A method for data communication of a sight

Abstract

The present invention discloses a method for data communication of a telescopic sight, which relates to the technical field of data communication of telescopic sights. The method includes constructing a virtual network and updating it to an encrypted virtual network. Each virtual subnet reserves a spectrum channel as an emergency spectrum channel. Each of the telescopic sight devices collects environmental images in real time, processes the images collected by the telescopic sight using the grid method, establishes a three-dimensional terrain model near the nodes and performs swelling processing, optimizes the network node allocation using an improved bat algorithm, and obtains the optimal paths of all nodes in the virtual subnet according to the local optimal path solution. By encrypting the network composed of telescopic sight devices and using frequency hopping technology, the communication process of the telescopic sight is made secure in the present invention. The improved dynamic network node allocation algorithm enables the telescopic sight communication to perform group collaboration and intercommunication, dynamic component network, priority information screening, fast real-time transmission adjustment, and allocate node positions in accordance with the three-dimensional actual terrain.

Description

Technical Field

[0001] The present invention relates to the technical field of aiming scope data communication, and in particular to a wireless data communication method. Background Art

[0002] An aiming scope is an important and inseparable part of modern weapons, and it has become an important means to improve the combat capabilities of weapons, especially all-weather combat capabilities. The mobile ad-hoc network of aiming scopes in a military environment not only has problems such as a dynamically changing topological structure and limited wireless transmission bandwidth, but also has requirements for high reliability, high security, and high real-time performance.

[0003] Currently, the Chinese utility model patent with the application number 202023012868.3 discloses a digital multi-functional civilian night vision aiming scope movement mechanism. Although the aiming scope can support wireless video transmission and has the characteristic of low latency, this aiming scope does not have the ability to collaborate and communicate within a group, dynamically form a network, nor does it have security, and it does not have the capabilities of fast real-time transmission and adjustment required by military communication technologies, nor the ability to plan the aiming scope user allocation and priority information screening according to the three-dimensional terrain. Summary of the Invention

[0004] The technical problem solved by the present invention is that in the related art, the aiming scope cannot perform group collaboration and communication, dynamically form a network, securely transmit information, quickly and real-time transmit and adjust, nor plan the aiming scope user allocation and priority information screening according to the three-dimensional terrain.

[0005] To solve the above technical problems, the present invention provides the following technical solution: An aiming scope data communication method, comprising the following steps:

[0006] Step S1: Construct a virtual network, the virtual network includes multiple virtual subnets, each virtual subnet includes multiple nodes, enable encryption certificates on each virtual subnet, and update the virtual network to an encrypted virtual network, where the nodes are aiming scope devices;

[0007] Step S2: Reserve a spectrum channel as an emergency spectrum channel for each virtual subnet, and generate a three-dimensional node label of the aiming scope according to the node data;

[0008] Step S3: Each of the aiming scope devices real-time collects environmental images, processes the images collected by the aiming scope using the grid method, establishes a three-dimensional terrain model near the node and performs swelling processing, uploads the swollen three-dimensional terrain model to the virtual subnet where the aiming scope device is located, and shares the swollen three-dimensional terrain model with the remaining virtual subnets;

[0009] Step S4: Optimize the network node allocation using an improved bat algorithm, and the improvement of the bat algorithm includes:

[0010] Initialize the parameters of the sight and the spectrum allocation of the nodes. Use the total network loss as the evaluation criterion for the algorithm fitness, and calculate the initial fitness of the algorithm.

[0011] Horizontally decompose the three-dimensional topographic map from the lowest point to the highest point into multiple horizontal layers. The surface curve is represented as surface points on the horizontal layer. Select the surface nodes in each layer as path nodes according to the nearest nodes. Obtain the locally optimal path solution for node allocation based on the set of path nodes on all the horizontal layers, and obtain the optimal paths of all nodes of the virtual subnet according to the locally optimal path solution.

[0012] Step S5: Transmit information using frequency hopping technology. Analyze the frequency hopping pattern in the frequency hopping sequence, use Huffman coding to compress and encode the frequency hopping pattern, and compress the frequency hopping sequence into a shorter encoded sequence.

[0013] Step S6: When a node is damaged or abnormal, release the node and recover the key.

[0014] As a preferred solution of the present invention, step S1 specifically includes:

[0015] Enter each sight device into the network controller, install an encryption certificate for each sight device respectively, and enter the fingerprints of the users of each sight device into their respective encryption certificates. The encryption certificates are unique.

[0016] Create a virtual network in the network controller. The virtual network includes multiple virtual subnets, and each virtual subnet includes multiple sight devices. Enable the encryption certificates on each virtual subnet and update it to an encrypted virtual network.

[0017] When any sight device communicates with another sight device on the same subnet through a spectrum channel, it is automatically encrypted under the control of the encryption certificate.

