A multi-mode multi-frequency positioning device and positioning method

Abstract

The present application relates to a multi-mode multi-frequency positioning device, including a Beidou timing module, a multi-mode communication module and a BD3 multi-mode positioning module connected to an embedded microprocessor module; the embedded microprocessor module includes a communication module selection unit that calculates the confidence prediction value of each communication mode through a communication mode selection model, and transmits the generated communication mode selection instruction to the multi-mode communication module according to the confidence prediction value; the differential processing unit performs position calculation on multiple Beidou satellite positioning signals input by the BD3 multi-mode positioning module according to the differential model and the synchronous timing signal obtained by the Beidou timing module to obtain positioning differential data; the filtering processing unit obtains the differential correction amount according to the filtering model and the positioning differential data, and corrects the differential data according to the differential correction amount. Compared with the prior art, the present invention can improve the positioning accuracy of equipment in a complex communication environment of the power system, reduce the equipment maintenance cost, and meet the actual application needs.

Description

Technical Field

[0001] The present application relates to the field of Beidou positioning technology, and in particular to a multi-mode and multi-frequency positioning device and a positioning method. Background Art

[0002] With the steady advancement of communication systems and the gradual construction of power systems, power systems have put forward higher and higher requirements for location accuracy. Traditional location service systems often adopt a strong data center and weak user terminal model, that is, the data center is responsible for receiving the client's original observation data and location information data through the mobile network, and calculating the pseudo-range differential positioning results based on this data and returning them to the client. This solution causes a large amount of data computing business to be concentrated in the data center, and the business pressure of the data center is too high. At the same time, with the increase in the number of terminals, the system performance will decline to a certain extent.

[0003] Although there has been satellite-based augmented positioning services since the launch of the Beidou-3 satellite, the accuracy has been improved along with the increase in the size of the positioning device, which makes it difficult for workers in some scenarios to use and maintain it. In addition, most existing portable positioning devices use a single communication method, lack redundancy, and have low positioning accuracy. Summary of the invention

[0004] Based on this, it is necessary to provide a multi-mode and multi-frequency positioning device and positioning method to address the above technical problems, which can improve the equipment positioning accuracy and reduce the equipment maintenance cost in the complex communication environment of the power system.

[0005] An embodiment of the present invention provides a multi-mode multi-frequency positioning device, the device comprising:

[0006] An embedded microprocessor module, and a Beidou timing module, a multimode communication module and a BD3 multimode positioning module connected to the embedded microprocessor module; the embedded microprocessor module includes a communication module selection unit, a differential processing unit, and a filter processing unit; wherein,

[0007] The communication module selection unit is used to calculate the confidence prediction value of each communication mode through a built-in communication mode selection model, and transmit the generated communication mode selection instruction to the multi-mode communication module according to the confidence prediction value; the communication mode includes a 4G communication mode, a 5G communication mode, and a Beidou short message communication mode;

[0008] The differential processing unit is used to perform position calculation on multiple Beidou satellite positioning signals input by the BD3 multi-mode positioning module according to the built-in differential model and the synchronous timing signal obtained by the Beidou timing module to obtain positioning differential data;

[0009] The filtering processing unit is used to obtain a differential correction amount through a built-in filtering model and the positioning differential data, and to correct the positioning differential data according to the differential correction amount.

[0010] Furthermore, the Beidou timing module includes:

[0011] Beidou timing unit, used to detect erroneous BD3 positioning measurements through the T-RAIM model and output reference second pulse signals;

[0012] Chip-level rubidium atomic clock unit, used to output local second pulse signal;

[0013] The digital phase detector unit is used to obtain a synchronous timing signal based on the reference second pulse signal input by the Beidou timing unit and the local second pulse signal generated by the chip-level rubidium atomic unit.

[0014] Furthermore, the communication module selection unit includes:

[0015] The confidence acquisition subunit is used to obtain the data packet loss situation of various communication modes in real time, define the inverse of the packet loss rate of each selected corresponding communication mode transmission as the confidence value, and obtain the initial confidence value of each communication mode;

[0016] The interference calculation subunit is used to model the electromagnetic interference in the environment of each communication mode as a stable distributed noise model, and input the electromagnetic interference in the environment of the current communication mode into the stable distributed noise model to obtain the electromagnetic interference intensity at the current communication moment;

[0017] The mode determination subunit is used to obtain a confidence prediction value according to the product of the electromagnetic interference intensity and the trust interval at the current communication moment and the historical confidence value, and determine the communication mode at the current communication moment according to the confidence prediction value.

