Water surface three-dimensional collaborative navigation method and system and electronic equipment

Abstract

The invention relates to the technical field of water surface three-dimensional collaborative navigation scheme design, in particular to a water surface three-dimensional collaborative navigation method and system and electronic equipment. The underwater electromagnetic wave communication frequency automatic modulation model is trained, and after model training is completed and submarine position data of a target submarine are obtained through a sonar detector arranged on a water surface platform, the distance between the submarine position data and GPS position information of an underwater subsurface buoy is calculated; and inputting the distance into an underwater electromagnetic wave communication frequency automatic modulation model, and controlling the underwater subsurface buoy to communicate with the target submarine through electromagnetic waves according to a predicted electromagnetic wave frequency output by the model. The underwater electromagnetic wave communication frequency is automatically modulated, the technical problems that the influence on signal transmission is also increased due to the increase of the transmission distance, and the transmission frequency is difficult to be reasonably modulated in a threshold value calculation mode are effectively solved, and the positioning and navigation effects of the navigation system of the submarine are further improved to a great extent.

Description

Technical Field

[0001] The present invention relates to the technical field of water surface stereoscopic collaborative navigation scheme design, and in particular to a water surface stereoscopic collaborative navigation method and system, and electronic equipment. Background Art

[0002] Electromagnetic waves do not require a medium to propagate, so they can propagate without a medium. However, water has a strong absorption and attenuation effect on electromagnetic waves, especially high-frequency electromagnetic waves, such as radio waves and microwaves, which are greatly hindered when propagating in water. Although electromagnetic waves do not propagate well in water, they still have their uses in certain specific applications. For example, the guidance system of a torpedo relies on electromagnetic waves to establish contact with the missile. Although the propagation effect of electromagnetic waves in water is limited, target positioning can still be achieved through specific technical means. And the transmission speed of electromagnetic waves still has great advantages over sound wave conduction. However, due to the increase in transmission distance, the impact of water on signal transmission will also increase, and it is difficult to reasonably modulate the transmission frequency by threshold calculation. Therefore, how to reasonably use electromagnetic waves to improve the efficiency and accuracy of the submarine's own positioning, and then improve the positioning and navigation effect of the submarine's navigation system, is a problem that needs to be solved in the existing technology.‌

[0003] Therefore, the prior art needs to be further developed. Summary of the invention

[0004] The purpose of the present invention is to overcome the above-mentioned technical deficiencies and provide a water surface three-dimensional collaborative navigation method and system, and electronic equipment to solve the problems existing in the prior art.

[0005] To achieve the above technical objectives, according to a first aspect of the present invention, the present invention provides a water surface three-dimensional collaborative navigation method, comprising: S100, setting a GPS sensor in the underwater buoy, using the GPS sensor set in the underwater buoy to obtain the GPS position information of the underwater buoy before it is released underwater, releasing the underwater buoy into the water, using the sonar detector set on the surface platform to obtain the submarine position data of the submarine, controlling the surface platform to use wireless sound waves to send the submarine position data frame to the underwater buoy, using the underwater buoy to transmit the submarine position data frame to the target submarine according to a preset electromagnetic wave frequency, and the submarine position data frame also records the sending time of the submarine position data frame; recording the timestamp of the target submarine receiving the submarine position data frame, calculating the transmission time of the submarine position data frame according to the timestamp and the sending time, judging whether the transmission time is less than or equal to a first preset threshold value, if not, increasing the electromagnetic wave frequency of the next submarine position data frame according to the preset electromagnetic wave frequency interval until the transmission time is less than or equal to the first preset threshold value; S200, calculating the distance between the GPS position information of the underwater buoy and the submarine position data of the target submarine at this time, recording the distance and the electromagnetic wave frequency, and forming an underwater frequency modulation data set; collecting a first preset number of underwater frequency modulation data sets, and dividing the collected underwater frequency modulation data sets into a training data set and a verification data set according to a first preset ratio; using the collected training data set to train an underwater electromagnetic wave communication frequency automatic modulation model, using the verification data set to optimize the underwater electromagnetic wave communication frequency automatic modulation model, optimizing the model parameters, and completing the underwater electromagnetic wave communication frequency automatic modulation model training; S300. After the model training is completed, after the submarine position data of the target submarine is obtained by using the sonar detector installed on the surface platform, the distance between the submarine position data and the GPS position information of the underwater buoy is calculated, and the distance is input into the automatic modulation model of the underwater electromagnetic wave communication frequency. According to the predicted electromagnetic wave frequency output by the model, the underwater buoy is controlled to communicate with the target submarine through electromagnetic waves, so that the target submarine obtains the submarine position data. The target submarine plans the navigation path according to the obtained submarine position data.

[0006] Specifically, the method of obtaining the submarine position data of the submarine by using a sonar detector arranged on the surface platform includes: The sonar detector installed on the surface platform is used to obtain the submarine position data of the submarine at preset time intervals, and to generate submarine position data frames at preset time intervals.