[0018] As a preferred solution of the present invention, step S2 specifically includes:

[0019] The users of the sight devices in the same virtual subnet send information through the spectrum channel, and evaluate the priority level of the information to be sent. The initial priority level of each node is 0 level, denoted as flag = 0. The user holding the sight has the right to increase the node priority level by 2 levels, and the global commander of the virtual network has the right to increase the node priority level by 1 level.

[0020] The larger the flag, the higher the priority level and the higher the urgency of the information. The lowest priority level is 0 level, indicating ordinary transmission without priority. The highest priority level is 3 level, indicating that the information expected to be sent by the sight has the highest urgency and uses the emergency spectrum channel.

[0021] Taking the number of the virtual subnets as a variable, the spectrum quantity is allocated to each virtual subnet by using the Stackelberg game method;

[0022] The telescopic sight users who need to send emergency information preempt the emergency spectrum channel according to the priority level by using the multi-level feedback queue scheduling algorithm.

[0023] As a preferred solution of the present invention, the generation of the node label includes:

[0024] Each node sends node data to the nodes included in its respective virtual subnet. The node data includes node coordinates and the cost of expected transmission information. The distance between the node and its neighboring nodes and the cost of expected transmission information are weighted and calculated to obtain the transmission loss. Each node generates a node label and stores it in the telescopic sight memory;

[0025] The node label contains node coordinates, expected transmission cost and transmission loss. The format of the node label is a generalized list, and its mathematical expression is:

[0026] M((x,y,z),b,c)

[0027] where (x,y,z) are the three-dimensional coordinates of the location of the telescopic sight, b is the expected transmission cost, and c is the transmission loss.

[0028] As a preferred solution of the present invention, the step S4 specifically includes:

[0029] The initialization of the spectrum allocation process of the nodes includes:

[0030] The nodes are grouped according to the bandwidth of the spectrum channels applicable to the nodes. One node is applicable to greater than or equal to one spectrum channel, and a matrix of the nodes applicable to each spectrum channel is obtained. The columns of the matrix are node numbers, and the rows of the matrix are the spectrums of the spectrum channels. The applicable spectrum channels corresponding to the nodes are marked as A in the matrix, and the remaining spectrum channels are marked as B;

[0031] The loss value threshold of the node in the spectrum channel is set to a. If the transmission loss value of the node in the spectrum channel is greater than a, the spectrum channel corresponding to the node is marked as B in the matrix;

[0032] The matrix is converted into an adjacency list, and the adjacency list is traversed in depth first. Each row of the adjacency list represents the nodes applicable to the spectrum channel. When the data of a certain row of the adjacency list is traversed in depth first, the priority of each node is queried and compared with the priority of its previous node. If the priority of the node is greater than the priority of the previous node, the node and its previous node are exchanged. The operation is repeated until the priority of the node is no longer greater than the priority of the previous node, and a new adjacency list is obtained;

[0033] The first column of the adjacency list is the node with the highest priority in each spectrum channel, and the priority of the nodes decreases as we move backward. Re - perform a depth - first traversal on the new adjacency list. When the depth - first traversal reaches a node with a priority greater than or equal to level 2, stop the backward depth - first traversal. Archive the historical depth - first traversal point in the spectrum channel and perform a depth - first traversal on the next spectrum channel. If the depth - first traversal reaches the same node that has been depth - first traversed before, delete the node and perform a backward depth - first traversal. After the depth - first traversal of the last spectrum channel, start querying the node priorities from the historical depth - first traversal point of the first spectrum channel where the depth - first traversal started. If the depth - first traversal reaches a node with a priority of level 1, archive the historical depth - first traversal point in the spectrum channel and perform a depth - first traversal on the next spectrum channel. If the depth - first traversal reaches the same node that has been depth - first traversed before, delete the node and perform a backward depth - first traversal. After the depth - first traversal of the last spectrum channel, start querying the node priorities from the historical depth - first traversal point of the first depth - first traversed spectrum channel, and delete the duplicate nodes among the remaining nodes to obtain the adjacency list of the node distribution.

[0034] As a preferred embodiment of the present invention, after the nodes share node labels with neighboring nodes several times, the node labels of all nodes in the virtual subnet are obtained. A triple - table containing all node labels is generated in the memory of the sighting device. When a node moves or the transmission loss changes, the node updates its node label and shares it with its neighboring nodes. Each node in the virtual network quickly iteratively refreshes the triple - table and comprehensively considers the refreshed triple - table and the priorities of each refreshed node to refresh the spectrum allocation situation.

[0035] As a preferred embodiment of the present invention, the surface points are the feasibility sets of the nodes. The surface points form a node graph at each horizontal layer. The initialized nodes are the initial shortest distances. All nodes are vertically mapped onto all the horizontal layers. Query all nodes from the highest horizontal layer to the lowest horizontal layer, and sequentially query the distances to the neighboring nodes of each node. Find the nearest neighbor of each node, and insert the surface nodes selected from each layer as path nodes according to the nearest neighbor. Obtain the locally optimal path solution for node allocation based on the set of path nodes on all the horizontal layers. Update the fitness according to the locally optimal path solution, adjust the parameters and update the fitness. When the fitness is the smallest, decide whether to adjust or update the position of the node and the spectrum channel of the frequency it is in according to the new fitness and probability. When the fitness is the smallest, judge whether the combination of all locally optimal solutions can form a global path solution, and finally obtain the optimal path of all nodes in the virtual subnet;

[0036] The adjusted parameters are and .

