Method, device and storage medium for generating a motion trajectory of a mobile communication terminal

Abstract

The application discloses a mobile communication terminal motion trajectory generation method and device and a storage medium, and relates to the technical field of satellite communication. The method comprises the following steps: determining a time sequence signal frame sequence corresponding to a mobile communication terminal; performing clustering on the time sequence signal frame sequence according to an unsupervised clustering algorithm, and dividing independent signal frames with continuous emission time and a frequency change amount less than a preset threshold into a same signal frame subclass; constructing a nonlinear overdetermined equation set according to the signal frame subclass, wherein the nonlinear overdetermined equation set is used for representing Doppler frequency shift between a corresponding mobile communication terminal and a low-orbit satellite; determining an instantaneous position of the mobile communication terminal corresponding to the signal frame subclass according to the nonlinear overdetermined equation set; and generating a motion trajectory of the mobile communication terminal according to the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass. Thus, the application realizes multi-terminal signal automatic sorting and mobile communication terminal tracking under the conditions of no network control and no power supply.

Description

Technical Field

[0001] This application relates to the field of satellite communication technology, and in particular to a method, apparatus and storage medium for generating motion trajectories of a mobile communication terminal. Background Technology

[0002] Currently, mobile communication terminal trajectory tracking in low-Earth orbit satellite communication systems typically employs a multi-satellite collaborative approach. This involves demodulating satellite downlink network control signals to obtain information such as the terminal's nominal frequency, terminal identifier, and time slot planning, thereby reconstructing its motion trajectory. Some passive tracking solutions, on the other hand, deploy multiple sets of receiving equipment to passively receive uplink signals from the terminal for positioning.

[0003] For example, the invention disclosed in CN113114342A, entitled "Adaptive Position Management Method for Satellite Communication Oriented to Typical Mobility Characteristics," comprises the following steps: a mobile user constructs, updates, and continuously monitors a list of mobile trajectories to determine whether it has entered a reciprocating or habitual trajectory state; the mobile user sends a reciprocating beam / habitual trajectory binding request to the gateway station; the gateway station binds the beam contained in the request information to the mobile user and sends a binding confirmation message to the mobile user; after receiving the binding confirmation message, the mobile user no longer sends position update requests within the bound beam; when the mobile user enters a beam outside the bound beam, it sends a beam unbinding request to the gateway station; the gateway station unbinds the mobile user's beam and sends an unbinding confirmation message.

[0004] For example, CN114095107A, entitled "Switching Simulation Method, Apparatus and Simulation System for Satellite Mobile Communication System," describes a method comprising: acquiring measurement data of a communication terminal moving along a trajectory to obtain a handover test data set, wherein the trajectory is located within the overlapping coverage area of ​​multiple satellite beams, and the measurement data includes the received power and / or signal-to-interference-plus-noise ratio of pilot signals transmitted by multiple satellite beams; processing the handover test data set to obtain a handover test dataset, wherein the handover test dataset includes multiple data sets, and each data set is a subset of the handover test data set; and triggering satellite beam switching based on the handover test dataset to complete the handover simulation.

[0005] However, the aforementioned existing technologies still have the following drawbacks: First, trajectory tracking relies on network control signals for assistance. When the network control signals are encrypted, interfered with, or blocked, the trajectory tracking function will fail. It has weak anti-interference capabilities and cannot adapt to scenarios without network control. Second, the existing passive non-network control solution requires the deployment of multiple sets of receiving equipment, which results in high hardware costs and cannot solve the signal sorting problem when multiple terminals in the airspace transmit simultaneously, making it difficult to distinguish the terminal affiliation of each signal frame. Third, it lacks the ability to blindly estimate the nominal frequency, requiring the preset frequency range or reliance on additional frequency measurement equipment, thus limiting its applicability. Fourth, the segmented calculation and trajectory verification mechanism for the motion process of mobile communication terminals is imperfect, which can easily lead to excessive trajectory deviation, discontinuous trajectory, and insufficient positioning accuracy.

[0006] There are currently no effective solutions to the technical problems of reliance on network control signals, difficulty in sorting signals from multiple terminals, and insufficient trajectory accuracy in the existing technologies mentioned above. Summary of the Invention

[0007] The embodiments of this disclosure provide a method, apparatus, and storage medium for generating motion trajectories of a mobile communication terminal, so as to at least solve the technical problems of dependence on network control signals, difficulty in multi-terminal signal sorting, and insufficient trajectory accuracy in the prior art.

[0008] According to one aspect of the present disclosure, a method for generating the motion trajectory of a mobile communication terminal is provided, comprising: determining a time-series signal frame sequence corresponding to the mobile communication terminal; clustering the time-series signal frame sequence according to an unsupervised clustering algorithm, dividing independent signal frames with continuous transmission times and frequency changes less than a preset threshold into the same signal frame subclass; constructing a nonlinear overdetermined equation set according to the signal frame subclass, wherein the nonlinear overdetermined equation set is used to represent the Doppler frequency shift between the corresponding mobile communication terminal and a low-orbit satellite; determining the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass according to the nonlinear overdetermined equation set; and generating the motion trajectory of the mobile communication terminal according to the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass.

[0009] According to another aspect of the present disclosure, a storage medium is also provided, the storage medium including a stored program, wherein, when the program is executed, a processor performs any of the methods described above.

[0010] According to another aspect of the present disclosure, a motion trajectory generation device for a mobile communication terminal is also provided, comprising: a timing signal frame sequence determination module, configured to determine a timing signal frame sequence corresponding to the mobile communication terminal; a clustering module, configured to cluster the timing signal frame sequence according to an unsupervised clustering algorithm, dividing independent signal frames with continuous transmission times and frequency changes less than a preset threshold into the same signal frame subclass; an equation system construction module, configured to construct a nonlinear overdetermined equation system based on the signal frame subclass, wherein the nonlinear overdetermined equation system is used to represent the Doppler frequency shift between the corresponding mobile communication terminal and a low-orbit satellite; an instantaneous position determination module, configured to determine the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass based on the nonlinear overdetermined equation system; and a motion trajectory generation module, configured to generate the motion trajectory of the mobile communication terminal based on the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass.

[0011] According to another aspect of the present disclosure, a motion trajectory generation apparatus for a mobile communication terminal is also provided, comprising: a processor; and a memory connected to the processor, configured to provide the processor with instructions for processing the following steps: determining a sequence of time-series signal frames corresponding to the mobile communication terminal; clustering the sequence of time-series signal frames according to an unsupervised clustering algorithm, dividing independent signal frames with continuous transmission times and frequency variations less than a preset threshold into the same signal frame subclass; constructing a nonlinear overdetermined equation set based on the signal frame subclass, wherein the nonlinear overdetermined equation set is used to represent the Doppler frequency shift between the corresponding mobile communication terminal and a low-orbit satellite; determining the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass based on the nonlinear overdetermined equation set; and generating the motion trajectory of the mobile communication terminal based on the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass.

