Multipath TOA Calculation Method, System, and Electronic Equipment Based on Ground-Based Navigation Systems

Abstract

This invention provides a multipath TOA calculation method, system, and electronic device based on a ground-based navigation system. The method includes: acquiring the signal spectrum of the ground-based navigation system transmitted through multiple propagation paths in the frequency domain channel, and constructing a discrete frequency domain channel impulse response model related to the signal spectrum; determining the number of propagation paths of the ground-based navigation system signal based on the signal spectrum; and alternately correcting the arrival time and path amplitude of all propagation paths by gradually increasing the number of propagation paths to a second objective function until the first objective function converges, thereby obtaining the target arrival time and target path amplitude for each propagation path of the ground-based navigation system. This invention improves the accuracy of propagation path number calculation, reduces the probability of false alarms and missed detections in complex multipath channels, and improves the accuracy of propagation path arrival time and path amplitude calculation, thereby improving the positioning accuracy of the entire ground-based navigation system.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and in particular to a multipath TOA calculation method, system, and electronic device based on a ground-based navigation system. Background Technology

[0002] With the continuous advancement of information technology in modern society, navigation systems are being used more and more widely in various fields, especially in urban transportation, autonomous driving, aerospace, and various ground-based positioning technologies. Ground-based navigation systems, as a positioning method, possess high real-time performance and accuracy. In ground-based navigation systems, the accuracy of the time of arrival estimation of the propagated signal affects the position accuracy and synchronization accuracy of the user terminal.

[0003] While existing technologies have made some progress in positioning methods based on multipath TOA calculation, they still suffer from poor accuracy and low processing efficiency when faced with multiple propagation paths in complex environments. Traditional methods typically rely on basic cross-correlation, generalized cross-correlation, and feature structure methods. These methods usually only consider the analysis of a single propagation path, which can easily lead to low accuracy in calculating arrival time and path amplitude in complex indoor environments with multipath conditions, thus affecting the positioning accuracy at the user end. Summary of the Invention

[0004] This invention provides a multipath TOA calculation method, system, and electronic device based on a ground-based navigation system to improve the accuracy of propagation path arrival time calculation.

[0005] In a first aspect, the present invention provides a multipath TOA calculation method based on a ground-based navigation system, comprising:

[0006] In the frequency domain channel of the ground-based navigation system, the signal spectrum transmitted by the ground-based navigation system and superimposed after passing through multiple propagation paths is collected, and a discrete frequency domain channel impulse response model related to the signal spectrum is constructed.

[0007] The number of propagation paths for the transmitted signal in the ground-based navigation system is determined based on the signal spectrum.

[0008] Based on the discrete frequency domain channel impulse response model, a first objective function is constructed with the aim of optimizing the arrival time and path amplitude of multiple propagation paths of the ground-based navigation system.

[0009] Based on the first objective function, a second objective function is constructed with the objective of calculating the arrival time and path amplitude of a single propagation path.

[0010] By gradually increasing the number of propagation paths and the second objective function, the arrival time and path amplitude of all propagation paths are alternately corrected until the first objective function converges, so as to obtain the target arrival time and target path amplitude of each propagation path of the ground-based navigation system.

[0011] Secondly, the present invention also provides a multipath TOA calculation system for a ground-based navigation system, comprising:

[0012] The signal spectrum acquisition module is used to acquire the signal spectrum transmitted by the ground-based navigation system and superimposed after passing through multiple propagation paths in the frequency domain channel of the ground-based navigation system, and to construct a discrete frequency domain channel impulse response model related to the signal spectrum;

[0013] The path number acquisition module is used to determine the number of propagation paths of the transmitted signal in the ground-based navigation system based on the signal spectrum.

[0014] The first objective function construction module is used to construct a first objective function based on the discrete frequency domain channel impulse response model, with the objective of optimizing the arrival time and path amplitude of multiple propagation paths of the ground-based navigation system.

[0015] The second objective function construction module is used to construct a second objective function based on the first objective function, with the objective of calculating the arrival time and path amplitude of a single propagation path.

[0016] The target parameter acquisition module is used to alternately correct the arrival time and path amplitude of all the propagation paths by gradually increasing the number of propagation paths and the second objective function until the first objective function converges, so as to obtain the target arrival time and target path amplitude of each propagation path of the ground-based navigation system.