[0037] As a preferred solution of the present invention, the data expression of the total network loss is:

[0038]

[0039] where S is the total network loss value, the L() function is the Euclidean distance formula, is the predicted transmission loss value regarding distance between node and node , is the mathematical expectation of the transmission loss between all nodes, is the horizontal coordinate of the node label;

[0040] The fitness is used to evaluate the quality of each individual in the population, and the mathematical expression of the fitness is:

[0041]

[0042] where is the fitness, is the total network loss value, is an infinitesimal quantity, is the node, is the set of surface points;

[0043] The improved bat algorithm updates the node positions, user movement speeds, and transmission losses:

[0044]

[0045]

[0046]

[0047] where is the bandwidth frequency at which the i-th node can use the spectrum channel, is the maximum frequency, is the minimum frequency, is a random number, and are the user movement speeds of the i-th node at times t and t - 1 respectively, is the global optimal solution, and are the positions of the i-th node at times t and t - 1 respectively;

[0048] The mathematical expression for updating the local search is:

[0049]

[0050] where is a random value, x [0, 1], is the average loss value at the t time step, is the current global optimal solution. As the iteration progresses, the loss value also changes:

[0051]

[0052] Among them, and are the estimated loss values of the i-th node at times t and t - 1, is a parameter variable and > 0. The mathematical expression of the probability is:

[0053]

[0054] Among them, P is the probability, is the priority of the i-th node, is a constant and < 1, and t is the time;

[0055] When traversing the query node distance hierarchically, a priority queue is established to store candidate nodes, and the entry point is added to the priority queue. Each time, the node closest to the query point is taken out from the priority queue, and its neighbor nodes are queried. If the neighbor nodes have not been traversed by the hierarchy, they are added to the priority queue. Finally, the distances between the query point and all candidate nodes are calculated, and the distances are sorted to select the K nearest neighbor nodes of the query point;

[0056] If the combination of all local optimal solutions cannot form a global path solution, the parameters are readjusted to update the fitness until the initial set number of iterations is reached;

[0057] The process of the iteration includes adjusting parameters and updating fitness.

[0058] As a preferred solution of the present invention, the bat algorithm simultaneously provides real-time dynamic judgment by emitting infrared rays to determine whether there are active organisms near the location where the telescopic sight device is located. If such organisms appear, a warning is issued to the user of the telescopic sight device;

[0059] A flag value sign is set, and the initial sign value is 0. The user holding the telescopic sight device marks the coordinates including:

[0060] When setting the gathering location, the sign value of the coordinates of the gathering location is set to 1;

[0061] When a dangerous location is found, the sign value of the coordinates where the dangerous location is found is set to -1.

[0062] As a preferred embodiment of the present invention, step S6 specifically includes:

[0063] The method for releasing a node includes:

[0064] Delete the node to be released from all lists and the network where it exists, keep the spectrum allocation unchanged, and connect the neighbor nodes of the node in the network.

[0065] Advantages of the present invention: By encrypting the network composed of telescopic sight devices, the communication process of the telescopic sight is made secure. The improved network node dynamic allocation algorithm enables the telescopic sight communication to perform group collaboration and intercommunication, dynamic component networking, priority information screening, fast real-time transmission and adjustment. Combined with the three-dimensional topographic map, the telescopic sight can allocate node positions according to the three-dimensional actual terrain. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 It is a schematic diagram of the basic process of a telescopic sight data communication method provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0067] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following detailed description of the specific embodiments of the present invention is made in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all embodiments.

[0068] Embodiment 1, referring to Figure 1 This is an embodiment of the present invention, providing a telescopic sight data communication method, including the following steps:

[0069] Step S1: Construct a virtual network, the virtual network includes multiple virtual subnets, each virtual subnet includes multiple nodes, enable encryption certificates on each virtual subnet, and update the virtual network to an encrypted virtual network, where the nodes are telescopic sight devices;

[0070] Step S2: Reserve a spectrum channel as an emergency spectrum channel for each virtual subnet, and generate a three-dimensional node label for the telescopic sight according to the node data;

[0071] Step S3: Each telescopic sight device collects environmental images in real time, processes the collected images of the telescopic sight using the grid method, establishes a three-dimensional terrain model near the node and performs swelling processing, uploads the swollen three-dimensional terrain model to the virtual subnet where the telescopic sight device is located, and shares the swollen three-dimensional terrain model with the other virtual subnets;

[0072] Step S4: Optimize the network node allocation using an improved bat algorithm, and the improvement of the bat algorithm includes:

[0073] Initialize the parameters of the sight and the spectrum allocation of the nodes. Take the total network loss as the evaluation criterion for the algorithm fitness, and calculate the initial fitness of the algorithm.