[0007] Specifically, the method further includes: If the first transmission time is less than or equal to the first preset threshold, the distance between the initial GPS position information and the submarine position data of the target submarine is calculated, and the distance and the electromagnetic wave frequency are recorded to form an underwater frequency modulation data set.

[0008] Specifically, the method uses the collected training data set to train the underwater electromagnetic wave communication frequency automatic modulation model, uses the verification data set to optimize the underwater electromagnetic wave communication frequency automatic modulation model, optimizes the model parameters, and completes the underwater electromagnetic wave communication frequency automatic modulation model training, including: The training data set is input into the preset network layer in batches for training, and the preset network layer includes a Transformer network layer, and the Transformer network layer is used to predict the next underwater frequency modulation data set based on the forward propagation of the current underwater frequency modulation data set, and then obtain the predicted loss value; the loss value of the preset network layer is calculated and input into the optimizer for optimization, and the direction in which the parameter gradient of the underwater electromagnetic wave communication frequency automatic modulation model decreases fastest is determined; the underwater electromagnetic wave communication frequency automatic modulation model performs back propagation according to the loss value and the parameter gradient of the model, and optimizes the parameters of the underwater electromagnetic wave communication frequency automatic modulation model.

[0009] Specifically, the preset network layer also includes a ResNet network layer, and the ResNet network layer is used to predict the output result according to the collected underwater frequency modulation data set, and the prediction result includes the predicted electromagnetic wave frequency.

[0010] Specifically, the method uses the collected training data set to train the underwater electromagnetic wave communication frequency automatic modulation model, uses the verification data set to optimize the underwater electromagnetic wave communication frequency automatic modulation model, optimizes the model parameters, and completes the underwater electromagnetic wave communication frequency automatic modulation model training, and also includes: After each training, the verification data set is input into the preset network layer of the previous training in batches for model parameter verification, and cyclic training is performed, with the total number of training rounds set to the first preset round; the loss value of the preset network layer is recorded, and it is determined whether the loss value meets the first preset condition, and whether to end the training and output the model parameters based on the judgment result.

[0011] Specifically, the determining whether the loss value satisfies the first preset condition, and determining whether to end the training and output the model parameters according to the determination result, includes: If the loss value meets the first preset condition, the training is terminated and the parameters of the current underwater electromagnetic wave communication frequency automatic modulation model are output; if the loss value does not meet the first preset condition, the training is continued.

[0012] Specifically, the first preset condition is: After the second preset round of training, the loss values ​​obtained in the next round of training are greater than or equal to the loss values ​​that occurred during the second preset round of training.

[0013] According to a second aspect of the present invention, there is provided a water surface three-dimensional collaborative navigation system, comprising: An acquisition module is used to acquire GPS position information of the underwater buoy before it is released underwater using a GPS sensor disposed in the underwater buoy; The control module is used to release the underwater buoy into the water, and after the submarine position data of the submarine is obtained by using the sonar detector set on the surface platform, control the surface platform to use wireless sound waves to send the submarine position data frame to the underwater buoy, and use the underwater buoy to transmit the submarine position data frame to the target submarine according to the preset electromagnetic wave frequency, and the submarine position data frame also records the sending time of the submarine position data frame; record the timestamp of the target submarine receiving the submarine position data frame, calculate the transmission time of the submarine position data frame according to the timestamp and the sending time, and judge whether the transmission time is less than or equal to the first preset threshold value. If not, increase the electromagnetic wave frequency of the next submarine position data frame according to the preset electromagnetic wave frequency interval until the transmission time is less than or equal to the first preset threshold value; calculate the distance between the GPS position information of the underwater buoy and the submarine position data of the target submarine at this time, record the distance and the electromagnetic wave frequency, and form the underwater frequency modulation data The method comprises the steps of: collecting a first preset number of underwater frequency modulation data sets, dividing the collected underwater frequency modulation data sets into a training data set and a verification data set according to a first preset ratio; using the collected training data set to train an underwater electromagnetic wave communication frequency automatic modulation model, and using the verification data set to optimize the underwater electromagnetic wave communication frequency automatic modulation model, optimize the model parameters, and complete the underwater electromagnetic wave communication frequency automatic modulation model training; after the model training is completed, after obtaining the submarine position data of the target submarine by using the sonar detector set on the surface platform, calculating the distance between the submarine position data and the GPS position information of the underwater buoy, inputting the distance into the underwater electromagnetic wave communication frequency automatic modulation model, and controlling the underwater buoy to communicate with the target submarine through electromagnetic waves according to the predicted electromagnetic wave frequency output by the model, so that the target submarine obtains the submarine position data, and the target submarine performs navigation path planning according to the obtained submarine position data.

[0014] According to a third aspect of the present invention, there is provided an electronic device, comprising: a memory; and a processor, wherein the memory stores computer-readable instructions, and the computer-readable instructions, when executed by the processor, implement the above-mentioned surface stereo collaborative navigation method.