[0012] This application uses time-domain energy detection to segment independent signal frames from the uplink radio frequency signal transmitted by the communication terminal. Then, using an unsupervised clustering algorithm, independent signal frames belonging to the same communication terminal are grouped into the same terminal category, thus identifying all independent signal frames belonging to the target communication terminal without any network control information. These frames are then sorted by transmission time to form a time-series signal frame sequence. For mobile communication terminals, this application further employs a time-series unsupervised clustering algorithm to divide independent signal frames with continuous timing and frequency variations less than a preset threshold into the same signal frame subclass. Each signal frame subclass corresponds to a time period in which the mobile communication terminal's position is approximately constant. Next, based on the measured frequencies of each independent signal frame within each signal frame subclass and the corresponding satellite ephemeris, a nonlinear overdetermined equation system is established, combined with the Doppler pre-compensation rule before the mobile communication terminal's transmission. Simultaneously, this system is combined with Earth spherical constraints, and the LM iterative algorithm is used to solve the nonlinear overdetermined equation system, thereby obtaining the estimated instantaneous position and nominal frequency of the signal frame subclass. Furthermore, the instantaneous positions of all valid signal frame subclasses are sorted by time and converted into latitude and longitude coordinates, and motion trajectories are generated through linear or smooth fitting. Finally, the trajectory is verified by utilizing the consistency of the nominal frequency estimates of each valid signal frame subclass, and abnormal valid signal frame subclasses are removed before regenerating the trajectory.

[0013] This application thus achieves automatic signal sorting of multiple terminals and tracking of mobile communication terminals under conditions of no network control and no passive operation. It further solves the technical problems of reliance on network control signals, difficulties in multi-terminal signal sorting, and insufficient trajectory accuracy in existing technologies. Attached Figure Description

[0014] The accompanying drawings, which are included to provide a further understanding of this disclosure and form part of this application, illustrate exemplary embodiments of this disclosure and are used to explain this disclosure, but do not constitute an undue limitation of this disclosure. In the drawings: Figure 1This is a schematic diagram of the motion trajectory generation system of a mobile communication terminal according to Embodiment 1 of this disclosure; Figure 2 This is a hardware structure block diagram of a positioning station according to the motion trajectory generation method of a mobile communication terminal as described in Embodiment 1 of this disclosure; Figure 3 This is a flowchart illustrating the motion trajectory generation method for a mobile communication terminal according to Embodiment 1 of this disclosure; Figure 4 This is a schematic diagram of the motion trajectory generation device for a mobile communication terminal according to Embodiment 2 of this disclosure; Figure 5 This is a schematic diagram of a motion trajectory generation device for a mobile communication terminal according to Embodiment 3 of this disclosure. Detailed Implementation

[0015] To enable those skilled in the art to better understand the technical solutions of this disclosure, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this disclosure.

[0016] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0017] Example 1

[0018] According to this embodiment, a method for generating the motion trajectory of a mobile communication terminal is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0019] Figure 1A schematic diagram of a motion trajectory generation system for a mobile communication terminal according to this embodiment is shown. The system includes a low-Earth orbit (LEO) satellite 10, a mobile communication terminal 20, and a positioning station 30. The LEO satellite 10 orbits the Earth at high speed along a predetermined orbit, and its position and velocity at any given time are known ephemeris information. Before transmitting uplink radio frequency (RF) signals, the mobile communication terminal 20 calculates the Doppler frequency shift based on the real-time position and velocity of the LEO satellite 10 and performs Doppler frequency pre-compensation on the uplink RF signal to ensure that the uplink RF signal can be correctly received by the LEO satellite 10. The positioning station 30 is a single-station passive broadband receiving device used to detect uplink RF signals transmitted by all communication terminals (including stationary communication terminals and mobile communication terminal 20) within the airspace. Furthermore, the positioning station 30 performs time-domain energy detection, RF fingerprint clustering and sorting, and constructs a time-series signal frame sequence for the received uplink RF signals. Based on the calculated instantaneous position of the mobile communication terminal 20 in each signal frame sub-class time period, the motion trajectory of the mobile communication terminal 20 is generated, and the nominal frequency of the mobile communication terminal 20 is determined at the same time.

[0020] In addition, the positioning station 30 is unable to demodulate the downlink network control signals sent by the low-orbit satellite 10, nor can it obtain the nominal frequency, terminal identifier, and time slot planning information of the communication terminal.

[0021] Figure 2 Further shown Figure 1 A schematic diagram of the hardware architecture of the positioning station 30. (Reference) Figure 2 As shown, the positioning station 30 may include one or more processors (processors may include, but are not limited to, microprocessors such as MCUs or programmable logic devices such as FPGAs), a memory for storing data, a transmission device for communication functions, and an input / output interface. The memory, transmission device, and input / output interface are connected to the processor via a bus. In addition, it may also include a display, keyboard, and cursor control device connected to the input / output interface. Those skilled in the art will understand that... Figure 2 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, the ground system may also include... Figure 2 The more or fewer components shown, or having the same Figure 2 The different configurations shown.

[0022] It should be noted that, Figure 2One or more processors and / or other data processing circuits shown herein may generally be referred to as "data processing circuitry". This data processing circuitry may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuitry may be a single, independent processing module, or may be integrated, in whole or in part, into any other element in a computing device. As involved in embodiments of this disclosure, the data processing circuitry serves as processor control (e.g., selection of a variable resistor termination path connected to an interface).

[0023] Figure 2 The memory shown can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the motion trajectory generation method of the mobile communication terminal in this embodiment of the present disclosure. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, to implement the low-orbit satellite positioning method for the mobile communication terminal described above. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory.

[0024] It should be noted here that, in some optional embodiments, the above... Figure 2 The device shown may include hardware elements (including circuitry), software elements (including computer code stored on a computer-readable medium), or a combination of both hardware and software elements. It should be noted that... Figure 2 This is only one instance of a specific particular instance, and is intended to illustrate the types of components that may exist in the aforementioned devices.

[0025] Under the aforementioned operating environment, according to the first aspect of this embodiment, a method for generating a motion trajectory of a mobile communication terminal is provided. This method comprises... Figure 2 The positioning station 30 shown is implemented. Figure 3 A flowchart illustrating the method is shown below. (Refer to...) Figure 3 As shown, the method includes: S302: Determine the timing signal frame sequence corresponding to the mobile communication terminal; S304: Based on the unsupervised clustering algorithm, the time sequence signal frame sequence is clustered, and independent signal frames with continuous transmission time and frequency change less than a preset threshold are divided into the same signal frame subclass. S306: Construct a set of nonlinear overdetermined equations based on the signal frame subclass, where the set of nonlinear overdetermined equations is used to represent the Doppler frequency shift between the corresponding mobile communication terminal and the low-orbit satellite; S308: Determine the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass based on the nonlinear overdetermined equations. S310: Generate the motion trajectory of the mobile communication terminal based on the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass.

[0026] Specifically, the positioning station 30 can base its positioning on all independent signal frames transmitted by the m-th mobile communication terminal 20. ~ Generate a sequence of time-ordered signal frames corresponding to the mobile communication terminal 20. (Corresponding to step S302). Where k is the total number of independent signal frames of a single mobile communication terminal 20.

[0027] Specifically, positioning station 30 first analyzes all independent signal frames transmitted by the communication terminal obtained from time-domain segmentation. ~ (where n is the total number of all independent signal frames, n>k), obtain the independent signal frames. ~ Corresponding radio frequency fingerprint feature vector ~ Then, the positioning station 30 uses an unsupervised clustering algorithm (such as the DBSCAN algorithm or the K-Means algorithm) to analyze the radio frequency fingerprint feature vector. ~ The first cluster analysis will be performed. The method for the first cluster analysis will be explained later.

[0028] Then, based on the results of the first cluster analysis, the positioning station 30 divides the independent signal frames transmitted by the same communication terminal into the same terminal category, where each terminal category uniquely corresponds to a communication terminal (including stationary communication terminals and mobile communication terminals 20).