[0074] Horizontally decompose the three-dimensional topographic map from the lowest point to the highest point into multiple horizontal layers. The surface curve is represented as surface points on the horizontal layer. According to the nearest nodes, select the surface nodes in each layer and insert them as path nodes. Obtain the locally optimal path solution for node allocation based on the set of path nodes on all the horizontal layers, and obtain the optimal path for all nodes of the virtual subnet according to the locally optimal path solution.

[0075] Step S5: Transmit information using frequency hopping technology. Analyze the frequency hopping patterns in the frequency hopping sequence, and use Huffman coding to compress and encode the frequency hopping patterns to compress the frequency hopping sequence into a shorter encoded sequence.

[0076] Step S6: When a node is damaged or abnormal, release the node and recover the key.

[0077] The present invention encrypts the network composed of sight devices, making the communication process of the sight secure. The improved dynamic network node allocation algorithm enables the sight communication to perform group collaboration and interconnection, dynamic component network, priority information screening, fast real-time transmission and adjustment. Combined with the three-dimensional topographic map, the sight can allocate node positions according to the three-dimensional actual terrain; through frequency hopping processing after Huffman coding compression of the signal, the signal is converted into a pseudo-noise state, which can make the signal converge faster, occupy less memory, and the communication is more secure.

[0078] After establishing the initial environment model using the grid method, expand the initial environment model. Give a larger expansion unit in the relatively dangerous terrain area and a smaller expansion unit in the relatively flat and safe terrain area, which can not only ensure the safety of navigation but also ensure the best fit to the original terrain.

[0079] The expansion process includes:

[0080] Cut the entire environment on the XOY plane, divide it into different numbers of environment blocks according to different scales. The mathematical expression for the number of environment blocks after cutting is:

[0081]

[0082] where, and represent the scales of cutting in the length axis direction and the width axis direction respectively, is the number of environment blocks after cutting, and the set of environment blocks after cutting is ;

[0083] Calculate the ruggedness of each environmental block. The calculation of ruggedness mainly depends on the maximum slope of each environmental block. For the calculation of the maximum slope, two obstacle grids with the maximum D value and the minimum D value in each environmental block are taken, and then the slope is calculated according to the positions of the two grids in the XOY plane. Denote the grid with the maximum D value in the environmental block as , and the grid with the minimum value as . The specific mathematical expression for the calculation method is:

[0084]

[0085] Obtain a set of ruggedness values for an environmental block as ;

[0086] According to the different ruggedness values, divide different threat levels for each environmental block and perform inflation with different units. The inflation unit is larger in areas with high ruggedness and smaller in areas with low ruggedness. The mathematical expression for the inflation scale is:

[0087]

[0088] Thus, the inflation scale corresponding to each environmental block can be obtained, denoted as

[0089] The inflated three-dimensional topographic map can make the three-dimensional topographic map shaped by the grid method more refined and closer to the actual situation, ensuring the movement safety of users of the aiming scope device.

[0090] In an embodiment of the present invention, the step S1 specifically includes:

[0091] Enter each aiming scope device into the network controller, install encryption certificates for each aiming scope device respectively, and enter the fingerprints of the users of each aiming scope device into their respective encryption certificates. The encryption certificates are unique;

[0092] Create a virtual network in the network controller. The virtual network includes multiple virtual subnets, and each virtual subnet includes multiple aiming scope devices. Enable the encryption certificates on each virtual subnet and update it to an encrypted virtual network;

[0093] When any aiming scope device communicates with another aiming scope device on the same subnet through a spectrum channel, it is automatically encrypted under the control of the encryption certificate.

[0094] When communicating in the encrypted virtual network environment, information needs to be transmitted through a key to lock the communication process and make the communication more secure.

[0095] In an embodiment of the present invention, the step S2 specifically includes:

[0096] Users of the telescopic sight devices in the same virtual subnet send information through the spectrum channels and assign priorities to the information to be sent. The initial priority of each node is level 0, denoted as flag = 0. The user holding the telescopic sight has the right to increase the priority of the node by 2 levels, and the global commander of the virtual network has the right to increase the priority of the node by 1 level;

[0097] The larger the flag, the higher the priority and the higher the urgency of the information. The lowest priority is level 0, indicating ordinary transmission without priority, and the highest priority is level 3, indicating that the information to be sent by the telescopic sight has the highest urgency and uses the emergency spectrum channel;

[0098] Taking the number of virtual subnets as a variable, the Stackelberg game method is used to allocate the spectrum quantity to each virtual subnet;

[0099] The telescopic sight users who need to send emergency information preempt the emergency spectrum channel according to the priority level using the multi-level feedback queue scheduling algorithm.