[0018] Furthermore, the differential processing unit includes:

[0019] A correction processing subunit, used for parsing a plurality of Beidou satellite positioning signals input by the BD3 multi-mode positioning module, and eliminating errors of the plurality of Beidou satellite positioning signals passing through the troposphere and the ionosphere, to obtain a corrected Beidou satellite positioning signal;

[0020] The differential processing subunit is used to access the reference station server through the multi-mode communication module to obtain Beidou satellite reference position data, input the corrected Beidou satellite positioning signal and Beidou satellite reference position data into the differential model, and obtain positioning differential data.

[0021] Furthermore, the filtering processing unit includes:

[0022] The differential correction subunit is used to obtain a positioning differential correction number; wherein the positioning differential correction number is the average of the current positioning differential data and the current positioning differential data estimated by the positioning differential data at the previous moment; the estimated current positioning differential data is obtained by multiplying the positioning differential data at the previous moment by the sum of the change rate of the positioning differential data and the time interval of two positioning times;

[0023] The differential sub-unit is used to input the positioning differential correction number into the filtering model to obtain the differential correction value, and correct the positioning differential data according to the differential correction value.

[0024] Furthermore, the filtering model is an LMS filtering model based on a BP neural network, and the loss function of the BP neural network is the variance of each LMS filtering model output value and an input positioning differential correction number.

[0025] Another embodiment of the present invention provides a positioning method of a multi-mode multi-frequency positioning device, which is applied to the multi-mode multi-frequency positioning device as described above. The method includes:

[0026] The confidence prediction value of each communication mode is calculated by the communication mode selection model, and the generated communication mode selection instruction is transmitted to the multi-mode communication module according to the confidence prediction value; the communication mode includes 4G communication mode, 5G communication mode, and Beidou short message communication mode;

[0027] According to the differential model and the synchronous timing signal obtained by the Beidou timing module, the multiple Beidou satellite positioning signals input by the BD3 multi-mode positioning module are position solved to obtain positioning differential data;

[0028] A differential correction amount is obtained through the filtering model and the positioning differential data, and the positioning differential data is corrected according to the differential correction amount.

[0029] Furthermore, the confidence prediction value of each communication mode is calculated by the built-in communication mode selection model, and a communication mode selection instruction is generated according to the confidence prediction value, specifically including:

[0030] Obtain the data packet loss situation of various communication modes in real time, define the inverse of the packet loss rate of each selected communication mode transmission as the confidence value, and obtain the initial confidence value of each communication mode;

[0031] The electromagnetic interference in the environment of each communication mode is modeled as a stable distributed noise model, and the electromagnetic interference in the environment of the current communication mode is input into the stable distributed noise model to obtain the electromagnetic interference intensity at the current communication moment;

[0032] A confidence prediction value is obtained according to the product of the electromagnetic interference intensity and the trust interval at the current communication moment, and the historical confidence value, and the communication mode at the current communication moment is determined according to the confidence prediction value.

[0033] Further, according to the built-in differential model and the synchronous timing signal obtained by the Beidou timing module, the multiple Beidou satellite positioning signals input by the BD3 multi-mode positioning module are position solved to obtain positioning differential data, specifically including:

[0034] Analyze multiple Beidou satellite positioning signals input by the BD3 multi-mode positioning module, and eliminate the errors of the multiple Beidou satellite positioning signals passing through the troposphere and ionosphere to obtain a corrected Beidou satellite positioning signal;

[0035] The reference station server is accessed through the multi-mode communication module to obtain Beidou satellite reference position data, and the corrected Beidou satellite positioning signal and Beidou satellite reference position data are input into the differential model to obtain positioning differential data.

[0036] Furthermore, the positioning differential data is corrected by a built-in filtering model, specifically including:

[0037] Obtaining a positioning differential correction number; wherein the positioning differential correction number is the average of the current positioning differential data and the current positioning differential data estimated from the previous moment positioning differential data; the estimated current positioning differential data is obtained by multiplying the previous moment positioning differential data by the change rate of the positioning differential data and the time interval between two positioning operations;

[0038] The positioning differential correction number is input into the filtering model to obtain a differential correction amount, and the positioning differential data is corrected according to the differential correction amount.

