centroid feature point, corresponding to the position information of the centroid feature point in the state basic data, Calculate the real coordinates of the right feature point at the current moment : ； When any of the following three inequalities is not true, the latest state basic data of the local simulation entity is sent to the distributed simulation system network: in, represents the two-norm, , , They represent the deviation thresholds of the centroid feature point, the front feature point, and the right feature point respectively.

8. The method according to claim 7, characterized in that In the step of calculating and sending the basic data of the state of the non-local simulation entity, the Euler angle of the posture of the non-local simulation entity at the current moment is calculated as follows: ， in, , , The current moment The Euler angles of yaw, pitch, and roll.

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