[0100] In an embodiment of the present invention, the generation of the node label includes:

[0101] Each node sends node data to the nodes included in its respective virtual subnet. The node data includes the node coordinates and the cost of the expected transmission information. The distance between the node and its neighboring nodes and the cost of the expected transmission information are weighted and calculated to obtain the transmission loss. Each node generates a node label and stores it in the telescopic sight memory;

[0102] The node label contains the node coordinates, the expected transmission cost, and the transmission loss. The format of the node label is a generalized list, and its mathematical expression is:

[0103] M((x,y,z),b,c)

[0104] Among them, (x,y,z) is the three-dimensional coordinate of the position where the telescopic sight is located, b is the expected transmission cost, and c is the transmission loss.

[0105] In an embodiment of the present invention, the step S4 specifically includes:

[0106] The initialization of the spectrum allocation process of the nodes includes:

[0107] The nodes are grouped according to the bandwidth of the spectrum channels applicable to the nodes. One node is applicable to greater than or equal to one spectrum channel, and a matrix of nodes applicable to each spectrum channel is obtained. The columns of the matrix are the node numbers, and the rows of the matrix are the spectrums of the spectrum channels. The applicable spectrum channels corresponding to the nodes are marked as A in the matrix, and the remaining spectrum channels are marked as B;

[0108] Set the loss value threshold of the node in the spectrum channel to a. If the transmission loss value of the node in the spectrum channel is greater than a, mark the spectrum channel corresponding to the node as B in the matrix;

[0109] Convert the matrix into an adjacency list, and perform a depth-first traversal of the adjacency list. Each row of the adjacency list represents the applicable nodes included in the spectrum channel. When performing a depth-first traversal of a certain row of data in the adjacency list, query the priority of each node and compare it with the priority of its previous node. If the priority of the node is greater than the priority of the previous node, swap the positions of the node and its previous node, and repeat the operation until the priority of the node is no longer greater than the priority of the previous node to obtain a new adjacency list;

[0110] The first column of the adjacency list is the node with the highest priority in each spectrum channel, and the lower the node priority is towards the back. Re-perform a depth-first traversal of the new adjacency list. When the depth-first traversal reaches a node with a priority greater than or equal to level 2, stop the depth-first traversal backward, archive the historical depth-first traversal point in the spectrum channel and perform a depth-first traversal of the next spectrum channel. If the depth-first traversal reaches the same node that has been depth-first traversed before, delete the node and perform a depth-first traversal backward. After the depth-first traversal of the last spectrum channel, start querying the node priority from the historical depth-first traversal point of the first spectrum channel where the depth-first traversal started. If the depth-first traversal reaches a node with a priority of level 1, archive the historical depth-first traversal point in the spectrum channel and perform a depth-first traversal of the next spectrum channel. If the depth-first traversal reaches the same node that has been depth-first traversed before, delete the node and perform a depth-first traversal backward. After the depth-first traversal of the last spectrum channel, start querying the node priority from the historical depth-first traversal point of the first spectrum channel where the depth-first traversal started, and delete the duplicate nodes among the remaining nodes to obtain the adjacency list of the node distribution.

[0111] Initializing the spectrum allocation of nodes makes the convergence speed of the optimized node allocation algorithm faster and the calculation simpler. In an embodiment of the present invention, after the nodes share the node labels with neighboring nodes several times, the node labels of all nodes in the virtual subnet are obtained, and a triple table containing all node labels is generated in the memory of the aiming device. When the node moves or the transmission loss changes, the node updates the node label and shares it with its neighboring nodes. Each node in the virtual network quickly iteratively refreshes the triple table, and comprehensively considers the refreshed triple table and the priorities of the refreshed nodes to refresh the spectrum allocation situation.

[0112] In one embodiment of the present invention, the surface points are the feasible sets of the nodes. The surface points form a node graph at each horizontal layer. The initialized nodes are the initial shortest distances. All nodes are vertically mapped onto all the horizontal layers. Starting from the highest horizontal layer to the lowest horizontal layer, all nodes are queried, and the distances to the neighboring nodes of each node are queried in turn. The nearest neighbor nodes of each node are found, and the surface nodes in each layer are selected and inserted as path nodes according to the nearest neighbor nodes. Based on the set of path nodes on all the horizontal layers, a locally optimal path solution for node allocation is obtained. The fitness is updated according to the locally optimal path solution, the parameters are adjusted and the fitness is updated. When the fitness is the smallest, it is determined whether to adjust or update the positions of the nodes and the spectral channels of the frequencies they are in according to the new fitness and probability. When the fitness is the smallest, it is judged whether the combination of all the locally optimal solutions can form a global path solution, and finally the optimal paths of all the nodes of the virtual subnet are obtained;

[0113] The improved bat algorithm uses a hierarchical approach to process the three-dimensional topographic map and query the neighboring nodes to generate a locally optimal path solution, and then obtains the global optimal solution from the locally optimal path solution, solving the problem of local optimal solution convergence in the traditional bat algorithm; the improved bat algorithm uses the idea of calculus to plan the locally optimal path solution, making the path planning more in line with the actual surface and the allocation of users of the aiming device more accurate.