[0039] The above-mentioned multi-mode multi-frequency positioning device includes an embedded microprocessor module, and a Beidou timing module, a multi-mode communication module and a BD3 multi-mode positioning module connected to the embedded microprocessor module; the embedded microprocessor module includes a communication module selection unit, a differential processing unit, and a filtering processing unit; wherein the communication module selection unit calculates the confidence prediction value of each communication mode through a built-in communication mode selection model, and transmits the generated communication mode selection instruction to the multi-mode communication module according to the confidence prediction value; the communication mode includes a 4G communication mode, a 5G communication mode, and a Beidou short message communication mode; the differential processing unit performs position calculation on multiple Beidou satellite positioning signals input by the BD3 multi-mode positioning module according to the built-in differential model and the synchronous timing signal obtained by the Beidou timing module, and obtains positioning differential data; the filtering processing unit obtains a differential correction amount through a built-in filtering model and the positioning differential data, and corrects the positioning differential data according to the differential correction amount. Compared with the prior art, the present invention can improve the positioning accuracy of equipment in a complex communication environment of the power system, reduce the equipment maintenance cost, and meet the actual application needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A structural block diagram of a multi-mode and multi-frequency positioning device provided by an embodiment of the present invention;

[0041] Figure 2 A schematic flow chart of a positioning method for a multi-mode and multi-frequency positioning device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this technical field without creative work are within the scope of protection of the present invention.

[0043] It should be noted that the step numbers in the text are only for the convenience of explaining the specific embodiment and do not limit the order of execution of the steps. The method provided in this embodiment can be executed by a related server, and the following description will be given by taking the server as the execution subject as an example.

[0044] like Figure 1As shown, an embodiment of the present invention provides a multi-mode multi-frequency positioning device, which includes: an embedded microprocessor module, a Beidou timing module, a multi-mode communication module and a BD3 multi-mode positioning module electrically connected to the embedded microprocessor module, and a power supply module for supplying power to the embedded microprocessor module, the Beidou timing module, the multi-mode communication module and the BD3 multi-mode positioning module respectively, and the power supply module is used to provide continuous and stable power supply to the interior of the positioning device.

[0045] Among them, the multi-mode communication module includes a 4G communication module, a 5G communication module and a Beidou short message communication module. The multi-mode communication module is used to select the communication mode instruction issued by the embedded microprocessor module, adopt the corresponding communication mode, upload the location information to the platform, or report the location to other Beidou terminals according to business requirements, and upload the generated location report to the cloud server. At the same time, the multi-mode communication module can also receive communication information sent by the platform, Beidou terminal and cloud service. The BD3 multi-mode positioning module is used to receive the positioning differential data sent from BD3, and then transmit it to the embedded microprocessor module for position solution. The Beidou timing module supports the capture and tracking of all BD3 signal frequencies including B1I, B1C, B1A, B2A, B3I, B3Q, B3A, and B3AE.

[0046] Furthermore, the Beidou timing module includes a Beidou timing unit, a chip-level rubidium atomic clock unit and a digital phase detector unit. The Beidou timing unit has a built-in T-RAIM model, which is used to detect erroneous BD3 positioning measurements through the T-RAIM model, and output a reference second pulse signal with an accuracy of up to 20ns and no cumulative error. The chip-level rubidium atomic clock unit is used to output a local second pulse signal with excellent short-term and long-term stability. Compared with the crystal oscillator, it has better stability and can still have a better timing function in the unlocked state. The digital phase detector unit uses its high phase resolution to obtain the deviation between the reference second pulse signal input by the Beidou timing unit and the local second pulse signal generated by the chip-level rubidium atomic unit, obtain the synchronous timing signal, and then input it into the embedded microprocessor module to ensure the time synchronization between the Beidou satellite signal and the positioning differential data.

[0047] Furthermore, the embedded microprocessor module adopts a dual-core processor with low power consumption, small size and high performance. More specifically, the embedded microprocessor module includes a communication module selection unit, a differential processing unit, and a filter processing unit. The filter processing unit is used to filter the synchronous timing signal input by the digital phase detector through the I / O interface to eliminate the second jitter. At the same time, the filter processing unit is also used to transmit the synchronous timing signal after eliminating the second jitter to the differential processing unit to ensure the time synchronization between the Beidou satellite signal and the positioning differential data.

