Sighting telescope data communication method

Abstract

The invention discloses a sighting telescope data communication method, which relates to the technical field of sighting telescope data communication, and comprises the following steps: constructing a virtual network, updating the virtual network into an encrypted virtual network, reserving a frequency spectrum channel as an emergency frequency spectrum channel for each virtual sub-network, acquiring an environment image in real time by each sighting telescope device, and transmitting the environment image to the corresponding virtual sub-network. And a grid method is adopted to process the image collected by the sighting telescope, a three-dimensional terrain model near nodes is established and puffing processing is carried out, an improved bat algorithm is adopted to optimize network node distribution, and all node optimal paths of the virtual subnet are obtained according to the local optimal path solution. According to the invention, a network formed by sighting telescope equipment is encrypted and a frequency hopping technology is used, so that the communication process of the sighting telescope is safe; the improved network node dynamic allocation algorithm enables sighting telescope communication to perform group cooperation intercommunication, dynamic component network, priority information screening, rapid real-time transmission adjustment and attachment to three-dimensional actual terrain allocation node positions.

Description

Technical Field

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

[0002] The sight is an integral and important part of modern weapons. It has become an important means to improve the combat capability of weapons, especially the all-weather combat capability. The sight mobile ad hoc network in the military environment not only has the problems of dynamically changing topology and limited wireless transmission bandwidth, but also requires high reliability, high security and high real-time performance.

[0003] At present, the Chinese utility model patent with application number 202023012868.3 discloses a digital multifunctional civilian night vision sight movement. Although the sight can support wireless video transmission and has the characteristics of low latency, the sight does not have the ability of group collaboration and intercommunication and dynamic network formation, nor does it have security. It does not have the fast real-time transmission and adjustment required by military communication technology, and the ability to allocate sight users and prioritize information based on three-dimensional terrain planning. Summary of the invention

[0004] The technical problem solved by the present invention is that the sight in the related technology cannot perform group collaboration and communication, dynamic component network, secure information transmission, fast real-time transmission and adjustment, and the ability to allocate sight users and filter priority information according to three-dimensional terrain planning.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a sighting scope data communication method, comprising the following steps: 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.

[0006] As a preferred solution of the present invention, 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.

[0007] As a preferred solution of the present invention, 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.

[0008] As a preferred solution of the present invention, 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.

[0009] As a preferred solution of the present invention, 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.

[0010] As a preferred solution of the present invention, each node obtains the node labels of all nodes in the virtual subnet after sharing the node labels with adjacent nodes several times, 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.

[0011] As a preferred solution of the present invention, the surface points are the feasibility 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, the nearest nodes of each node are found, and 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, according to the new fitness and probability, it is decided whether to adjust or update the position of the node and the spectrum channel of the frequency where it is located, 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 .

[0012] As a preferred solution of the present invention, the data expression of the total network loss is:

[0013] Among them, S is the total network loss value, and the L() function is the Euclidean distance formula. For Node The expected transmission loss value with respect to the distance between is the mathematical expectation of the 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:

[0014] in, For fitness, is the total network loss value, is an infinitesimal quantity, For nodes, is a set of ground points; The improved bat algorithm updates the node location, user movement speed and transmission loss:

[0015]

[0016]

[0017] 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:

[0018] 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:

[0019] 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:

[0020] 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.

[0021] As a preferred solution of the present invention, the bat algorithm also provides infrared rays to dynamically determine in real time whether there are 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.

[0022] As a preferred solution of the present invention, 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.

[0023] Beneficial effects of the present invention: The present invention encrypts the network composed of sight equipment to make the communication process of the sight safe. The improved network node dynamic allocation algorithm enables the sight communication to carry out group collaboration and intercommunication, dynamic component network, priority information screening, fast real-time transmission and adjustment. Combined with the three-dimensional terrain map, the sight can allocate node positions in accordance with the three-dimensional actual terrain. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A basic flow chart of a sighting scope data communication method provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, but not all of the embodiments.

[0026] Example 1, reference Figure 1 , as an embodiment of the present invention, provides a sighting scope data communication method, comprising the following steps: 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.

[0027] The invention encrypts the network composed of the sight equipment so that the communication process of the sight is safe. The improved network node dynamic allocation algorithm enables the sight communication to carry out group collaboration, dynamic component network, priority information screening, fast real-time transmission and adjustment. Combined with the three-dimensional terrain map, the sight can allocate node positions according to the three-dimensional actual terrain. The signal is converted into a pseudo-noise state by frequency hopping after Huffman coding compression, which can make the signal converge faster, occupy less memory, and make the communication safer.

[0028] After using the grid method to build the initial environmental model, the initial environmental model is expanded. In areas with relatively dangerous terrain, larger units are expanded, and in areas with relatively flat and safe terrain, smaller units are expanded. This can ensure the safety of navigation and ensure that it fits the original terrain as closely as possible.