[0114] The adjusted parameters are and 。

[0115] In one embodiment of the present invention, the data expression of the total network loss is:

[0116]

[0117] where S is the total network loss value, the L() function is the Euclidean distance formula, is the expected transmission loss value regarding the distance between node and node , is the mathematical expectation of the transmission loss between all nodes, is the horizontal coordinate of the node label;

[0118] The fitness is used to evaluate the quality of each individual in the population. The mathematical expression of the fitness is:

[0119]

[0120] where is the fitness, is the total network loss value, is an infinitesimal quantity, is the node, is a set of surface points;

[0121] The improved bat algorithm updates the node positions, user movement speeds, and transmission losses:

[0122]

[0123]

[0124]

[0125] where is the bandwidth frequency that the i-th node can use for the spectrum channel, is the maximum frequency, is the minimum frequency, is a random number, and are the user movement speeds of the i-th node at times t and t - 1 respectively, is the global optimal solution, and are the positions of the i-th node at times t and t - 1 respectively; The mathematical expression for updating the local search is:

[0126]

[0127] where is a random value, x ∈ [0, 1], is the average loss value at time step t, is the current global optimal solution, and as the iteration progresses, the loss value also changes:

[0128]

[0129] where and are the estimated loss values of the i-th node at times t and t - 1 respectively, is a parameter variable and > 0, and the mathematical expression for the probability is:

[0130]

[0131] where P is the probability, is the priority of the i-th node, is a constant and < 1, and t is the time;

[0132] When traversing the query node distance hierarchically, a priority queue is established to store candidate nodes, and the entry point is added to the priority queue. Each time, the node closest to the query point is taken out from the priority queue, and its neighbor nodes are queried. If the neighbor nodes have not been traversed hierarchically, they are added to the priority queue. Finally, the distances between the query point and all candidate nodes are calculated and sorted, and the K nearest neighbor nodes of the query point are selected; the optimized node optimal path can combine the priority with the transmission loss and three-dimensional terrain to obtain the node path planning with the optimal spectrum allocation and the minimum transmission loss on the three-dimensional topographic map, which can make the aiming scope user interaction more effective and cooperation more convenient, and the efficiency of dividing group tasks higher.

[0133] If the combination of all local optimal solutions cannot form a global path solution, the parameters are readjusted to update the fitness until the initial set number of iterations is reached;

[0134] The iterative process includes adjusting parameters and updating fitness.

[0135] The algorithm improves the efficiency of searching for the nearest neighbor by saving the neighbor relationship between nodes, reduces the query time, and is applicable to large-scale data sets.

[0136] In an embodiment of the present invention, the bat algorithm simultaneously provides infrared ray emission to dynamically judge in real time whether there are active organisms near the location where the aiming scope device is located. If there are such organisms, a warning is issued to the user of the aiming scope device;

[0137] Set a flag value sign, and the initial sign value is 0. The user holding the aiming scope device marks the coordinates, including:

[0138] When setting the gathering location, set the sign value of the coordinates of the gathering location to 1;

[0139] When a dangerous location is found, set the sign value of the coordinates where the dangerous location is found to -1.

[0140] The improved optimized node allocation algorithm not only solves the defect of easy local convergence in the traditional bat algorithm, but also can give the user path planning of the aiming scope device close to the ground.

[0141] In an embodiment of the present invention, the step S6 specifically includes:

[0142] The node release method includes:

[0143] Delete the released node from all lists and networks where it exists, keep the spectrum allocation unchanged, and connect the neighbor nodes of the node in the network.

[0144] The present invention encrypts the network composed of the aiming device, making the communication process of the aiming device secure. The improved network node dynamic allocation algorithm enables the aiming device communication to perform group collaboration and interconnection, dynamic component networking, priority information screening, fast real-time transmission and adjustment. Combined with the three-dimensional topographic map, the aiming device can allocate node positions according to the three-dimensional actual terrain.

[0145] It should be recognized that embodiments of the present invention can be implemented or carried out by a combination of computer hardware and software, or by computer instructions stored in a non-transitory computer-readable memory. The methods can be implemented in a computer program using standard programming techniques - including a non-transitory computer-readable storage medium configured with the computer program, wherein the storage medium so configured causes the computer to operate in a specific and predefined manner - according to the methods and drawings described in the specific embodiments. Each program can be implemented in a high-level procedural or object-oriented programming language to communicate with the computer system. However, if desired, the program can be implemented in assembly or machine language. In any case, the language can be a compiled or interpreted language. Additionally, for this purpose the program is capable of running on a dedicated integrated circuit programmed for this purpose.