[0048] The differential processing unit includes a correction processing subunit and a differential processing subunit.

[0049] The correction processing subunit is used to parse the multiple Beidou satellite positioning signals input by the BD3 multi-mode positioning module, and eliminate the errors of the multiple Beidou satellite positioning signals passing through the troposphere and ionosphere to obtain a corrected Beidou satellite positioning signal.

[0050] Specifically, the correction processing subunit analyzes multiple Beidou satellite positioning signals input by the BD3 multi-mode positioning module, and the correction processing subunit contains the Saastamoinen model and the Klobuchar model. The Saastamoinen model approximates the error caused by tropospheric interference as a function related to satellite position, temperature, and air pressure. The Klobuchar model regards the error caused by ionospheric interference in the atmosphere as a cosine function related to time. The two models are used to estimate the interference caused by the current satellite positioning signal in the ionosphere and troposphere, and the error of the received satellite positioning signal is corrected to obtain a corrected Beidou satellite positioning signal.

[0051] The differential processing subunit is used to access the reference station server through the multi-mode communication module to obtain Beidou satellite reference position data, input the corrected Beidou satellite positioning signal and Beidou satellite reference position data into the differential model, and obtain positioning differential data.

[0052] Specifically, the differential processing subunit separates the observation data and the ephemeris file from the positioning data packet carried by the corrected Beidou satellite positioning signal, and then inputs the Beidou satellite reference position data obtained by the multi-mode communication module accessing the reference station server and the observation data into the differential model to obtain the positioning differential data. That is, the differential model subtracts the observation data from the Beidou satellite reference position data to obtain the positioning differential data.

[0053] The filtering processing unit includes a differential correction subunit and a differential division subunit.

[0054] The differential correction subunit is used to obtain the positioning differential correction number. The positioning differential correction number is the average of the current positioning differential data and the current positioning differential data estimated by the previous moment positioning differential data; the estimated current positioning differential data is obtained by multiplying the previous moment positioning differential data by the change rate of the positioning differential data and the time interval between two positionings.

[0055] The differential sub-unit is used to input the positioning differential correction number into the filtering model to obtain the differential correction value, and correct the positioning differential data according to the differential correction value.

[0056] Furthermore, the filtering model is an LMS filtering model based on a BP neural network, and the loss function of the BP neural network is the variance of each output value of the LMS filtering model (filter) and the input positioning differential correction number.

[0057] Specifically, the positioning differential correction numbers of all Beidou satellites are input into the iterative operation of the LMS filter improved based on the BP neural network. Considering the electromagnetic interference in the power system, a stable distributed noise model is used to describe it. It is iterated based on the gradient descent method through the difference between the output and the input. The positioning differential data obtained by actual calculation is set as the target value. In the LMS filtering process, the closer to the estimated target value, the faster the iteration and the more accurate the result. Therefore, the BP neural network is used to improve the LMS, and the output value, target value and input value of the LMS filter in each iteration process are input into the neural network and the correction amount of the test data is output, and then combined with the result after LMS filtering to obtain a filtering estimate with faster iteration speed and higher accuracy.

[0058] Furthermore, the BP neural network structure used to improve the LMS filter in the filtering algorithm unit includes:

[0059] 1. Selection of initial weights of BP neural network.

[0060] The initial value of the BP neural network weight directly affects the performance of the entire neural network. However, since there is currently no definite method to calculate the optimal initial weight, a randomly distributed decimal in the closed interval [-1,1] can be selected as the initial weight.

[0061] 2. Selection of the number of hidden layers and nodes in each layer of the BP neural network.

[0062] Since the three-layer BP neural network can approximate any rational function with arbitrary precision, a three-layer BP neural network is used, and the number of input nodes is determined by the dimension of the input part variables: each iterative LMS filter has 1 output and 1 target value, as well as the input of multiple positioning differential data. Therefore, the number of nodes in the input layer of the designed neural network should be equal to the number of input differential data, the output layer has one node, and the number of hidden layer nodes is the sum of the number of input layer nodes, the number of output layer nodes and the number of target values.

[0063] 3. Update the hidden layer weights of the BP neural network.