[0015] Beneficial effects: The present invention trains an automatic modulation model of underwater electromagnetic wave communication frequency. After the model training is completed, after the submarine position data of the target submarine is obtained by using a sonar detector set on a surface platform, the distance between the submarine position data and the GPS position information of the underwater buoy is calculated, and the distance is input into the automatic modulation model of underwater electromagnetic wave communication frequency. According to the predicted electromagnetic wave frequency output by the model, the underwater buoy is controlled to communicate with the target submarine through electromagnetic waves, so that the target submarine obtains the submarine position data, and the target submarine performs navigation path planning according to the obtained submarine position data. The automatic modulation of the underwater electromagnetic wave communication frequency is realized, and the technical problem that the increase of the transmission distance will also increase the influence on the signal transmission and it is difficult to reasonably modulate the transmission frequency by means of threshold value calculation is effectively overcome. The reasonable use of electromagnetic waves is realized to improve the efficiency and accuracy of the submarine's own positioning, thereby greatly improving the positioning and navigation effect of the submarine's navigation system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flow chart of a method for three-dimensional collaborative navigation on a water surface provided in a specific embodiment of the present invention; Figure 2 is a schematic diagram of the system composition of the water surface three-dimensional collaborative navigation system provided in a specific embodiment of the present invention; Figure 3 It is a structural schematic diagram of an automatic modulation model of underwater electromagnetic wave communication frequency provided in a specific embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to enable those skilled in the art to better understand the technical solution of the present invention, the technical solution of the present invention is clearly and completely described below in conjunction with the accompanying drawings of the present invention. Based on the embodiments in this application, other similar embodiments obtained by ordinary technicians in this field without making creative work should all fall within the scope of protection of this application. In addition, the directional words mentioned in the following embodiments, such as "up", "down", "left", "right", etc., are only reference to the directions of the accompanying drawings. Therefore, the directional words used are used to illustrate rather than limit the invention.

[0018] The present invention will be further described below in conjunction with the accompanying drawings and preferred embodiments.

[0019] See also Figure 1 The present invention provides a water surface three-dimensional collaborative navigation method, comprising: S100, setting a GPS sensor in the underwater buoy, using the GPS sensor set in the underwater buoy to obtain the GPS position information of the underwater buoy before it is released underwater, releasing the underwater buoy into the water, and using the sonar detector set on the surface platform to obtain the submarine position data of the submarine, controlling the surface platform to use wireless sound waves to send the submarine position data frame to the underwater buoy, using the underwater buoy to transmit the submarine position data frame to the target submarine according to a preset electromagnetic wave frequency, and the submarine position data frame also records the sending time of the submarine position data frame; recording the timestamp of the target submarine receiving the submarine position data frame, calculating the transmission time of the submarine position data frame according to the timestamp and the sending time, and judging whether the transmission time is less than or equal to a first preset threshold value, if not, increasing the electromagnetic wave frequency of the next submarine position data frame according to the preset electromagnetic wave frequency interval until the transmission time is less than or equal to the first preset threshold value.

[0020] It should be noted that before step S100, the following steps are included: A first preset threshold, a preset electromagnetic wave frequency interval, a first preset number, a first preset ratio, a first preset round, and a second preset round are preset in the control module.

[0021] It can be understood that the first preset threshold, preset electromagnetic wave frequency interval, first preset number, first preset ratio, first preset round and second preset round can be specifically set according to the actual needs of the user of the present invention. The present invention does not limit the specific values ​​of the above parameters, and there is no regularity in setting the specific values ​​of the above parameters, as long as it is applicable to the water surface three-dimensional collaborative navigation method proposed in the present invention.

[0022] Preferably, the present invention sets the first preset threshold to 0.2 seconds, the present invention sets the preset electromagnetic wave frequency interval to 2Mhz, the present invention sets the first preset number to 2000, the present invention sets the first preset ratio to 8:2, the present invention sets the first preset round to 40000 times, and the present invention sets the second preset round to 300. The above settings can further improve the performance of the model and the efficiency of model training, and greatly improve the accuracy and reliability of the prediction of the underwater electromagnetic wave communication frequency automatic modulation model of the present invention.

[0023] Specifically, the method of obtaining the submarine position data of the submarine by using a sonar detector arranged on the surface platform includes: The sonar detector installed on the surface platform is used to obtain the submarine position data of the submarine at preset time intervals, and to generate submarine position data frames at preset time intervals.

[0024] Specifically, the method further includes: If the first transmission time is less than or equal to the first preset threshold, the distance between the initial GPS position information and the submarine position data of the target submarine is calculated, and the distance and the electromagnetic wave frequency are recorded to form an underwater frequency modulation data set.

[0025] It can be understood that the lower the frequency of the electromagnetic wave, the longer the transmission distance in the water. This is because low-frequency electromagnetic waves attenuate less in water and can propagate longer distances. Based on this, the present invention designs and trains an automatic modulation model for underwater electromagnetic wave communication frequency.

[0026] S200, calculating the distance between the GPS position information of the underwater buoy and the submarine position data of the target submarine at this time, recording the distance and the electromagnetic wave frequency, and forming an underwater frequency modulation data set; collecting a first preset number of underwater frequency modulation data sets, and dividing the collected underwater frequency modulation data sets into a training data set and a verification data set according to a first preset ratio; using the collected training data set to train an underwater electromagnetic wave communication frequency automatic modulation model, and using the verification data set to optimize the underwater electromagnetic wave communication frequency automatic modulation model, optimize the model parameters, and complete the underwater electromagnetic wave communication frequency automatic modulation model training.