[0029] Next, the positioning station 30 sorts all independent signal frames belonging to the same mobile communication terminal category in ascending order according to the transmission time of each independent signal frame (i.e., the start time recorded when the independent signal frame is cut in the time domain), thereby forming a time-series signal frame sequence corresponding to the mobile communication terminal 20.

[0030] Furthermore, since the position of the mobile communication terminal 20 changes over time, if the positioning station 30 directly performs overall positioning calculation on all independent signal frames transmitted by the mobile communication terminal 20, the positioning error will be too large due to the positional changes of the mobile communication terminal 20. Therefore, the positioning station 30 needs to perform a second clustering analysis on the time-series signal frame sequence corresponding to the mobile communication terminal 20 using an unsupervised clustering algorithm. Then, based on the results of the second clustering analysis, the positioning station 30 divides independent signal frames with continuous transmission times and frequency variations less than a preset threshold into the same signal frame subclass (corresponding to step 304). Each signal frame subclass corresponds to a segment in which the position of the mobile communication terminal 20 is approximately constant for a very short period of time.

[0031] It should be noted that the frequency change is the difference between the measured frequencies of adjacent independent signal frames. Since the frequency change is related to the radial movement speed of the mobile communication terminal 20, when the frequency change is less than the preset threshold, it indicates that the position change of the mobile communication terminal 20 is very small during that period and can be approximated as constant.

[0032] Next, the positioning station 30 establishes observation equations for each signal frame subclass. Then, the positioning station 30 simultaneously solves the observation equations corresponding to all independent signal frames within the signal frame subclass to construct a set of nonlinear overdetermined equations. This set of nonlinear overdetermined equations is used to represent the Doppler frequency shift relationship between the mobile communication terminal 20 and the low-Earth orbit satellite 10 (corresponding to step 306).

[0033] Subsequently, the positioning station 30 numerically solves the nonlinear overdetermined equations to determine the instantaneous position of the mobile communication terminal 20 corresponding to each signal frame subclass, and simultaneously determines its nominal frequency (corresponding to step 308). The solution process for the nonlinear overdetermined equations will be explained later.

[0034] Finally, since the mobile communication terminal 20 will pass through multiple consecutive signal frame subclass periods during its movement, and each signal frame subclass provides an approximately static instantaneous position, the positioning station 30 needs to connect these discrete instantaneous positions in chronological order to form a complete motion trajectory of the mobile communication terminal 20 (corresponding to step 310).

[0035] As described in the background section, the existing trajectory tracking technology for mobile communication terminals 20 in low-Earth orbit satellite communication systems still has the following shortcomings: First, trajectory tracking relies on network control signals for assistance. When the network control signals are encrypted, interfered with, or blocked, the trajectory tracking function fails, resulting in weak anti-interference capabilities and an inability to adapt to scenarios without network control. Second, existing passive solutions without network control require the deployment of multiple sets of receiving equipment, leading to high hardware costs. Furthermore, they cannot solve the signal sorting problem when multiple terminals simultaneously transmit in the airspace, making it difficult to distinguish the terminal affiliation of each signal frame. Third, they lack the ability to blindly estimate the nominal frequency, requiring preset frequency ranges or reliance on additional frequency measurement equipment, thus limiting their applicability. Fourth, the segmented calculation and trajectory verification mechanism for the movement process of the mobile communication terminal 20 is imperfect, easily leading to excessive trajectory deviation, discontinuous trajectories, and insufficient positioning accuracy.

[0036] In view of this, this application segments independent signal frames from the uplink radio frequency signals transmitted by the communication terminal through time-domain energy detection. Then, using an unsupervised clustering algorithm, independent signal frames transmitted by the same communication terminal are grouped into the same terminal category, thereby sorting out all independent signal frames belonging to the target communication terminal without any network control information, and forming a time-series signal frame sequence according to the transmission time. For mobile communication terminals, this application further employs a time-series unsupervised clustering algorithm to divide independent signal frames with continuous time sequence and frequency variation less than a preset threshold into the same signal frame subclass, with each signal frame subclass corresponding to a time period in which the mobile communication terminal's position is approximately constant. Next, based on the measured frequency of each independent signal frame within each signal frame subclass and the corresponding satellite ephemeris, a nonlinear overdetermined equation system is established in conjunction with the Doppler pre-compensation rule before the mobile communication terminal's transmission. Simultaneously, combined with the Earth's spherical constraints, the LM iterative algorithm is used to solve the nonlinear overdetermined equation system, thereby obtaining the estimated instantaneous position and nominal frequency of the signal frame subclass. Furthermore, the instantaneous positions of all valid signal frame subclasses are sorted by time and converted into latitude and longitude coordinates, and motion trajectories are generated through linear or smooth fitting. Finally, the trajectory is verified by utilizing the consistency of the nominal frequency estimates of each valid signal frame subclass, and abnormal valid signal frame subclasses are removed before regenerating the trajectory.

[0037] This application thus achieves automatic signal sorting of multiple terminals and tracking of mobile communication terminals under conditions of no network control and no passive operation. It further solves the technical problems of reliance on network control signals, difficulties in multi-terminal signal sorting, and insufficient trajectory accuracy in existing technologies.

[0038] Optionally, the operation of clustering the time-series signal frame sequence according to the unsupervised clustering algorithm, and dividing independent signal frames with continuous transmission times and frequency changes less than a preset threshold into the same signal frame subclass, includes: sorting the time-series signal frame sequence according to the transmission time of each independent signal frame; and dividing independent signal frames with temporal proximity and frequency changes less than a preset threshold into the same signal frame subclass using the time-series unsupervised clustering algorithm based on temporal continuity and the preset threshold, wherein the independent signal frames within the signal frame subclass correspond to multiple observation times of the mobile communication terminal within a time period in which the position is approximately constant.

[0039] Specifically, the positioning station 30 targets all independent signal frames transmitted by the m-th mobile communication terminal 20. ~ According to the transmission time of each independent signal frame (i=1~k, and, Generates a sequence of time-ordered signal frames corresponding to the mobile communication terminal 20. .in This represents the i-th independent signal frame transmitted by the m-th mobile communication terminal 20, where k is the total number of independent signal frames. This ensures that subsequent clustering operations can correctly identify the chronological order of the independent signal frames on the time axis.

[0040] Furthermore, the positioning station 30 utilizes a temporal unsupervised clustering algorithm (such as the density-based DBSCAN algorithm or hierarchical clustering algorithm) to classify all independent signal frames transmitted by the m-th mobile communication terminal 20. ~ Divided into H signal frame subclasses, i.e. The positioning station 30 classifies independent signal frames that are temporally adjacent and whose frequency variation between adjacent independent signal frames is less than a preset threshold into the same signal frame subclass.

[0041] For example, positioning station 30 sets two adjacent independent signal frames. and The measured frequencies are respectively and Define the frequency variation between adjacent independent signal frames. for: (1) The preset threshold for the frequency change is denoted as . (This can be set according to actual accuracy requirements by those skilled in the art). The positioning station iterates through the sorted sequence of timing signal frames 30 times, determining whether two adjacent independent signal frames simultaneously satisfy the following conditions: they are consecutive in transmission time with no other independent signal frames in between, and the frequency change between the two adjacent independent signal frames is less than a preset threshold. That is: (2) When any two adjacent independent signal frames in a set of consecutively arranged independent signal frames simultaneously satisfy the above two conditions, the positioning station 30 classifies these independent signal frames into the same signal frame subclass. Each signal frame subclass Include Individual signal frames ( (p=1~H), that is .