[0017] Thirdly, the present invention also provides an electronic device, the electronic device comprising:

[0018] One or more processors;

[0019] Storage device for storing one or more programs;

[0020] When the one or more programs are executed by the one or more processors, the one or more processors implement the multipath TOA calculation method based on a ground-based navigation system as provided in the first aspect of the present invention.

[0021] Fourthly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the multipath TOA calculation method based on a ground-based navigation system as provided in the first aspect of the present invention.

[0022] Fifthly, the present invention also provides a computer program product, the computer program product comprising a computer program, which, when executed by a processor, implements the multipath TOA calculation method based on a ground-based navigation system as provided in the first aspect of the present invention.

[0023] This invention provides a multipath TOA calculation method based on a ground-based navigation system. The method involves acquiring the signal spectrum of the ground-based navigation system after multiple propagation paths, collected in the frequency domain channel of the system, and constructing a discrete frequency domain channel impulse response model related to the signal spectrum. The number of propagation paths for the transmitted signal in the ground-based navigation system is determined based on the signal spectrum. A first objective function is constructed based on the discrete frequency domain channel impulse response model to optimize the arrival time and path amplitude of the multiple propagation paths of the ground-based navigation system. A second objective function is constructed based on the first objective function to calculate the arrival time and path amplitude of a single propagation path. By gradually increasing the number of propagation paths and the second objective function, the arrival time and path amplitude of all propagation paths are alternately corrected until the first objective function converges, thereby obtaining the target arrival time and target path amplitude for each propagation path of the ground-based navigation system. This invention analyzes received signals in the frequency domain to capture the superposition effect of multiple propagation paths. Through spectrum analysis, it can understand the time delay of signals on different paths. The discrete frequency domain channel impulse response model provides a theoretical basis for subsequent path estimation and optimization, effectively distinguishing each propagation path, improving the accuracy of propagation path number calculation, and reducing the probability of false alarms and missed detections in complex multipath channels. The determination of the number of paths provides a data foundation for subsequent signal processing. By constructing a first objective function, the arrival time and path amplitude of propagation paths can be optimized in the frequency domain, accurately calculating the relative delay and path strength of multiple paths, thereby improving the positioning accuracy of the user end. The second objective function optimizes individual propagation paths. Each propagation path needs to be optimized independently to better superimpose into the calculation of the entire ground-based navigation system. By gradually increasing the number of propagation paths and alternately correcting the arrival time and path amplitude of each path, the parameters of all propagation paths can be accurately solved in the case of multiple propagation paths. The alternating correction strategy, through multiple iterations of optimization, ensures the convergence of the first objective function, achieving high-precision calculation of the arrival time and path amplitude of propagation paths, thereby improving the positioning accuracy of the entire ground-based navigation system. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 A flowchart of a multipath TOA calculation method based on a ground-based navigation system provided in this embodiment of the invention;

[0026] Figure 2 A structural block diagram of a multipath TOA calculation system based on a ground-based navigation system provided in this embodiment of the invention;

[0027] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0028] Explanation of reference numerals in the attached figures: 10-Electronic device, 11-Processor, 12-Read-only memory (ROM), 13-Random access memory (RAM), 14-Bus, 15-I / O interface, 16-Input unit, 17-Output unit, 18-Storage unit, 19-Communication unit. Detailed Implementation

[0029] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention 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 used interchangeably where appropriate so that the embodiments of the invention described herein can cover implementations in sequences 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.

[0031] Figure 1This invention provides a flowchart of a multipath TOA calculation method based on a ground-based navigation system. This embodiment is applicable to calculating the arrival time and path amplitude of a propagation path in a ground-based navigation system. The method can be executed by a multipath TOA calculation system based on the ground-based navigation system, which can be implemented in hardware and / or software and can be configured in a computer device. Figure 1 As shown, the method includes:

[0032] Step 101: Collect the signal spectrum transmitted by the ground-based navigation system after passing through multiple propagation paths in the frequency domain channel of the ground-based navigation system, and construct a discrete frequency domain channel impulse response model related to the signal spectrum.

[0033] Ground-based navigation systems (GDS) are systems that provide positioning, navigation, and time synchronization services through ground base stations and sensor networks. GDS utilizes ground-based facilities (such as base stations, sensors, and radio signals) to transmit signals, which receiving devices use to calculate position and time of arrival. GDS are primarily used to supplement or replace traditional satellite navigation systems, especially in environments where satellite signals are unavailable or weak, such as densely populated urban areas or indoor environments. GDS offer advantages such as high accuracy and low latency.