[0064] In particular, since the fitting accuracy of the three-layer BP neural network depends on the weight design of each node in the hidden layer, in order to improve the output accuracy of the BP neural network, this patent defines the loss function of the BP neural network as the variance of each LMS filter output value and the input positioning differential correction number. After each LMS output, the loss function is calculated, and based on the obtained loss function, the weight of the hidden layer of the BP neural network is updated according to the gradient descent method, so that the output of the neural network is more accurate.

[0065] Furthermore, the communication module selection unit includes a confidence acquisition subunit, an interference calculation subunit and a mode determination subunit.

[0066] The confidence acquisition subunit is used to obtain the data packet loss situation of various communication modes in real time, define the inverse of the packet loss rate of each selected communication mode transmission as the confidence value, and obtain the initial confidence value of each communication mode. Specifically, 5G, 4G, and Beidou short message communication can be selected for data transmission in turn during the first three transmissions, and the inverse of the data transmission packet loss rate can be obtained to obtain its initial confidence value.

[0067] The interference calculation subunit is used to model the electromagnetic interference in the environment of each communication mode as a stable distributed noise model, and input the electromagnetic interference in the environment of the current communication mode into the stable distributed noise model to obtain the electromagnetic interference intensity at the current communication moment.

[0068] The mode determination subunit is used to obtain a confidence prediction value according to the product of the electromagnetic interference intensity and the trust interval at the current communication moment, and the historical confidence value, and determine the communication mode at the current communication moment according to the confidence prediction value. Specifically, in the process of selecting each communication mode, the trust interval can be pre-multiplied by the electromagnetic interference intensity of the communication mode and added to the historical confidence value. Based on this design, when the electromagnetic interference is more serious, it tends to explore other communication modes, and when the electromagnetic interference is smaller, it tends to use the current communication mode for transmission, so as to achieve a dynamic balance between exploration and utilization, so as to ensure that the packet loss rate during the communication process is always kept at a low level under the influence of strong electromagnetic interference in the power system.

[0069] It can be understood that in other embodiments, after obtaining the initial confidence value, the average confidence value of each communication mode up to the current selection process can be calculated, and then the average confidence value and the average information value of each communication mode in the past are combined, and the confidence prediction value is calculated by the average confidence value and the inverse of the number of past communication mode selections; when the confidence prediction value of the communication mode selected last time is the largest, this communication mode is still selected for transmission; when the confidence prediction value of the communication mode selected last time is not the largest, the communication mode with the maximum confidence prediction value is switched for transmission, and the confidence value of the communication mode selected this time is updated.

[0070] The multi-mode multi-frequency positioning device provided by the present invention comprises an embedded microprocessor module, and a Beidou timing module, a multi-mode communication module and a BD3 multi-mode positioning module connected to the embedded microprocessor module; the embedded microprocessor module comprises a communication module selection unit, a differential processing unit, and a filtering processing unit; wherein the communication module selection unit calculates the confidence prediction value of each communication mode through a built-in communication mode selection model, and transmits the generated communication mode selection instruction to the multi-mode communication module according to the confidence prediction value; the communication mode comprises a 4G communication mode, a 5G communication mode, and a Beidou short message communication mode; the differential processing unit performs position calculation on a plurality of Beidou satellite positioning signals input by the BD3 multi-mode positioning module according to the built-in differential model and the synchronous timing signal obtained by the Beidou timing module, and obtains positioning differential data; the filtering processing unit obtains a differential correction amount through the built-in filtering model and the positioning differential data, and corrects the positioning differential data according to the differential correction amount. Compared with the prior art, the present invention can improve the positioning accuracy of equipment in a complex communication environment of the power system, reduce equipment maintenance costs, and meet practical application needs.

[0071] See also Figure 2 The present invention also provides a positioning method for a multi-mode multi-frequency positioning device, which is applied to the above-mentioned multi-mode multi-frequency positioning device. The device includes: an embedded microprocessor module, a Beidou timing module, a multi-mode communication module and a BD3 multi-mode positioning module electrically connected to the embedded microprocessor module, and a power supply module for supplying power to the embedded microprocessor module, the Beidou timing module, the multi-mode communication module and the BD3 multi-mode positioning module respectively, and the power supply module is used to provide continuous and stable power supply to the inside of the positioning device.