[0042] It should be noted that, This represents the signal frame subclass of the m-th mobile communication terminal 20. (Or the first independent signal frame included in the p-th signal frame subclass). This represents the signal frame subclass of the m-th mobile communication terminal 20. (Or, the second independent signal frame included in the p-th signal frame subclass.) And so on. This represents the signal frame subclass of the m-th mobile communication terminal 20. (Or the p-th signal frame subclass) includes the th Each independent signal frame.

[0043] Furthermore, since the measured frequency is directly related to the radial velocity of the mobile communication terminal 20 relative to the low-Earth orbit satellite 10, a small frequency change means that the positional change of the mobile communication terminal 20 during that time period can be ignored and can be approximated as constant. Therefore, each signal frame subclass This corresponds to multiple observation times of the mobile communication terminal 20 within a time period in which the location is approximately constant.

[0044] Thus, through the above methods, the positioning station 30 can segment the continuous motion process of the mobile communication terminal 20 into multiple approximately static signal frame subclasses, providing an effective data foundation for subsequent high-precision positioning calculations based on the static assumption.

[0045] Optionally, the operation of constructing a nonlinear overdetermined equation system based on the signal frame subclass includes: obtaining the measured frequency corresponding to each independent signal frame within each signal frame subclass, as well as the satellite position and satellite velocity at the observation time corresponding to each independent signal frame; establishing observation equations with the instantaneous position and nominal frequency of the mobile communication terminal as unknowns based on the Doppler pre-compensation rules before the communication terminal's transmission, the measured frequency, the satellite position, and the satellite velocity; and combining the observation equations corresponding to all independent signal frames within the signal frame subclass with the Earth's spherical constraint equations to construct a nonlinear overdetermined equation system.

[0046] Specifically, positioning station 30 acquires each signal frame subclass. Measured frequencies corresponding to all independent signal frames within Satellite position and satellite speed .in, The measured frequency of the i-th independent signal frame of the p-th signal frame subclass of the m-th mobile communication terminal 20. Let be the three-dimensional spatial coordinates (i.e., satellite position) of the low-orbit satellite 10 corresponding to the transmission time of the i-th independent signal frame. Let $\frac{i}{i}$ be the satellite velocity of low-Earth orbit satellite 10 corresponding to the transmission time of the $i$-th independent signal frame.

[0047] Furthermore, to compensate for the Doppler frequency shift between itself and the low-Earth orbit satellite 10, and to ensure that its transmitted uplink radio frequency signal can be correctly received by the low-Earth orbit satellite 10, the mobile communication terminal 20 will perform Doppler pre-compensation before transmitting the uplink radio frequency signal. That is: (3) In the formula, For the p-th signal frame subclass of the m-th mobile communication terminal 20 The measured frequency of the i-th independent signal frame; The nominal frequency of mobile communication terminal 20, The true Doppler shift between the mobile communication terminal 20 and the low-orbit satellite 10, corresponding to the i-th independent signal frame of the p-th signal frame subclass of the m-th mobile communication terminal 20.

[0048] It should be noted that, according to the Doppler effect, the actual Doppler frequency shift between the mobile communication terminal 20 and the low-Earth orbit satellite 10 is... The radial relative velocity between the two is determined by the following theoretical formula: (4) Where c is the speed of light in a vacuum. The instantaneous position of the mobile communication terminal 20 corresponding to the p-th signal frame subclass; It is the dot product of the satellite velocity and the satellite-terminal line-of-sight vector, that is, it represents the magnitude of the projected component of the satellite velocity in the line-of-sight direction multiplied by the line-of-sight distance. The distance between the mobile communication terminal 20 and the low-Earth orbit satellite 10 is Euclidean distance, and the ratio of the two is the radial relative velocity of the low-Earth orbit satellite 10 with respect to the mobile communication terminal 20.

[0049] Next, positioning station 30 combines formulas (3) and (4) to eliminate intermediate variables. The following observation equation can be obtained: (5) Furthermore, positioning station 30 will classify the signal frame subclasses. Inside Each independent signal frame corresponds to All observation equations are listed. Furthermore, since the mobile communication terminal 20 is located on the Earth's surface, its instantaneous position must also satisfy the Earth's spherical constraint equations: (6) Where R is the average radius of the Earth. for The three coordinate components.

[0050] Next, positioning station 30 will The observation equations and the Earth's spherical constraint equations shown in formula (6) are combined to construct the following set of nonlinear equations: (7) It should be noted that, since the unknown quantity is only (3 coordinate components) and (1 scalar), a total of 4 unknowns, and the number of observation equations is +1 ( Since the number of equations is ≥3, the number of equations is ≥4. Therefore, this nonlinear system of equations is a nonlinear overdetermined system of equations.

[0051] Thus, through the above methods, the positioning station 30 can transform the discrete measured frequency observations and satellite ephemeris information into a mathematically solvable optimization problem.

[0052] Optionally, the operation of determining the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass based on the nonlinear overdetermined equations includes: constructing an objective function for the residual sum of squares, whereby the objective function represents the deviation between the measured frequency and the predicted frequency of each independent signal frame within the signal frame subclass; solving the objective function, and correcting the instantaneous position according to the Earth's spherical constraint after each iteration, wherein the Earth's spherical constraint means that the instantaneous position of the mobile communication terminal is located on the Earth's surface; stopping the iteration when the change in the objective function is less than a preset convergence threshold, taking the instantaneous position obtained in the current iteration as the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass, and taking the nominal frequency obtained at the time of iteration convergence as the nominal frequency estimate of the mobile communication terminal.

[0053] Specifically, positioning station 30 defines a subclass of the signal frame used for quantization. The objective function J is the deviation between the measured and predicted frequencies of all independent signal frames. Where the predicted frequency of the i-th independent signal frame is... The calculation formula is: (8) The objective function J is then defined as: (9) The smaller the value of the objective function, the stronger the current hypothesis. and The closer it is to the true value.

[0054] Furthermore, positioning station 30 employs the LM iterative algorithm to minimize the objective function J. In each iteration, positioning station 30 first calculates the objective function J based on the current estimate at the t-th observation time. and Calculate the current prediction frequency for each independent signal frame. .

[0055] Then, positioning station 30 constructs the residual vector and Jacobian matrix according to formula (9). Wherein, the residual vector... Defined as the difference between the measured frequency and the predicted frequency, i.e. Jacobian matrix for A 4th-order matrix whose elements are the first-order partial derivatives of the objective function J with respect to each unknown.

[0056] Next, positioning station 30 uses the LM iterative algorithm to solve for the correction amount. : (10) in, , They are respectively The correction amount for the three coordinate components. This is the correction amount for the nominal frequency. Damping factor ( ≥0 is used to adjust iteration stability and avoid matrix singularities. Jacobian matrix The transpose of the matrix, It is a 4th order identity matrix.

[0057] Subsequently, positioning station 30 updates the unknowns at the next observation time (t+1) according to the following formula: (11) (12) It should be noted that, since the mobile communication terminal 20 is located on the Earth's surface, its location must meet certain conditions. Therefore, positioning station 30 will forcibly project the updated position vector onto the Earth's surface to ensure that the solution results always conform to the physical constraints of mobile communication terminal 20 being located on the Earth's surface, i.e.: (13) Furthermore, positioning station 30 calculates the objective function value after this iteration. and the objective function value of the previous iteration Compare the results. Stop iterating when the following convergence condition is met: (14) In the formula, This is the preset convergence threshold.