[0146] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

Claims

1. A sight data communication method, characterized in that: The following steps are involved: Step S1: constructing a virtual network, wherein the virtual network includes a plurality of virtual subnets, the virtual subnet includes a plurality of nodes, enabling an encryption certificate on each virtual subnet, updating the virtual network to an encrypted virtual network, and the node is a sight device; Step S2: Each virtual subnet reserves a spectrum channel as an emergency spectrum channel, and generates a three-dimensional node label of the sight according to the node data; Step S3: each of the sighting devices collects environmental images in real time, processes the images collected by the sighting device using a grid method, establishes a three-dimensional terrain model near the node and performs a puffing process, uploads the puffed three-dimensional terrain model to the virtual subnet where the sighting device is located, and shares the puffed three-dimensional terrain model with other virtual subnets; Step S4: using an improved bat algorithm to optimize network node allocation, the improved bat algorithm includes: Initialize the scope parameters and the spectrum allocation of nodes, use the total network loss as the evaluation criterion for the algorithm fitness, and calculate the initial fitness of the algorithm; Decompose the three-dimensional terrain map into multiple horizontal layers from the lowest point to the highest point, represent the surface curve as surface points on the horizontal layers, select the surface nodes in each layer according to the nearest nodes and insert them as path nodes, obtain the local optimal path solution of node allocation according to the set of path nodes on all the horizontal layers, and obtain the optimal path of all nodes in the virtual subnet according to the local optimal path solution; Step S5: using frequency hopping technology to transmit information, analyzing the frequency hopping pattern in the frequency hopping sequence, compressing and encoding the frequency hopping pattern using Huffman coding, and compressing the frequency hopping sequence into a shorter coding sequence; Step S6: When a node is damaged or abnormal, release the node and recycle the key.

2. The sight data communication method as claimed in claim 1, characterized in that: The step S1 specifically includes: Enter each sighting device into the network controller, install encryption certificates for each sighting device respectively, and enter the fingerprint of the user of each sighting device into the respective encryption certificates respectively, wherein the encryption certificates are unique; Creating a virtual network in the network controller, the virtual network including multiple virtual subnets, the virtual subnets including multiple scope devices, enabling encryption certificates on each virtual subnet, and updating to an encrypted virtual network; When any sight device communicates with another sight device on the same subnet through a spectrum channel, encryption is automatically performed under the control of the encryption certificate.

3. The sight data communication method as claimed in claim 1, characterized in that: The step S2 specifically includes: Users of the scope device in the same virtual subnet send information through the spectrum channel, and the priority of the pre-sent information is evaluated. The initial priority of each node is level 0, which is recorded as flag=0. The user holding the scope has the right to increase the priority of the node by 2 levels, and the global commander of the virtual network has the right to increase the priority of the node by 1 level; The larger the flag is, the higher the priority is, and the more urgent the information is. The lowest priority is level 0, indicating that ordinary transmission has no priority, and the highest priority is level 3, indicating that the information that the scope is expected to send has the highest urgency and uses the emergency spectrum channel. Taking the number of the virtual subnets as a variable, using the Stackelberg game method to allocate the number of spectrums to each virtual subnet; A scope user who needs to send emergency information uses a multi-level feedback queue scheduling algorithm to seize the emergency spectrum channel according to the priority level.

4. The sight data communication method as claimed in claim 3, characterized in that: The generation of the node label includes: Each node sends node data to the nodes included in the virtual subnet where it is located, and the node data includes node coordinates and the estimated cost of transmitting information. The distance between the node and the adjacent node and the estimated cost of transmitting information are weighted to obtain the transmission loss. Each node generates a node label and stores it in the sight memory; The node label includes the node coordinates, the estimated transmission cost and the transmission loss. The format of the node label is a generalized table, and its mathematical expression is: M((x,y,z),b,c) Among them, (x, y, z) is the three-dimensional coordinate of the location of the sight, b is the estimated transmission cost, and c is the transmission loss.

5. The sight data communication method as claimed in claim 4, characterized in that: The step S4 specifically includes: The spectrum allocation process of the initialization node includes: The nodes are grouped according to the bandwidth of the spectrum channel applicable to the nodes. One node is applicable to one or more spectrum channels. A matrix of nodes applicable to each spectrum channel is obtained. The columns of the matrix are node numbers, and the rows of the matrix are spectrum channel spectra. The applicable spectrum channels corresponding to the nodes are marked as A in the matrix, and the remaining spectrum channels are marked as B. Set the loss value threshold of the node in the spectrum channel to a. If the transmission loss value of the node in the spectrum channel is greater than a, mark the spectrum channel corresponding to the node as B in the matrix. The matrix is ​​converted into an adjacency list, and the adjacency list is traversed in depth-first manner, where each row of the adjacency list represents an applicable node included in the spectrum channel. When a row of data in the adjacency list is traversed in depth-first manner, the priority of each node is queried and compared with the priority of the previous node. If the priority of the node is greater than the priority of the previous node, the node is exchanged with the previous node, and the operation is repeated until the priority of the node is no longer greater than the priority of the previous node, thereby obtaining a new adjacency list. The first column of the adjacency table is the node with the highest priority in each spectrum channel, and the priority of the node decreases as the depth goes backward. The new adjacency table is traversed again with depth-first traversal. When the depth-first traversal reaches a node with a priority greater than or equal to level 2, the backward depth-first traversal is stopped, and the historical depth-first traversal point is archived in the spectrum channel and the next spectrum channel is traversed with depth-first traversal. If the depth-first traversal reaches the same node that has been traversed with depth-first traversal before, the node is deleted and the depth-first traversal is performed backward. After the depth-first traversal of the last spectrum channel is completed, the node priority is queried from the historical depth-first traversal point of the first spectrum channel that started the depth-first traversal. If the depth-first traversal reaches a node with a priority of level 1, the historical depth-first traversal point is archived in the spectrum channel and the next spectrum channel is traversed with depth-first traversal. If the depth-first traversal reaches the same node that has been traversed with depth-first traversal before, the node is deleted and the depth-first traversal is performed backward. After the depth-first traversal of the last spectrum channel is completed, the node priority is queried from the historical depth-first traversal point of the first spectrum channel that was traversed with depth-first traversal, and the node distribution adjacency table is obtained.