[0072] Among them, the multi-mode communication module includes a 4G communication module, a 5G communication module and a Beidou short message communication module. The multi-mode communication module is used to select the communication mode according to the communication mode selection instruction issued by the embedded microprocessor module, adopt the corresponding communication mode, upload the location information to the platform, or report the location to other Beidou terminals according to business requirements, and upload the generated location report to the cloud server. At the same time, the multi-mode communication module can also receive communication information sent by the platform, Beidou terminals and cloud services. The BD3 multi-mode positioning module is used to receive the positioning differential data sent from BD3, and then transmit it to the embedded microprocessor module for high-precision position solution. The Beidou timing module supports the capture and tracking of all BD3 signal frequencies including B1I, B1C, B1A, B2A, B3I, B3Q, B3A, and B3AE. The method includes:

[0073] Step S21, calculating the confidence prediction value of each communication mode through the communication mode selection model, and transmitting the generated communication mode selection instruction to the multi-mode communication module according to the confidence prediction value. Wherein, the communication mode includes 4G communication mode, 5G communication mode, and Beidou short message communication mode.

[0074] Specifically, calculating the confidence prediction value of each communication mode through the communication mode selection model, and transmitting the generated communication mode selection instruction to the multi-mode communication module according to the confidence prediction value includes:

[0075] Obtain the data packet loss situation of various communication modes in real time, define the inverse of the packet loss rate of each selected communication mode transmission as the confidence value, and obtain the initial confidence value of each communication mode;

[0076] The electromagnetic interference in the environment of each communication mode is modeled as a stable distributed noise model, and the electromagnetic interference in the environment of the current communication mode is input into the stable distributed noise model to obtain the electromagnetic interference intensity at the current communication moment;

[0077] A confidence prediction value is obtained according to the product of the electromagnetic interference intensity and the trust interval at the current communication moment, and the historical confidence value, and the communication mode at the current communication moment is determined according to the confidence prediction value.

[0078] Furthermore, in each communication mode selection process, the trust interval can be multiplied by the electromagnetic interference strength of the communication mode and added to the historical confidence value. Based on this design, when the electromagnetic interference is more serious, it tends to explore other communication modes, and when the electromagnetic interference is smaller, it tends to use the current communication mode for transmission, achieving a dynamic balance between exploration and utilization, so as to ensure that the packet loss rate in the communication process is always kept at a low level under the influence of strong electromagnetic interference in the power system.

[0079] It can be understood that in other embodiments, after obtaining the initial confidence value, the average confidence value of each communication mode up to the current selection process can be calculated, and then the average confidence value and the average information value of each communication mode in the past are combined, and the confidence prediction value is calculated by the average confidence value and the inverse of the number of past communication mode selections; when the confidence prediction value of the communication mode selected last time is the largest, this communication mode is still selected for transmission; when the confidence prediction value of the communication mode selected last time is not the largest, the communication mode with the maximum confidence prediction value is switched for transmission, and the confidence value of the communication mode selected this time is updated.

[0080] Step S22, based on the differential model and the synchronous timing signal obtained by the Beidou timing module, the positions of the multiple Beidou satellite positioning signals input by the BD3 multi-mode positioning module are solved to obtain positioning differential data.

[0081] Among them, the acquisition of synchronous timing signals includes: detecting erroneous BD3 positioning measurements through the T-RAIM model built into the Beidou timing unit, and outputting a reference second pulse signal with an accuracy of up to 20ns and no cumulative error. The chip-level rubidium atomic clock unit outputs a local second pulse signal with excellent short-term and long-term stability, which has better stability than the crystal oscillator and can still have a high-precision timing function in the unlocked state. The digital phase detector unit uses its high phase resolution to obtain the deviation between the reference second pulse signal input by the Beidou timing unit and the local second pulse signal generated by the chip-level rubidium atomic unit, and obtains a synchronous timing signal, which is then input into the embedded microprocessor module to ensure the time synchronization between the Beidou satellite signal and the positioning differential data.