[0058] If the current iteration meets the convergence condition, positioning station 30 stops iterating; if the current iteration does not meet the convergence condition, positioning station 30 proceeds to the next iteration and adjusts the damping factor. (like If the number of positioning stations is 30, then the number of stations will decrease. Conversely, it increases. Continue until the maximum number of iterations is reached.

[0059] After the iteration converges, the positioning station 30 will record the instantaneous position obtained in the current iteration. As a subclass of signal frames The instantaneous position of the corresponding mobile communication terminal 20, and the nominal frequency obtained during iterative convergence. As the nominal frequency estimate of a mobile communication terminal.

[0060] Thus, through the above methods, the positioning station 30 can deduce the precise location and nominal frequency of the mobile communication terminal 20 within a certain approximately static time period from a set of measured frequency observations without any network control information.

[0061] Optionally, the operation of generating the motion trajectory of the mobile communication terminal based on the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass includes: sorting all signal frame subclasses in ascending order according to the average transmission time of the independent signal frames within each signal frame subclass to determine the time sequence subclass sequence; extracting the instantaneous position of the mobile communication terminal corresponding to each signal frame subclass and converting each instantaneous position into latitude and longitude coordinates; and using a linear fitting algorithm or a smooth fitting algorithm to connect or fit the latitude and longitude coordinates corresponding to the time sequence subclasses in sorted order to generate the motion trajectory of the mobile communication terminal.

[0062] Specifically, the positioning station 30 integrates the instantaneous positions of all signal frame subclasses to generate the complete motion trajectory of the mobile communication terminal 20.

[0063] Specifically, after removing abnormal subclasses, the positioning station 30 obtained a total of Valid signal frame subclasses ( ≤H), that is Then, positioning station 30 calculates the subclass of each valid signal frame. Average transmission time of all independent signal frames within: (15) in For the first Valid signal frame subclasses The number of independent signal frames in the data. Let i be the transmission time of the i-th independent signal frame. Positioning station 30 will classify all valid signal frames into subclasses according to... Sort the sequences in ascending order from smallest to largest to obtain the sequence of time series subclasses. .

[0064] Subsequently, for the time-series subclass sequences Each valid signal frame subclass The positioning station 30 extracts its corresponding instantaneous position and converts each instantaneous position into latitude and longitude coordinates.

[0065] The formula for converting three-dimensional spatial coordinates to longitude is: (16) The formula for converting three-dimensional spatial coordinates to latitude is: (17) Therefore, positioning station 30 can obtain instantaneous latitude and longitude coordinates. (), ), ......, ( ).in, These are the effective signal frame subclasses included in the mobile communication terminal 20. The three coordinate components of the corresponding instantaneous position.

[0066] Finally, the positioning station 30 uses a linear fitting algorithm or a smooth fitting algorithm to connect or fit the instantaneous latitude and longitude coordinates in the sorted order to form a continuous spatial curve, which serves as the motion trajectory of the mobile communication terminal 20.

[0067] Through the above methods, the positioning station 30 integrates the originally discrete positioning results belonging to different time segments into a continuous, orderly and readable complete motion trajectory, realizing a comprehensive restoration of the motion process of the mobile communication terminal 20.

[0068] Optionally, the method further includes trajectory verification of the motion trajectory of the mobile communication terminal: calculating the average value of the nominal frequency estimates corresponding to all signal frame subclasses, and calculating the absolute deviation between the nominal frequency estimate of each signal frame subclass and the average value; if all absolute deviations are less than or equal to a preset deviation threshold, the motion trajectory is determined to be valid; otherwise, the signal frame subclasses with absolute deviations greater than the deviation threshold are removed, and the motion trajectory of the mobile communication terminal is regenerated using the remaining signal frame subclasses.

[0069] Specifically, after generating the motion trajectory of the mobile communication terminal 20, the positioning station 30 also needs to verify the reliability of the motion trajectory. This is because the nominal frequency of the same mobile communication terminal 20... Since the frequency will not change in a short period of time, the deviation of the nominal frequency estimate calculated by each effective signal frame subclass should be controlled within the set threshold to verify the availability of the trajectory.

[0070] Specifically, positioning station 30 first calculates the average of the nominal frequency estimates for all valid signal frame subclasses: (18) Next, positioning station 30 calculates the effective signal frame subclass for each subclass. nominal frequency estimate Compared with the average The absolute deviation between: (19) Furthermore, positioning station 30 will classify each valid signal frame into subclasses. absolute deviation Deviation threshold from the preset nominal frequency Comparison: If for all valid signal frame subclasses This indicates that the nominal frequency of each valid signal frame subclass is consistent, and the instantaneous position of each valid signal frame subclass belongs to the same mobile communication terminal 20 and the calculation is reliable. Therefore, the positioning station 30 determines that the currently generated motion trajectory is valid and can be directly output.

[0071] If some valid signal frame subclasses satisfy If the positioning station 30 determines that the positioning results of these valid signal frame subclasses are unreliable, it needs to re-examine the signal frame quality, clustering parameters, and solution process of that valid signal frame subclass. If it cannot be corrected, the valid signal frame subclass is discarded, and the remaining valid signal frame subclasses are reassembled to generate the corresponding motion trajectory of the mobile communication terminal 20. If the abnormal valid signal frame subclasses are discarded, the total number of valid signal frame subclasses will be... If the positioning station 30 determines that the motion trajectory of the corresponding mobile communication terminal 20 cannot be generated, it needs to re-collect independent signal frames and then execute the entire process again.

[0072] Thus, through the above methods, the positioning station 30 can automatically identify and eliminate abnormal valid signal frame subclasses with large positioning errors, ensuring that the final output motion trajectory has high continuity and accuracy.

[0073] Optionally, the operation of determining the timing signal frame sequence corresponding to the mobile communication terminal includes: acquiring independent signal frames of the communication terminal and determining a set of signal frames, wherein the communication terminal includes a stationary communication terminal and a mobile communication terminal; extracting the radio frequency fingerprint feature vector corresponding to each independent signal frame in the set of signal frames and determining a set of feature vectors, wherein the radio frequency fingerprint feature vector is used to uniquely identify the hardware identity of the communication terminal; and clustering all independent signal frames in the set of signal frames using an unsupervised clustering algorithm based on the set of feature vectors, classifying independent signal frames whose radio frequency fingerprint feature vector similarity meets a preset condition into the same terminal category, each terminal category uniquely corresponding to one communication terminal, and sorting them according to the transmission time to form a timing signal frame sequence corresponding to the communication terminal.

[0074] Specifically, the positioning station 30 first continuously collects the uplink radio frequency signals transmitted directionally from the mobile communication terminal 20 to the low-Earth orbit satellite 10, and performs time-domain energy detection on the continuously collected uplink radio frequency signals to obtain independent signal frames transmitted separately by each mobile communication terminal 20, which do not interfere with each other and have a complete frame structure, thus determining the set of signal frames. ~ Where n is the total number of independent signal frames.

[0075] Furthermore, after acquiring the independent signal frames sent by each mobile communication terminal 20 to the low-Earth orbit satellite 10, the positioning station 30 processes each independent signal frame... (j=1, 2, ..., n) Perform comprehensive analysis in the time domain and frequency domain respectively to extract the unique radio frequency fingerprint feature that can characterize the mobile communication terminal 20 to which the independent signal frame belongs.