[0027] Specifically, the method uses the collected training data set to train the underwater electromagnetic wave communication frequency automatic modulation model, uses the verification data set to optimize the underwater electromagnetic wave communication frequency automatic modulation model, optimizes the model parameters, and completes the underwater electromagnetic wave communication frequency automatic modulation model training, including: The training data set is input into the preset network layer in batches for training, and the preset network layer includes a Transformer network layer, and the Transformer network layer is used to predict the next underwater frequency modulation data set based on the forward propagation of the current underwater frequency modulation data set, and then obtain the predicted loss value; the loss value of the preset network layer is calculated and input into the optimizer for optimization, and the direction in which the parameter gradient of the underwater electromagnetic wave communication frequency automatic modulation model decreases fastest is determined; the underwater electromagnetic wave communication frequency automatic modulation model performs back propagation according to the loss value and the parameter gradient of the model, and optimizes the parameters of the underwater electromagnetic wave communication frequency automatic modulation model.

[0028] It can be understood that Transformer is a deep learning model based on the self-attention mechanism, which consists of a multi-head attention mechanism and a feedforward neural network. It can process sequence data and capture long-distance dependencies. The Transformer model does not contain traditional convolutional layers, but processes each element in the input sequence through an attention layer. The typical structure of Transformer includes an encoder and a decoder, wherein the encoder is composed of multiple identical layers stacked together, and the decoder adds a self-attention layer on the basis of the encoder to process sequence generation tasks. The present invention uses Transformer to supplement global context information, enhances the model's capabilities in feature extraction and global understanding, greatly improves the performance of the model, and greatly reduces the computational cost.

[0029] Specifically, the preset network layer also includes a ResNet network layer, and the ResNet network layer is used to predict the output result according to the collected underwater frequency modulation data set, and the prediction result includes the predicted electromagnetic wave frequency.

[0030] It should be noted here that ResNet is a deep convolutional neural network that solves the gradient vanishing problem in deep network training by introducing residual connections. The core component of ResNet is the residual block, which usually contains two or three convolutional layers and a jump connection, which allows the gradient to bypass these convolutional layers directly. The network structure of ResNet can be very deep. These networks extract the characteristics of distance and electromagnetic wave frequency in the underwater frequency modulation data set by stacking multiple residual blocks, and predict the output results through global average pooling and fully connected layers, and the predicted results include the predicted electromagnetic wave frequency.

[0031] See also Figure 3 The present invention combines the ResNet network layer and the Transformer network layer. ResNet is good at extracting local features of distance and electromagnetic wave frequency in the water frequency modulation data set, while Transformer can supplement the global context information. This combination can enhance the model's ability in feature extraction and global understanding, greatly improve the performance of the model, and greatly reduce the computational cost.

[0032] It can be understood that the ResNet network layer is used to predict the output result through the water frequency modulation data set collected in the training data set and the verification data set. The specific steps are: (1) First, put the training data set into the Backbones network layer of the model. Backbone refers to a series of convolutional layers that constitute the skeleton of the neural network. The main function of these layers is to extract the features of the input data. The Backbone network is usually composed of multiple convolutional layers, pooling layers, and activation functions. It can extract meaningful feature representations from the original data. Backbones is composed of multiple Backbones, and the core network layer in Backbone is the Resnet network layer. After the data set is input into the model, the underwater frequency modulation data set will be input into Backbones for training; (2) When constructing Backbone, a Resnet network layer was added. After the training data set was input, Resnet began to train layer by layer. The training extracted features from the underwater frequency modulation data set and assisted Transformer in predicting the output results, including the predicted electromagnetic wave frequency.

[0033] Specifically, the method uses the collected training data set to train the underwater electromagnetic wave communication frequency automatic modulation model, uses the verification data set to optimize the underwater electromagnetic wave communication frequency automatic modulation model, optimizes the model parameters, and completes the underwater electromagnetic wave communication frequency automatic modulation model training, and also includes: After each training, the verification data set is input into the preset network layer of the previous training in batches for model parameter verification, and cyclic training is performed, with the total number of training rounds set to the first preset round; the loss value of the preset network layer is recorded, and it is determined whether the loss value meets the first preset condition, and whether to end the training and output the model parameters based on the judgment result.

[0034] Specifically, after each training, the verification data set is input into the preset network layer of the previous training in batches to verify the model parameters, and the cyclic training is performed, including the following methods: When the number of training times is not enough and the model needs to be optimized, the training can only be performed from the beginning. Therefore, the present invention develops a method for continuing the following training based on the previously trained model parameter file; (1) Provide custom parameters, which can be set according to user needs to continue training based on any training parameters; (2) Load the parameters of the custom model file; (3) Put the validation data set into the custom parameter network layer for validation, obtain the loss value and record the model parameters of the model corresponding to the minimum loss value during the training process; (4) Based on this set of model parameters, forward propagation training and back propagation are performed, and the optimizer optimizes the parameters to obtain a new set of data; (5) Put the verification data into the new data network layer for inference to obtain the loss value; (6) Perform cyclic training to obtain the best model and complete model optimization.