[0082] Specifically, according to the differential model and the synchronous timing signal obtained by the Beidou timing module, the multiple Beidou satellite positioning signals input by the BD3 multi-mode positioning module are position solved to obtain the positioning differential data including:

[0083] Analyze multiple Beidou satellite positioning signals input by the BD3 multi-mode positioning module, and eliminate the errors of the multiple Beidou satellite positioning signals passing through the troposphere and ionosphere to obtain a corrected Beidou satellite positioning signal;

[0084] The reference station server is accessed through the multi-mode communication module to obtain Beidou satellite reference position data, and the corrected Beidou satellite positioning signal and Beidou satellite reference position data are input into the differential model to obtain positioning differential data.

[0085] Step S23, obtaining a differential correction amount through the filtering model and the positioning differential data, and correcting the positioning differential data according to the differential correction amount.

[0086] Specifically, a positioning differential correction number is obtained; wherein the positioning differential correction number is the average of the current positioning differential data and the current positioning differential data estimated by the positioning differential data at the previous moment; the estimated current positioning differential data is obtained by multiplying the positioning differential data at the previous moment by the change rate of the positioning differential data and the time interval of two positioning times;

[0087] The positioning differential correction number is input into the filtering model to obtain a differential correction amount, and the positioning differential data is corrected according to the differential correction amount.

[0088] The filtering model is an LMS filtering model based on a BP neural network, and the loss function of the BP neural network is the variance between the output value of each LMS filtering model and the input positioning differential correction number.

[0089] The positioning method of the multi-mode multi-frequency positioning device provided by the present invention calculates the confidence prediction value of each communication mode through the communication mode selection model, and transmits the generated communication mode selection instruction to the multi-mode communication module according to the confidence prediction value; the communication mode includes 4G communication mode, 5G communication mode, and Beidou short message communication mode; according to the differential model and the synchronous timing signal obtained by the Beidou timing module, the position of the multiple Beidou satellite positioning signals input by the BD3 multi-mode positioning module is solved to obtain positioning differential data; through the filtering model and the positioning differential data, the differential correction amount is obtained, and the positioning differential data is corrected according to the differential correction amount. Compared with the prior art, the present invention can improve the positioning accuracy of the equipment in the complex communication environment of the power system, reduce the equipment maintenance cost, and meet the actual application needs.

[0090] It should be understood that, although the various steps in the above-mentioned flow chart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the above-mentioned flow chart may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0091] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A multi-mode multi-frequency positioning device, characterized in that: The device comprises: An embedded microprocessor module, and a Beidou timing module, a multimode communication module and a BD3 multimode positioning module connected to the embedded microprocessor module; the embedded microprocessor module includes a communication module selection unit, a differential processing unit, and a filter processing unit; wherein, The communication module selection unit is used to calculate the confidence prediction value of each communication mode through the built-in communication mode selection model, and transmit the generated communication mode selection instruction to the multi-mode communication module according to the confidence prediction value; the communication mode includes a 4G communication mode, a 5G communication mode, and a Beidou short message communication mode; wherein the communication module selection unit includes: The confidence acquisition subunit is used to obtain the data packet loss situation of various communication modes in real time, define the inverse of the packet loss rate of each selected corresponding communication mode transmission as the confidence value, and obtain the initial confidence value of each communication mode; The interference calculation subunit is used to model the electromagnetic interference in the environment of each communication mode as a stable distributed noise model, and input the electromagnetic interference in the environment of the current communication mode into the stable distributed noise model to obtain the electromagnetic interference intensity at the current communication moment; A mode determination subunit, configured to obtain a confidence prediction value according to the product of the electromagnetic interference intensity and the trust interval at the current communication moment and the historical confidence value, and determine the communication mode at the current communication moment according to the confidence prediction value; The differential processing unit is used to perform position calculation on multiple Beidou satellite positioning signals input by the BD3 multi-mode positioning module according to the built-in differential model and the synchronous timing signal obtained by the Beidou timing module to obtain positioning differential data; wherein the differential processing unit includes: A correction processing subunit, used for parsing a plurality of Beidou satellite positioning signals input by the BD3 multi-mode positioning module, and eliminating errors of the plurality of Beidou satellite positioning signals passing through the troposphere and the ionosphere, to obtain a corrected Beidou satellite positioning signal; The differential processing subunit is used to access the reference station server through the multi-mode communication module to obtain Beidou satellite reference position data, input the corrected Beidou satellite positioning signal and the Beidou satellite reference position data into the differential model, and obtain positioning differential data; The filtering processing unit is used to obtain a differential correction amount through a built-in filtering model and the positioning differential data, and to correct the positioning differential data according to the differential correction amount; wherein the filtering processing unit includes: The differential correction subunit is used to obtain a positioning differential correction number; wherein the positioning differential correction number is the average of the current positioning differential data and the current positioning differential data estimated by the positioning differential data at the previous moment; the estimated current positioning differential data is obtained by multiplying the positioning differential data at the previous moment by the sum of the change rate of the positioning differential data and the time interval of two positioning times; The differential sub-unit is used to input the positioning differential correction number into the filtering model to obtain the differential correction value, and correct the positioning differential data according to the differential correction value.