[0029] The puffing process includes: The entire environment is divided on the XOY plane into different numbers of environmental blocks according to different scales. The mathematical expression for the number of environmental blocks after division is:

[0030] in, and Respectively represent the scale of segmentation in the length axis direction and the width axis direction, is the number of environment blocks after segmentation, and the set of environment blocks after segmentation is ; Calculate the ruggedness of each environmental block. The calculation of ruggedness mainly depends on the maximum slope of each environmental block. To calculate the maximum slope, take two obstacle grids with the maximum D value and the minimum D value in each environmental block, and then calculate the slope according to the position of the two grids on the XOY plane. The maximum D value grid in the environmental block is recorded as , the minimum value grid is , the specific mathematical expression of the calculation method is:

[0031] Get the roughness set of an environment block as ; Different threat levels are assigned to each environment block according to the different ruggedness, and different units of expansion are performed. The expansion unit is large in places with high ruggedness, and small in places with low ruggedness. The mathematical expression of the expansion scale is:

[0032] In this way, the expansion scale corresponding to each environment block can be obtained, which is recorded as

[0033] The expanded three-dimensional topographic map can make the three-dimensional topographic map created by the grid method more detailed and more realistic, ensuring the mobile safety of users of the scope equipment.

[0034] In one embodiment of the present invention, 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.

[0035] In an encrypted virtual network environment, communication requires the use of keys to transmit information, which locks the communication process and makes communication more secure.

[0036] In one embodiment of the present invention, 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.

[0037] In one embodiment of the present invention, 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.

[0038] In one embodiment of the present invention, 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.

[0039] Initializing the spectrum allocation of nodes makes the optimized node allocation algorithm converge faster and easier to calculate. In one embodiment of the present invention, each node obtains the node labels of all nodes in the virtual subnet after sharing the node labels with neighboring nodes several times, and generates a triple 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 neighboring nodes. Each node in the virtual network quickly iterates and refreshes the triple table, and comprehensively considers the refreshed triple table and the refreshed priority of each node to refresh the spectrum allocation.

[0040] In one embodiment of the present invention, the surface point is a feasible set of the nodes, and the surface points form a node graph in each horizontal layer. The initialization node is the initial shortest distance, and 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 node of each node, and 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, and the fitness is updated according to the local optimal path solution, and the parameters are adjusted and the fitness is updated. When the fitness is the minimum, it is determined 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 improved bat algorithm uses the method of layered processing of three-dimensional terrain maps and querying neighboring nodes to generate a local optimal path solution, and then obtains the global optimal solution from the local optimal path solution, which solves the problem of convergence of local optimal solutions in the traditional bat algorithm; the improved bat algorithm uses the idea of ​​calculus to plan the local optimal path solution, making the path planning more in line with the actual surface and the allocation of users of the sight equipment more accurate.

[0041] The parameters adjusted are and .

[0042] In one embodiment of the present invention, the data expression of the total network loss is:

[0043] Among them, S is the total network loss value, and the L() function is the Euclidean distance formula. For Node The expected transmission loss value with respect to the distance between is the mathematical expectation of the 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:

[0044] in For fitness, is the total network loss value, is an infinitesimal quantity, For nodes, is a set of ground points; The improved bat algorithm updates the node location, user movement speed and transmission loss:

[0045]

[0046]

[0047] 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:

[0048] 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:

[0049] 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:

[0050] Where P is the probability, is the priority of the ith node, is a constant and <1, t is time; When the hierarchy 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 out from the priority queue, and its neighbor node is queried. If the neighbor node has not been traversed by the hierarchy, 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 to select the K nearest neighbor nodes of the query point. The optimized node optimal path can combine priority with transmission loss and three-dimensional terrain to obtain a node path planning with optimal spectrum allocation and minimum transmission loss on a three-dimensional terrain map, which can make the interaction between sight users more effective and cooperation more convenient, and the division of group tasks more efficient.

[0051] 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.

[0052] The algorithm improves the efficiency of searching for nearest neighbors and reduces query time by preserving the neighbor relationships between nodes. It is also applicable to large-scale data sets.

[0053] In one embodiment of the present invention, the bat algorithm also provides for emitting infrared rays to dynamically determine in real time whether there are active creatures near the location where the sight device is located, and 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.

[0054] The improved optimization node allocation algorithm not only solves the defect of easy local convergence in the traditional bat algorithm, but also can provide user path planning for the sighting device implemented close to the surface.

[0055] In one embodiment of the present invention, step S6 specifically includes: The node release methods 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.

[0056] The present invention encrypts the network composed of sight equipment to make the communication process of the sight safe. The improved network node dynamic allocation algorithm enables the sight communication to perform group collaboration, dynamic component network, priority information screening, fast real-time transmission and adjustment. Combined with the three-dimensional terrain map, the sight can allocate node positions in accordance with the three-dimensional actual terrain.

[0057] It should be appreciated that embodiments of the present invention may be implemented or enforced by a combination of computer hardware and software, or by computer instructions stored in a non-transitory computer-readable memory. The method may be implemented in a computer program using standard programming techniques - including a non-transitory computer-readable storage medium configured with a 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 may be implemented in a high-level procedural or object-oriented programming language to communicate with a computer system. However, if desired, the program may be implemented in an assembly or machine language. In any case, the language may be a compiled or interpreted language. In addition, the program may be run on a programmed ASIC for this purpose.

[0058] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in 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. Setting a loss value threshold of a node in a spectrum channel to a, if the transmission loss value of the node in the spectrum channel is greater than a, marking 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, and 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 .

8. The sight data communication method as claimed in claim 7, characterized in that: 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 The expected transmission loss value with respect to the distance between is the mathematical expectation of the 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.

9. The sight data communication method as claimed in claim 8, 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.

10. The sight data communication method according to claim 1, wherein: The step S6 specifically includes: Methods for releasing nodes include: The released node is deleted from all existing lists and networks, spectrum allocation remains unchanged, and neighbor nodes of the node are connected in the network.

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