[0076] Among them, radio frequency fingerprint features include the duration of signal frames. signal peak amplitude Time-domain amplitude standard deviation Signal start-up time Signal descent time Extracting peak frequencies from the frequency domain 3dB bandwidth of spectrum I / Q branch amplitude ratio Phase noise peak spurious signal peak .

[0077] Specifically, the duration of the signal frame Independent signal frames From the start time of the uplink radio frequency signal Until the end time The complete duration of the time is determined by the transmission protocol and hardware driving characteristics of the mobile communication terminal 20. Different mobile communication terminals 20 have slight differences, which can be directly extracted by the positioning station 30. That is: (20) signal peak amplitude Independent signal frames The maximum signal amplitude that the time-domain waveform can reach is determined by the power amplifier hardware characteristics of the mobile communication terminal 20. Different mobile communication terminals 20 have inherent differences in the peak output of their power amplifiers. Without any calculation, the positioning station 30 can directly read the independent signal frames. Time-domain amplitude sequence The maximum value. That is: (twenty one) Peak frequency of the spectrum This refers to the center peak frequency corresponding to the location where the signal spectrum energy is concentrated. In other words, the positioning station has 30 pairs of independent signal frames. Perform a Fast Fourier Transform to obtain the spectral amplitude sequence. The frequency corresponding to the maximum spectral amplitude in this spectral amplitude sequence is the peak frequency. Therefore, positioning station 30 can directly read from the spectrum diagram.

[0078] 3dB bandwidth of spectrum It is a positioning station with 30 pairs of independent signal frames. The spectrum is analyzed by directly measuring the frequency range corresponding to a 3dB drop in the amplitude of the spectral peak, which is obtained through spectrum measurement. That is, (twenty two) in, The upper cutoff frequency is the frequency at which the amplitude of the peak value drops by 3dB. This is the lower cutoff frequency where the amplitude of the peak spectrum drops by 3dB.

[0079] Time-domain amplitude standard deviation Independent signal frames The degree of dispersion of the overall fluctuation of the time-domain amplitude. It can be calculated by positioning station 30 according to the following formula: (twenty three) Where N is the number of sampling points in the signal frame. denoted as the average amplitude in the time domain, and g represents the total number of observation times t.

[0080] Signal start-up time This refers to the time required for the signal to rise from a quiet noise level to a stable operating level, i.e., the time it takes for the uplink RF signal to reach 90% of its peak amplitude from the start. It can be obtained directly from an independent signal frame by the positioning station 30. Measured in the time-domain waveform and read directly from the time-domain waveform.

[0081] signal fall time This is the time required for the signal to drop from a stable operating level to a quiet noise level, i.e., the time it takes for the uplink RF signal to decrease from 90% of its peak amplitude to 10%. It is related to the signal start-up time. Correspondingly, all values ​​can be directly measured from the time-domain waveform by the positioning station 30 and read directly.

[0082] I / Q branch amplitude ratio This represents the amplitude ratio between the in-phase branch and the quadrature branch of the signal. Specifically, this is the amplitude ratio of the I / Q branch. The ratio of the amplitude of the I-branch to the amplitude of the Q-branch can be directly calculated by demodulating the j-th independent signal frame using 1 / Q at positioning station 30. That is: (twenty four) Phase noise peak It is a positioning station with 30 pairs of independent signal frames. After performing spectrum analysis, the maximum phase noise value at a frequency offset of 1 kHz is directly read.

[0083] Spurious signal peak This is the maximum peak value of spurious radiation outside the signal's operating frequency band. That is, the peak value of this spurious signal. It can be generated by 30 independent signal frames from the positioning station. Analyze the spectrum and eliminate useful signal frequency bands (based on peak frequency). Centered on the spectrum, 3dB bandwidth (Within), the maximum amplitude of spurious signals in the remaining frequency band can be directly read without the need for additional definition standards; direct measurement is sufficient.

[0084] Then, the positioning station 30 integrates the extracted radio frequency fingerprint features to construct a multi-dimensional radio frequency fingerprint feature vector. This serves as the identifier for each independent signal frame. The radio frequency fingerprint feature is used to characterize the inherent hardware differences and subtle waveform features of the uplink radio frequency signals transmitted by different mobile communication terminals 20.

[0085] Subsequently, positioning station 30 uses an unsupervised clustering algorithm to perform clustering on all independent signal frames. ~ The corresponding feature vector set is subjected to the first cluster analysis. Then, based on the results of the first cluster analysis, the positioning station 30 divides the independent signal frames transmitted by the same communication terminal into the same terminal category, with each terminal category corresponding to a mobile communication terminal 20 or a stationary communication terminal.

[0086] Furthermore, the positioning station 30 can target all independent signal frames transmitted by the m-th mobile communication terminal 20. ~ According to the transmission time of each independent signal frame (Right now, Generates a sequence of time-ordered signal frames corresponding to the mobile communication terminal 20. .

[0087] In addition, refer to Figure 1 As shown, according to a second aspect of this embodiment, a storage medium is provided. The storage medium includes a stored program, wherein, when the program is executed, a processor performs any of the methods described above.

[0088] Therefore, according to this embodiment, this application realizes automatic signal sorting of multiple terminals and tracking of mobile communication terminals under conditions of no network control and no passive operation. This solves the technical problems of reliance on network control signals, difficulty in multi-terminal signal sorting, and insufficient trajectory accuracy in the prior art.

[0089] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0090] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0091] Example 2

[0092] Figure 4 A motion trajectory generation apparatus for a mobile communication terminal according to this embodiment is shown, which corresponds to the method described in Embodiment 1. (Reference) Figure 4 As shown, the device includes: a timing signal frame sequence determination module 410, used to determine the timing signal frame sequence corresponding to the mobile communication terminal; a clustering module 420, used to cluster the timing signal frame sequence according to an unsupervised clustering algorithm, dividing independent signal frames with continuous transmission times and frequency changes less than a preset threshold into the same signal frame subclass; an equation system construction module 430, used to construct a nonlinear overdetermined equation system according to the signal frame subclass, wherein the nonlinear overdetermined equation system is used to represent the Doppler frequency shift between the corresponding mobile communication terminal and the low-orbit satellite; an instantaneous position determination module 440, used to determine the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass according to the nonlinear overdetermined equation system; and a motion trajectory generation module 450, used to generate the motion trajectory of the mobile communication terminal according to the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass.

[0093] Optionally, the operation of clustering the time-series signal frame sequence according to the unsupervised clustering algorithm, and dividing independent signal frames with continuous transmission times and frequency changes less than a preset threshold into the same signal frame subclass, includes: sorting the time-series signal frame sequence according to the transmission time of each independent signal frame; and dividing independent signal frames with temporal proximity and frequency changes less than a preset threshold into the same signal frame subclass using the time-series unsupervised clustering algorithm based on temporal continuity and the preset threshold, wherein the independent signal frames within the signal frame subclass correspond to multiple observation times of the mobile communication terminal within a time period in which the position is approximately constant.

[0094] Optionally, the operation of constructing a nonlinear overdetermined equation system based on the signal frame subclass includes: obtaining the measured frequency corresponding to each independent signal frame within each signal frame subclass, as well as the satellite position and satellite velocity at the observation time corresponding to each independent signal frame; establishing observation equations with the instantaneous position and nominal frequency of the mobile communication terminal as unknowns based on the Doppler pre-compensation rules before the communication terminal's transmission, the measured frequency, the satellite position, and the satellite velocity; and combining the observation equations corresponding to all independent signal frames within the signal frame subclass with the Earth's spherical constraint equations to construct a nonlinear overdetermined equation system.