2. The multi-mode multi-frequency positioning device according to claim 1, characterized in that: The Beidou timing module includes: Beidou timing unit, used to detect erroneous BD3 positioning measurements through the T-RAIM model and output reference second pulse signals; Chip-level rubidium atomic clock unit, used to output local second pulse signal; The digital phase detector unit is used to obtain a synchronous timing signal based on the reference second pulse signal input by the Beidou timing unit and the local second pulse signal generated by the chip-level rubidium atomic unit.

3. The multi-mode multi-frequency positioning device according to claim 1, characterized in that: The filtering model is an LMS filtering model based on a BP neural network, and the loss function of the BP neural network is the variance between the output value of each LMS filtering model and the input positioning differential correction number.

4. A positioning method for a multi-mode multi-frequency positioning device, characterized in that: Applied to the multi-mode multi-frequency positioning device according to any one of claims 1 to 3, the method comprises: The confidence prediction value of each communication mode is calculated by the communication mode selection model, and the generated communication mode selection instruction is transmitted to the multi-mode communication module according to the confidence prediction value; the communication mode includes 4G communication mode, 5G communication mode, and Beidou short message communication mode; According to the differential model and the synchronous timing signal obtained by the Beidou timing module, the multiple Beidou satellite positioning signals input by the BD3 multi-mode positioning module are position solved to obtain positioning differential data; A differential correction amount is obtained through the filtering model and the positioning differential data, and the positioning differential data is corrected according to the differential correction amount.

5. The positioning method of the multi-mode multi-frequency positioning device according to claim 4, characterized in that: The confidence prediction value of each communication mode is calculated by the built-in communication mode selection model, and a communication mode selection instruction is generated according to the confidence prediction value, specifically including: Obtain the data packet loss situation of various communication modes in real time, define the inverse of the packet loss rate of each selected communication mode transmission as the confidence value, and obtain the initial confidence value of each communication mode; The electromagnetic interference in the environment of each communication mode is modeled as a stable distributed noise model, and the electromagnetic interference in the environment of the current communication mode is input into the stable distributed noise model to obtain the electromagnetic interference intensity at the current communication moment; A confidence prediction value is obtained according to the product of the electromagnetic interference intensity and the trust interval at the current communication moment, and the historical confidence value, and the communication mode at the current communication moment is determined according to the confidence prediction value.

6. The positioning method of the multi-mode multi-frequency positioning device according to claim 4, characterized in that: According to the built-in differential model and the synchronous timing signal obtained by the Beidou timing module, the multiple Beidou satellite positioning signals input by the BD3 multi-mode positioning module are position solved to obtain positioning differential data, which specifically includes: Analyze multiple Beidou satellite positioning signals input by the BD3 multi-mode positioning module, and eliminate the errors of the multiple Beidou satellite positioning signals passing through the troposphere and ionosphere to obtain a corrected Beidou satellite positioning signal; The reference station server is accessed through the multi-mode communication module to obtain Beidou satellite reference position data, and the corrected Beidou satellite positioning signal and Beidou satellite reference position data are input into the differential model to obtain positioning differential data.

7. The positioning method of the multi-mode multi-frequency positioning device according to claim 4, characterized in that: The positioning differential data is corrected by a built-in filtering model, specifically including: Obtaining a positioning differential correction number; wherein the positioning differential correction number is the average of the current positioning differential data and the current positioning differential data estimated from the previous moment positioning differential data; the estimated current positioning differential data is obtained by multiplying the previous moment positioning differential data by the change rate of the positioning differential data and the time interval between two positioning operations; The positioning differential correction number is input into the filtering model to obtain a differential correction amount, and the positioning differential data is corrected according to the differential correction amount.

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