[0035] It is understandable that the training method adopted by the present invention is batch training, which means that each time the model parameters are updated, only a part of the samples in the validation data set is used, which is called a batch. The advantages of batch training are that it can reduce memory consumption, speed up training, increase randomness, and facilitate the generalization of the model.

[0036] It should be noted here that, in the present invention, batch_size=4, and the batch_size is the batch size. For example, when batch_size=4, it means that four water frequency modulation data sets are selected from the verification data set each time and put into the model for verification.

[0037] Specifically, the determining whether the loss value satisfies the first preset condition, and determining whether to end the training and output the model parameters according to the determination result, includes: If the loss value satisfies the first preset condition, the training is terminated and the parameters of the current underwater electromagnetic wave communication frequency automatic modulation model are output; if the loss value does not satisfy the first preset condition, the training is continued; The first preset condition is that after the second preset round of training, the loss values ​​obtained in the next round of training are greater than or equal to the loss values ​​that occurred during the second preset round of training.

[0038] It can be understood that the present invention preferably sets the maximum round of cyclic training to 40,000 times, which can effectively ensure the accuracy of the model prediction of the present invention and record the loss value of the model training. The present invention sets the second preset round to 300, that is, when the loss value of the training no longer decreases within 300 rounds of training, the round with the smallest loss value in the 300 rounds of training is saved as the best verification round parameter to generate the best model file. The above setting makes the training rounds no longer rely on manual judgment, but uses the deep learning model for automatic training, which improves the accuracy of the model prediction, and automatically ends the training when the accuracy meets the requirements, which greatly saves the training time, and can also effectively prevent overfitting, which greatly improves the intelligence level of the present invention and the efficiency of model training.

[0039] Furthermore, the specific process of the present invention for training the underwater electromagnetic wave communication frequency automatic modulation model is as follows: (1) Obtain the potential vector mean mu and logarithmic variance logvar in the forward propagation process of the underwater electromagnetic wave communication frequency automatic modulation model; (2) Calculate a reasonable loss value representing the training effect: Calculate the divergence: k1=-0.5*(1+logvar-mu^2-(e^logvar)); Calculate the loss between the water frequency modulation data set and the predicted value in the validation data set: loss=L1+k1*k1_weight; Among them, loss is the loss value, k1 is the divergence, k1_weight is the proportion of k1, the value is 10, L1 is the absolute difference between the predicted value and the true value, and the calculation formula of L1 is as follows: ; Among them, A is the L1 loss in pytorch, which calculates the average or sum of the absolute differences between two tensors; the shape of A is N*C*H*W, which indicates that it is a four-dimensional tensor, N represents the number of samples (Batch Size), indicating that there are N data points, C represents the number of channels (Channels), H and W represent the height and width respectively, which are usually the two-dimensional spatial dimensions of the input features; P represents the padding value, which is a Boolean type, and the shape of P is c*h*w*1. The dimensions of P are the same as those of A in terms of channel, height, and width, but there is no sample number N, which means that P is a mask or padding information for a feature map of each sample, and the Boolean value of P may be used to mark whether the elements in A are filled (True) or valid (False).

[0040] (3) The loss value when using the validation data set to validate the current model network; (4) If the validation loss of this round is less than that of the previous round, the best model parameters are replaced with the training model of this round; (5) Put the rounds and loss values ​​into the dictionary one by one; (6) Compare the loss value of the current round with the loss values ​​of the 300 rounds before this round (parameters are provided and can be set according to actual needs, the default is 300), that is, traverse the loss values ​​from epoch-300 to epoch-1 (epoch is the training round, and comparison is performed when epoch is greater than 300). If the loss values ​​of the current round of epoch are all greater than the loss values ​​from (epoch-300) to (epoch-1), stop training.

[0041] (7) Save the best model parameters in the cyclic validation as a ckpt model file.

[0042] Specifically, the determining whether the loss value satisfies the first preset condition, and determining whether to end the training and output the model parameters according to the determination result, includes: If the loss value meets the first preset condition, the training is terminated and the parameters of the current underwater electromagnetic wave communication frequency automatic modulation model are output; if the loss value does not meet the first preset condition, the training is continued.

[0043] Specifically, the first preset condition is: After the second preset round of training, the loss values ​​obtained in the next round of training are greater than or equal to the loss values ​​that occurred during the second preset round of training.

[0044] S300. After the model training is completed, after the submarine position data of the target submarine is obtained by using the sonar detector installed on the surface platform, the distance between the submarine position data and the GPS position information of the underwater buoy is calculated, and the distance is input into the automatic modulation model of the underwater electromagnetic wave communication frequency. According to the predicted electromagnetic wave frequency output by the model, the underwater buoy is controlled to communicate with the target submarine through electromagnetic waves, so that the target submarine obtains the submarine position data. The target submarine plans the navigation path according to the obtained submarine position data.