[0095] Optionally, the operation of determining the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass based on the nonlinear overdetermined equations includes: constructing an objective function for the residual sum of squares, whereby the objective function represents the deviation between the measured frequency and the predicted frequency of each independent signal frame within the signal frame subclass; solving the objective function, and correcting the instantaneous position according to the Earth's spherical constraint after each iteration, wherein the Earth's spherical constraint means that the instantaneous position of the mobile communication terminal is located on the Earth's surface; stopping the iteration when the change in the objective function is less than a preset convergence threshold, taking the instantaneous position obtained in the current iteration as the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass, and taking the nominal frequency obtained at the time of iteration convergence as the nominal frequency estimate of the mobile communication terminal.

[0096] Optionally, the operation of generating the motion trajectory of the mobile communication terminal based on the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass includes: sorting all signal frame subclasses in ascending order according to the average transmission time of the independent signal frames within each signal frame subclass to determine the time sequence subclass sequence; extracting the instantaneous position of the mobile communication terminal corresponding to each signal frame subclass and converting each instantaneous position into latitude and longitude coordinates; and using a linear fitting algorithm or a smooth fitting algorithm to connect or fit the latitude and longitude coordinates corresponding to the time sequence subclasses in sorted order to generate the motion trajectory of the mobile communication terminal.

[0097] Optionally, the motion trajectory generation module 450 further includes a trajectory verification submodule, which is used to calculate the average value of the nominal frequency estimates corresponding to all signal frame subclasses, and calculate the absolute deviation between the nominal frequency estimate of each signal frame subclass and the average value; if all absolute deviations are less than or equal to a preset deviation threshold, the motion trajectory is determined to be valid; otherwise, the signal frame subclasses with absolute deviations greater than the deviation threshold are removed, and the motion trajectory of the mobile communication terminal is regenerated using the remaining signal frame subclasses.

[0098] Optionally, the operation of determining the timing signal frame sequence corresponding to the mobile communication terminal includes: acquiring independent signal frames of the communication terminal and determining a set of signal frames, wherein the communication terminal includes a stationary communication terminal and a mobile communication terminal; extracting the radio frequency fingerprint feature vector corresponding to each independent signal frame in the set of signal frames and determining a set of feature vectors, wherein the radio frequency fingerprint feature vector is used to uniquely identify the hardware identity of the communication terminal; and clustering all independent signal frames in the set of signal frames using an unsupervised clustering algorithm based on the set of feature vectors, classifying independent signal frames whose radio frequency fingerprint feature vector similarity meets a preset condition into the same terminal category, each terminal category uniquely corresponding to one communication terminal, and sorting them according to the transmission time to form a timing signal frame sequence corresponding to the communication terminal.

[0099] Therefore, according to this embodiment, this application realizes automatic signal sorting of multiple terminals and tracking of mobile communication terminals under conditions of no network control and no passive operation. This solves the technical problems of reliance on network control signals, difficulty in multi-terminal signal sorting, and insufficient trajectory accuracy in the prior art.

[0100] Example 3

[0101] Figure 5 A motion trajectory generation apparatus for a mobile communication terminal according to this embodiment is shown, which corresponds to the method described in Embodiment 1. (Reference) Figure 5 As shown, the device includes: a processor 510; and a memory 520 connected to the processor 510, used to provide the processor 510 with instructions to process the following steps: determining a time-series signal frame sequence corresponding to the mobile communication terminal; clustering the time-series signal frame sequence according to an unsupervised clustering algorithm, classifying independent signal frames with continuous transmission times and frequency variations less than a preset threshold into the same signal frame subclass; constructing a nonlinear overdetermined equation set based on the signal frame subclass, wherein the nonlinear overdetermined equation set is used to represent the Doppler frequency shift between the corresponding mobile communication terminal and the low-orbit satellite; determining the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass based on the nonlinear overdetermined equation set; and generating the motion trajectory of the mobile communication terminal based on the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass.

[0102] Optionally, the operation of clustering the time-series signal frame sequence according to the unsupervised clustering algorithm, and dividing independent signal frames with continuous transmission times and frequency changes less than a preset threshold into the same signal frame subclass, includes: sorting the time-series signal frame sequence according to the transmission time of each independent signal frame; and dividing independent signal frames with temporal proximity and frequency changes less than a preset threshold into the same signal frame subclass using the time-series unsupervised clustering algorithm based on temporal continuity and the preset threshold, wherein the independent signal frames within the signal frame subclass correspond to multiple observation times of the mobile communication terminal within a time period in which the position is approximately constant.

[0103] Optionally, the operation of constructing a nonlinear overdetermined equation system based on the signal frame subclass includes: obtaining the measured frequency corresponding to each independent signal frame within each signal frame subclass, as well as the satellite position and satellite velocity at the observation time corresponding to each independent signal frame; establishing observation equations with the instantaneous position and nominal frequency of the mobile communication terminal as unknowns based on the Doppler pre-compensation rules before the communication terminal's transmission, the measured frequency, the satellite position, and the satellite velocity; and combining the observation equations corresponding to all independent signal frames within the signal frame subclass with the Earth's spherical constraint equations to construct a nonlinear overdetermined equation system.

[0104] Optionally, the operation of determining the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass based on the nonlinear overdetermined equations includes: constructing an objective function for the residual sum of squares, whereby the objective function represents the deviation between the measured frequency and the predicted frequency of each independent signal frame within the signal frame subclass; solving the objective function, and correcting the instantaneous position according to the Earth's spherical constraint after each iteration, wherein the Earth's spherical constraint means that the instantaneous position of the mobile communication terminal is located on the Earth's surface; stopping the iteration when the change in the objective function is less than a preset convergence threshold, taking the instantaneous position obtained in the current iteration as the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass, and taking the nominal frequency obtained at the time of iteration convergence as the nominal frequency estimate of the mobile communication terminal.

[0105] Optionally, the operation of generating the motion trajectory of the mobile communication terminal based on the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass includes: sorting all signal frame subclasses in ascending order according to the average transmission time of the independent signal frames within each signal frame subclass to determine the time sequence subclass sequence; extracting the instantaneous position of the mobile communication terminal corresponding to each signal frame subclass and converting each instantaneous position into latitude and longitude coordinates; and using a linear fitting algorithm or a smooth fitting algorithm to connect or fit the latitude and longitude coordinates corresponding to the time sequence subclasses in sorted order to generate the motion trajectory of the mobile communication terminal.

[0106] Optionally, the memory 520 is also used to provide the processor 510 with instructions to process the following steps: calculate the average of the nominal frequency estimates corresponding to all signal frame subclasses, and calculate the absolute deviation between the nominal frequency estimate of each signal frame subclass and the average value; if all absolute deviations are less than or equal to a preset deviation threshold, the motion trajectory is determined to be valid; otherwise, the signal frame subclasses with absolute deviations greater than the deviation threshold are eliminated, and the motion trajectory of the mobile communication terminal is regenerated using the remaining signal frame subclasses.