6. The sight data communication method as claimed in claim 5, characterized in that: After sharing node labels with adjacent nodes several times, each node obtains the node labels of all nodes in the virtual subnet, and generates a triplet table containing all node labels in the memory of the sight device. When the node moves or the transmission loss changes, the node updates the node label and shares it with its adjacent nodes. Each node in the virtual network quickly iterates and refreshes the triplet table, and comprehensively considers the refreshed triplet table and the refreshed priority of each node to refresh the spectrum allocation.

7. The sight data communication method as claimed in claim 5, characterized in that: The surface points are the feasible set of the nodes. The surface points form a node graph in each horizontal layer. The initialization node is the initial shortest distance. All nodes are vertically mapped on all the horizontal layers. All nodes are queried from the highest horizontal layer to the lowest horizontal layer, and the distances of the neighboring nodes of each node are queried in turn to find the nearest nodes of each node. The surface nodes in each layer are selected according to the nearest nodes and inserted as path nodes. The local optimal path solution of the node allocation is obtained according to the set of path nodes on all the horizontal layers. The fitness is updated according to the local optimal path solution, the parameters are adjusted and the fitness is updated. When the fitness is the minimum, it is decided whether to adjust or update the position of the node and the spectrum channel of the frequency at which it is located according to the new fitness and probability. When the fitness is the minimum, it is determined whether the combination of all local optimal solutions can form a global path solution, and finally the optimal path of all nodes in the virtual subnet is obtained. The parameters adjusted are and ; The data expression of the total network loss is: ； Among them, S is the total network loss value, and the L() function is the Euclidean distance formula. For Node and nodes The expected transmission loss value with respect to the distance between is the mathematical expectation of transmission loss between all nodes, is the horizontal coordinate of the node label; The fitness is used to evaluate the quality of each individual in the population. The mathematical expression of fitness is: ； in is the fitness, S is the total network loss value, is an infinitesimal quantity, For nodes, is a collection of surface points; The improved bat algorithm updates the node location, user movement speed and transmission loss: ； ； ； in, is the bandwidth frequency of the spectrum channel that the i-th node can use, is the maximum frequency, is the minimum frequency, is a random number, and are the user movement speeds of the i-th node at time t and t-1, respectively. is the global optimal solution, and are the positions of the i-th node at time t and t-1 respectively; The mathematical expression for updating the local search is: ； in, is a random value, x [0,1], is the average loss value of t time steps, This is the current global optimal solution. As the iteration progresses, the loss value also changes: ； in, and is the estimated loss value of the i-th node at time t and t-1, is a parameter variable and >0, the mathematical expression of the probability is: ； Where P is the probability, is the priority of the ith node, is a constant and <1, t is time; When the level traverses the query node distance, a priority queue is established to store candidate nodes, and the entry point is added to the priority queue. Each time, the node closest to the query point is taken from the priority queue, and its neighbor node is queried. If the neighbor node has not been traversed by the level, it is added to the priority queue. Finally, the distance between the query point and all candidate nodes is calculated, and the distance is sorted, and the K nearest neighbor nodes of the query point are selected; If the combination of all local optimal solutions cannot form a global path solution, the parameters are readjusted to update the fitness until the number of iterations set initially is reached; The iterative process includes adjusting parameters and updating fitness.

8. The sight data communication method as claimed in claim 7, characterized in that: The bat algorithm also provides infrared rays to dynamically determine in real time whether there are any active creatures near the location where the sight device is located. If the creatures appear, a warning is issued to the user of the sight device. A sign value sign is set, the initial sign value is 0, and the user holding the scope device marks the coordinates including: When setting a gathering place, set the sign value of the coordinates of the gathering place to 1; When a dangerous place is found, the sign value of the coordinates where the dangerous place is found is set to -1.

9. The sight data communication method as claimed in claim 1, characterized in that: The step S6 specifically includes: Methods for releasing nodes include: The released node is deleted from all lists and networks in which it exists, spectrum allocation remains unchanged, and neighbor nodes of the node are connected in the network.

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