[0045] It should be noted that the present invention trains the automatic modulation model of electromagnetic wave communication frequency in water. After the model training is completed, after the submarine position data of the target submarine is obtained by using the sonar detector set on the surface platform, the distance between the submarine position data and the GPS position information of the underwater buoy is calculated, and the distance is input into the automatic modulation model of electromagnetic wave communication frequency in water. According to the predicted electromagnetic wave frequency output by the model, the underwater buoy is controlled to communicate with the target submarine through electromagnetic waves, so that the target submarine obtains the submarine position data, and the target submarine performs navigation path planning according to the obtained submarine position data. The automatic modulation of electromagnetic wave communication frequency in water is realized, and the technical problem that the increase of transmission distance and the influence on signal transmission will also increase and it is difficult to reasonably modulate the transmission frequency by threshold calculation is effectively overcome, and the reasonable use of electromagnetic waves is realized to improve the efficiency and accuracy of the submarine's own positioning, thereby greatly improving the positioning and navigation effect of the submarine's navigation system.

[0046] See also Figure 2 The present invention provides another embodiment, which provides a water surface stereoscopic collaborative navigation system, the water surface stereoscopic collaborative navigation system comprising: The acquisition module 100 is used to acquire the GPS position information of the underwater buoy before it is released underwater by using the GPS sensor disposed in the underwater buoy; The control module 200 is used to release the underwater buoy into the water, and after the submarine position data of the submarine is obtained by using the sonar detector set on the surface platform, control the surface platform to use wireless sound waves to send the submarine position data frame to the underwater buoy, and use the underwater buoy to transmit the submarine position data frame to the target submarine according to the preset electromagnetic wave frequency, and the submarine position data frame also records the sending time of the submarine position data frame; record the timestamp of the target submarine receiving the submarine position data frame, calculate the transmission time of the submarine position data frame according to the timestamp and the sending time, and judge whether the transmission time is less than or equal to the first preset threshold value. If not, increase the electromagnetic wave frequency of the next submarine position data frame according to the preset electromagnetic wave frequency interval until the transmission time is less than or equal to the first preset threshold value; calculate the distance between the GPS position information of the underwater buoy and the submarine position data of the target submarine at this time, record the distance and the electromagnetic wave frequency, and form an underwater frequency modulation number The method comprises the steps of: collecting a first preset number of underwater frequency modulation data sets, dividing the collected underwater frequency modulation data sets into a training data set and a verification data set according to a first preset ratio; using the collected training data set to train an underwater electromagnetic wave communication frequency automatic modulation model, using the verification data set to optimize the underwater electromagnetic wave communication frequency automatic modulation model, optimizing the model parameters, and completing the underwater electromagnetic wave communication frequency automatic modulation model training; and calculating the distance between the submarine position data and the GPS position information of the underwater buoy after the submarine position data of the target submarine is obtained by using a sonar detector set on a surface platform after the model training is completed, inputting the distance into the underwater electromagnetic wave communication frequency automatic modulation model, and controlling the underwater buoy to communicate with the target submarine through electromagnetic waves according to the predicted electromagnetic wave frequency output by the model, so that the target submarine obtains the submarine position data, and the target submarine performs navigation path planning according to the obtained submarine position data.

[0047] It can be understood that the present invention trains the automatic modulation model of electromagnetic wave communication frequency in water. After the model training is completed, after the submarine position data of the target submarine is obtained by using the sonar detector set on the surface platform, the distance between the submarine position data and the GPS position information of the underwater buoy is calculated, and the distance is input into the automatic modulation model of electromagnetic wave communication frequency in water. According to the predicted electromagnetic wave frequency output by the model, the underwater buoy is controlled to communicate with the target submarine through electromagnetic waves, so that the target submarine obtains the submarine position data, and the target submarine performs navigation path planning according to the obtained submarine position data. The automatic modulation of electromagnetic wave communication frequency in water is realized, which effectively overcomes the technical problem that the increase in transmission distance will also increase the impact on signal transmission and it is difficult to reasonably modulate the transmission frequency by threshold calculation, and realizes the reasonable use of electromagnetic waves to improve the efficiency and accuracy of the submarine's own positioning, thereby greatly improving the positioning and navigation effect of the submarine's navigation system.

[0048] In a preferred embodiment, the present application further provides an electronic device, the electronic device comprising: A memory; and a processor, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the method for three-dimensional collaborative navigation on the water surface is implemented. The computer device can be broadly a server, a terminal, or any other electronic device with necessary computing and / or processing capabilities. In one embodiment, the computer device may include a processor, a memory, a network interface, a communication interface, etc. connected via a system bus. The processor of the computer device can be used to provide necessary computing, processing and / or control capabilities. The memory of the computer device may include a non-volatile storage medium and an internal memory. An operating system, a computer program, etc. may be stored in or on the non-volatile storage medium. The internal memory can provide an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface and the communication interface of the computer device can be used to connect and communicate with external devices via a network. When the computer program is executed by the processor, the steps of the method of the present invention are performed.