[0107] Optionally, the operation of determining the timing signal frame sequence corresponding to the mobile communication terminal includes: acquiring independent signal frames of the communication terminal and determining a set of signal frames, wherein the communication terminal includes a stationary communication terminal and a mobile communication terminal; extracting the radio frequency fingerprint feature vector corresponding to each independent signal frame in the set of signal frames and determining a set of feature vectors, wherein the radio frequency fingerprint feature vector is used to uniquely identify the hardware identity of the communication terminal; and clustering all independent signal frames in the set of signal frames using an unsupervised clustering algorithm based on the set of feature vectors, classifying independent signal frames whose radio frequency fingerprint feature vector similarity meets a preset condition into the same terminal category, each terminal category uniquely corresponding to one communication terminal, and sorting them according to the transmission time to form a timing signal frame sequence corresponding to the communication terminal.

[0108] Therefore, according to this embodiment, this application realizes automatic signal sorting of multiple terminals and tracking of mobile communication terminals under conditions of no network control and no passive operation. This solves the technical problems of reliance on network control signals, difficulty in multi-terminal signal sorting, and insufficient trajectory accuracy in the prior art.

[0109] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0110] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0111] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0112] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0113] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0114] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0115] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for generating the motion trajectory of a mobile communication terminal, characterized in that, include: Determine the timing signal frame sequence corresponding to the mobile communication terminal; According to the unsupervised clustering algorithm, the time sequence signal frame sequence is clustered, and independent signal frames with continuous transmission time and frequency change less than a preset threshold are divided into the same signal frame subclass. Based on the signal frame subclass, a set of nonlinear overdetermined equations is constructed, wherein the set of nonlinear overdetermined equations is used to represent the Doppler frequency shift between the corresponding mobile communication terminal and the low-orbit satellite. Based on the nonlinear overdetermined equations, the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass is determined; The motion trajectory of the mobile communication terminal is generated based on the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass.

2. The method according to claim 1, characterized in that, According to the unsupervised clustering algorithm, the operation of clustering the time-series signal frame sequence and dividing independent signal frames with continuous transmission times and frequency variations less than a preset threshold into the same signal frame subclass includes: The timing signal frame sequence is sorted according to the transmission time of each independent signal frame; and Based on temporal continuity and a preset threshold, a temporal unsupervised clustering algorithm is used to classify independent signal frames that are temporally adjacent and whose frequency variation between adjacent independent signal frames is less than the preset threshold into the same signal frame subclass. The independent signal frames in the signal frame subclass correspond to multiple observation times of the mobile communication terminal within a time period in which the position is approximately constant.

3. The method according to claim 1, characterized in that, The operation of constructing a nonlinear overdetermined system of equations based on the signal frame subclass includes: Obtain the measured frequency corresponding to each independent signal frame within each signal frame subclass, as well as the satellite position and satellite velocity at the observation time corresponding to each independent signal frame; Based on the Doppler pre-compensation rules before the communication terminal's transmission, the measured frequency, the satellite position, and the satellite velocity, an observation equation is established with the instantaneous position and nominal frequency of the mobile communication terminal as unknowns; and By combining the observation equations corresponding to all independent signal frames within the aforementioned signal frame subclass with the Earth's spherical constraint equations, a nonlinear overdetermined set of equations is constructed.

4. The method according to claim 3, characterized in that, The operation of determining the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass based on the nonlinear overdetermined equations includes: Construct an objective function for the sum of squared residuals, wherein the objective function is used to represent the deviation between the measured frequency and the predicted frequency of each independent signal frame within the signal frame subclass; The objective function is solved, and the instantaneous position is corrected according to the Earth's spherical constraint after each iteration, wherein the Earth's spherical constraint means that the instantaneous position of the mobile communication terminal is located on the Earth's surface. When the change in the objective function is less than a preset convergence threshold, the iteration stops. The instantaneous position obtained in the current iteration is taken as the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass, and the nominal frequency obtained when the iteration converges is taken as the nominal frequency estimate of the mobile communication terminal.

5. The method according to claim 4, characterized in that, The operation of generating the motion trajectory of the mobile communication terminal based on the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass includes: Sort all signal frame subclasses in ascending order of the average transmission time of the independent signal frames within each subclass to determine the timing subclass sequence; Extract the instantaneous location of the mobile communication terminal corresponding to each signal frame subclass, and convert each instantaneous location into latitude and longitude coordinates; and Using a linear fitting algorithm or a smooth fitting algorithm, the latitude and longitude coordinates corresponding to the time series subsequences are connected or fitted in sorted order to generate the motion trajectory of the mobile communication terminal.

6. The method according to claim 5, characterized in that, It also includes trajectory verification of the movement trajectory of the mobile communication terminal: Calculate the average of the nominal frequency estimates corresponding to all signal frame subclasses, and calculate the absolute deviation of the nominal frequency estimate of each signal frame subclass from the average value; If all absolute deviations are less than or equal to a preset deviation threshold, the motion trajectory is determined to be valid; otherwise, the signal frame subclass with an absolute deviation greater than the deviation threshold is discarded, and the motion trajectory of the mobile communication terminal is regenerated using the remaining signal frame subclasses.

7. The method according to claim 1, characterized in that, The operation of determining the timing signal frame sequence corresponding to the mobile communication terminal includes: Acquire independent signal frames of the communication terminal and determine the signal frame set, wherein the communication terminal includes a static communication terminal and the mobile communication terminal; Extract the radio frequency fingerprint feature vector corresponding to each independent signal frame in the signal frame set to determine the feature vector set, wherein the radio frequency fingerprint feature vector is used to uniquely identify the hardware identity of the communication terminal; and Based on the set of feature vectors, an unsupervised clustering algorithm is used to cluster all independent signal frames in the set of signal frames. Independent signal frames whose radio frequency fingerprint feature vector similarity meets the preset conditions are classified into the same terminal category. Each terminal category uniquely corresponds to a communication terminal, and the corresponding communication terminal's time-series signal frame sequence is formed by sorting according to the transmission time.

8. A storage medium, characterized in that, The storage medium includes a stored program, wherein, when the program is executed, the method described in any one of claims 1 to 7 is performed by a processor.

9. A motion trajectory generation device for a mobile communication terminal, characterized in that, include: The timing signal frame sequence determination module is used to determine the timing signal frame sequence corresponding to the mobile communication terminal; The clustering module is used to cluster the time-series signal frame sequence according to the unsupervised clustering algorithm, and to divide independent signal frames with continuous transmission time and frequency change less than a preset threshold into the same signal frame subclass. The equation system construction module is used to construct a nonlinear overdetermined equation system based on the signal frame subclass, wherein the nonlinear overdetermined equation system is used to represent the Doppler frequency shift between the corresponding mobile communication terminal and the low-orbit satellite; The instantaneous position determination module is used to determine the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass based on the nonlinear overdetermined equations. The motion trajectory generation module is used to generate the motion trajectory of the mobile communication terminal based on the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass.

10. A motion trajectory generation device for a mobile communication terminal, characterized in that, include: processor; as well as A memory, connected to the processor, for providing the processor with instructions to perform the following processing steps: Determine the timing signal frame sequence corresponding to the mobile communication terminal; According to the unsupervised clustering algorithm, the time sequence signal frame sequence is clustered, and independent signal frames with continuous transmission time and frequency change less than a preset threshold are divided into the same signal frame subclass. Based on the signal frame subclass, a set of nonlinear overdetermined equations is constructed, wherein the set of nonlinear overdetermined equations is used to represent the Doppler frequency shift between the corresponding mobile communication terminal and the low-orbit satellite. Based on the nonlinear overdetermined equations, the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass is determined; The motion trajectory of the mobile communication terminal is generated based on the instantaneous position of the mobile communication terminal corresponding to the signal frame subclass.

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