[0049] The present invention may be implemented as a computer-readable storage medium having a computer program stored thereon, which causes the steps of the method of an embodiment of the present invention to be executed when executed by a processor. In one embodiment, the computer program is distributed on a plurality of computer devices or processors coupled to a network so that the computer program is stored, accessed and executed in a distributed manner by one or more computer devices or processors. A single method step / operation, or two or more method steps / operations, may be performed by a single computer device or processor or by two or more computer devices or processors. One or more method steps / operations may be performed by one or more computer devices or processors, and one or more other method steps / operations may be performed by one or more other computer devices or processors. One or more computer devices or processors may perform a single method step / operation, or perform two or more method steps / operations.

[0050] It will be appreciated by a person skilled in the art that the method steps of the present invention may be performed by instructing related hardware such as a computer device or a processor through a computer program, and the computer program may be stored in a non-temporary computer-readable storage medium, which causes the steps of the present invention to be performed when the computer program is executed. Depending on the circumstances, any reference to memory, storage, database, or other media herein may include non-volatile and / or volatile memory. Examples of non-volatile memory include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, magnetic tape, floppy disk, magneto-optical data storage device, optical data storage device, hard disk, solid state disk, etc. Examples of volatile memory include random access memory (RAM), external cache memory, etc.

[0051] It should be noted that the present invention trains the automatic modulation model of electromagnetic wave communication frequency in water. After the model training is completed, after the submarine position data of the target submarine is obtained by using the sonar detector set on the surface platform, the distance between the submarine position data and the GPS position information of the underwater buoy is calculated, and the distance is input into the automatic modulation model of electromagnetic wave communication frequency in water. According to the predicted electromagnetic wave frequency output by the model, the underwater buoy is controlled to communicate with the target submarine through electromagnetic waves, so that the target submarine obtains the submarine position data, and the target submarine performs navigation path planning according to the obtained submarine position data. The automatic modulation of electromagnetic wave communication frequency in water is realized, and the technical problem that the increase of transmission distance and the influence on signal transmission will also increase and it is difficult to reasonably modulate the transmission frequency by threshold calculation is effectively overcome, and the reasonable use of electromagnetic waves is realized to improve the efficiency and accuracy of the submarine's own positioning, thereby greatly improving the positioning and navigation effect of the submarine's navigation system.

[0052] The various technical features described above can be combined arbitrarily. Although all possible combinations of these technical features are not described, any combination of these technical features should be considered to be covered by this specification as long as there is no contradiction in such combination.

[0053] The specific implementation of the present invention described above does not constitute a limitation on the protection scope of the present invention. Any other corresponding changes and modifications made based on the technical concept of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A three-dimensional collaborative navigation method on a water surface, characterized in that: The method comprises: S100, setting a GPS sensor in the underwater buoy, using the GPS sensor set in the underwater buoy to obtain the GPS position information of the underwater buoy before it is released underwater, releasing the underwater buoy into the water, using the sonar detector set on the surface platform to obtain the submarine position data of the submarine, controlling the surface platform to use wireless sound waves to send the submarine position data frame to the underwater buoy, using the underwater buoy to transmit the submarine position data frame to the target submarine according to a preset electromagnetic wave frequency, and the submarine position data frame also records the sending time of the submarine position data frame; recording the timestamp of the target submarine receiving the submarine position data frame, calculating the transmission time of the submarine position data frame according to the timestamp and the sending time, judging whether the transmission time is less than or equal to a first preset threshold value, if not, increasing the electromagnetic wave frequency of the next submarine position data frame according to the preset electromagnetic wave frequency interval until the transmission time is less than or equal to the first preset threshold value; S200, calculating the distance between the GPS position information of the underwater buoy and the submarine position data of the target submarine at this time, recording the distance and the electromagnetic wave frequency, and forming an underwater frequency modulation data set; collecting a first preset number of underwater frequency modulation data sets, and dividing the collected underwater frequency modulation data sets into a training data set and a verification data set according to a first preset ratio; using the collected training data set to train an underwater electromagnetic wave communication frequency automatic modulation model, using the verification data set to optimize the underwater electromagnetic wave communication frequency automatic modulation model, optimizing the model parameters, and completing the underwater electromagnetic wave communication frequency automatic modulation model training; S300. After the model training is completed, after the submarine position data of the target submarine is obtained by using the sonar detector installed on the surface platform, the distance between the submarine position data and the GPS position information of the underwater buoy is calculated, and the distance is input into the automatic modulation model of the underwater electromagnetic wave communication frequency. According to the predicted electromagnetic wave frequency output by the model, the underwater buoy is controlled to communicate with the target submarine through electromagnetic waves, so that the target submarine obtains the submarine position data. The target submarine plans the navigation path according to the obtained submarine position data.

2. The water surface three-dimensional collaborative navigation method according to claim 1, characterized in that: The method of obtaining the submarine position data of the submarine by using the sonar detector arranged on the surface platform includes: The sonar detector installed on the surface platform is used to obtain the submarine position data of the submarine at preset time intervals, and to generate submarine position data frames at preset time intervals.

3. The water surface three-dimensional collaborative navigation method according to claim 1, characterized in that: The method further comprises: If the first transmission time is less than or equal to the first preset threshold, the distance between the initial GPS position information and the submarine position data of the target submarine is calculated, and the distance and the electromagnetic wave frequency are recorded to form an underwater frequency modulation data set.

4. The water surface three-dimensional collaborative navigation method according to claim 1, characterized in that: The method uses the collected training data set to train the underwater electromagnetic wave communication frequency automatic modulation model, uses the verification data set to optimize the underwater electromagnetic wave communication frequency automatic modulation model, optimizes the model parameters, and completes the underwater electromagnetic wave communication frequency automatic modulation model training, including: The training data set is input into the preset network layer in batches for training, and the preset network layer includes a Transformer network layer, and the Transformer network layer is used to predict the next underwater frequency modulation data set based on the forward propagation of the current underwater frequency modulation data set, and then obtain the predicted loss value; the loss value of the preset network layer is calculated and input into the optimizer for optimization, and the direction in which the parameter gradient of the underwater electromagnetic wave communication frequency automatic modulation model decreases fastest is determined; the underwater electromagnetic wave communication frequency automatic modulation model performs back propagation according to the loss value and the parameter gradient of the model, and optimizes the parameters of the underwater electromagnetic wave communication frequency automatic modulation model.

5. The water surface three-dimensional collaborative navigation method according to claim 4, characterized in that: The preset network layer also includes a ResNet network layer, and the ResNet network layer is used to predict the output result according to the collected underwater frequency modulation data set, and the prediction result includes the predicted electromagnetic wave frequency.

6. The water surface three-dimensional collaborative navigation method according to claim 5, characterized in that: The method of using the collected training data set to train the underwater electromagnetic wave communication frequency automatic modulation model, using the verification data set to optimize the underwater electromagnetic wave communication frequency automatic modulation model, optimizing the model parameters, and completing the underwater electromagnetic wave communication frequency automatic modulation model training also includes: After each training, the verification data set is input into the preset network layer of the previous training in batches for model parameter verification, and cyclic training is performed, with the total number of training rounds set to the first preset round; the loss value of the preset network layer is recorded, and it is determined whether the loss value meets the first preset condition, and whether to end the training and output the model parameters based on the judgment result.

7. The method for three-dimensional collaborative navigation on the water surface according to claim 6, characterized in that: The determining whether the loss value satisfies the first preset condition, and determining whether to end the training and output the model parameters according to the determination result, includes: If the loss value meets the first preset condition, the training is terminated and the parameters of the current underwater electromagnetic wave communication frequency automatic modulation model are output; if the loss value does not meet the first preset condition, the training is continued.

8. The water surface three-dimensional collaborative navigation method according to claim 7, characterized in that: The first preset condition is: After the second preset round of training, the loss values ​​obtained in the next round of training are greater than or equal to the loss values ​​that occurred during the second preset round of training.

9. A three-dimensional collaborative navigation system on the water surface, characterized in that: Set up a GPS sensor in an underwater buoy, including: An acquisition module is used to acquire GPS position information of the underwater buoy before it is released underwater using a GPS sensor disposed in the underwater buoy; The control module is used to release the underwater buoy into the water, and after the submarine position data of the submarine is obtained by using the sonar detector set on the surface platform, control the surface platform to use wireless sound waves to send the submarine position data frame to the underwater buoy, and use the underwater buoy to transmit the submarine position data frame to the target submarine according to the preset electromagnetic wave frequency, and the submarine position data frame also records the sending time of the submarine position data frame; record the timestamp of the target submarine receiving the submarine position data frame, calculate the transmission time of the submarine position data frame according to the timestamp and the sending time, and judge whether the transmission time is less than or equal to the first preset threshold value. If not, increase the electromagnetic wave frequency of the next submarine position data frame according to the preset electromagnetic wave frequency interval until the transmission time is less than or equal to the first preset threshold value; calculate the distance between the GPS position information of the underwater buoy and the submarine position data of the target submarine at this time, record the distance and the electromagnetic wave frequency, and form the underwater frequency modulation data The method comprises the steps of: collecting a first preset number of underwater frequency modulation data sets, dividing the collected underwater frequency modulation data sets into a training data set and a verification data set according to a first preset ratio; using the collected training data set to train an underwater electromagnetic wave communication frequency automatic modulation model, and using the verification data set to optimize the underwater electromagnetic wave communication frequency automatic modulation model, optimize the model parameters, and complete the underwater electromagnetic wave communication frequency automatic modulation model training; after the model training is completed, after obtaining the submarine position data of the target submarine by using the sonar detector set on the surface platform, calculating the distance between the submarine position data and the GPS position information of the underwater buoy, inputting the distance into the underwater electromagnetic wave communication frequency automatic modulation model, and controlling the underwater buoy to communicate with the target submarine through electromagnetic waves according to the predicted electromagnetic wave frequency output by the model, so that the target submarine obtains the submarine position data, and the target submarine performs navigation path planning according to the obtained submarine position data.

10. An electronic device, characterized in that: include: Memory; and a processor, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the water surface stereo collaborative navigation method according to any one of claims 1 to 8 is implemented.

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