[0034] A frequency domain channel refers to the influence of the channel on the signal in the frequency domain during signal propagation. The influence of the frequency domain channel on the signal is reflected not only in the time domain (i.e., signal delay) but also in the frequency domain. Signals of different frequencies may experience varying degrees of attenuation, phase changes, or multipath effects during propagation. By analyzing the frequency domain channel, we can obtain the propagation characteristics of the signal at different frequencies and estimate the multipath propagation of the signal.

[0035] In this embodiment, the propagation of signals by a ground-based navigation system is affected by multiple paths, a phenomenon known as multipath propagation. The signal travels to the receiver through multiple paths, which may have different lengths, delays, and amplitudes. Therefore, the received signal is a superposition of signals from these different paths. Acquiring the signal spectrum is to analyze the signal's distribution characteristics at different frequencies. The signal spectrum describes the energy distribution of the signal in the frequency domain, helping to understand how the signal is affected by different propagation paths during propagation. The signal spectrum contains information about signal strength, phase, and frequency, which is typically important for accurately estimating the signal's time of arrival (TOA) and path amplitude.

[0036] Discrete frequency domain channel impulse response (DTR) models are mathematical models that describe the changes in a signal after it has traveled through multiple propagation paths, particularly multipath effects. In the frequency domain, the channel impulse response represents the signal's propagation characteristics at various frequencies, including signal delay, attenuation, and phase changes. By discretizing the signal, continuous signals are transformed into discrete frequency components, allowing for more accurate capture and analysis of the signal propagation process, providing a basis for signal optimization and path estimation.

[0037] For example, the discrete frequency domain channel impulse response model is expressed as:

[0038] ;

[0039] in, For the first The signal spectrum at each frequency domain point The number of paths in the propagation path. Let the path amplitude be the k-th propagation path. The imaginary unit, For the center frequency, For frequency intervals, For the first Energy residuals at each frequency domain point Let be the arrival time of the k-th propagation path.

[0040] In one embodiment of the present invention, step 101 may include the following steps:

[0041] Step 1011: Collect the time-domain signal received by the mobile terminal, transmitted by the ground-based navigation system, and superimposed after passing through multiple propagation paths in the time-domain channel.

[0042] In this embodiment, the superimposed signals of multiple propagation paths can contain very rich information, but in the time domain, it is difficult to directly distinguish the independent characteristics (arrival time, path amplitude, etc.) of each propagation path from the superimposed signals. Acquiring these superimposed time-domain signals prepares for subsequent processing and provides raw signal data in a multipath propagation environment.

[0043] For example, time-domain signals in a multipath environment can be represented by a time-domain channel impulse response model.

[0044] The time-domain channel impulse response model can be expressed as:

[0045] ;

[0046] in, For time-domain signals, It is the number of propagation paths. It is the first The path amplitude of each propagation path, It is an impulse signal. It is the arrival time of the kth propagation path. Includes arrival time The impulse signal below.

[0047] Step 1012: Perform a Fourier transform operation on the time-domain signal to convert the time-domain signal into a frequency-domain signal.

[0048] In this embodiment, the Fourier transform is a mathematical tool that decomposes a time-domain signal into sinusoidal components of different frequencies. The core objective of this process is to decompose a composite signal in the time domain into frequency components in the frequency domain. The various frequency components contained in the time-domain signal will manifest in the frequency domain. By converting the signal from the time domain to the frequency domain, it becomes easier to analyze the contributions of different propagation paths. For example, the superposition of time-domain signals from multiple propagation paths may cause interference, but in the frequency domain, the characteristics of different propagation paths (such as differences in arrival time and path amplitude variations) can be distinguished by observing the frequency components of the time-domain signal.

[0049] For example, a frequency domain signal can be represented by a frequency domain channel response.

[0050] The frequency domain channel response is expressed as:

[0051] ;

[0052] in, It is a frequency domain signal. The number of paths in the propagation path. Let the path amplitude be the k-th propagation path. The imaginary unit is f, where f is the frequency. Let be the arrival time of the k-th propagation path.

[0053] Step 1013: Perform sampling operations on the frequency domain signal at multiple equally spaced frequency sampling points in the frequency domain channel to obtain the signal spectrum of the frequency domain signal.

[0054] In this embodiment, a sampling operation is performed on the frequency domain signal to discretize it, obtaining the signal spectrum. This allows for further analysis of information from different frequency sampling points. The signal spectrum contains the energy distribution of the frequency domain signal at different frequencies. By sampling at equally spaced multiple frequency sampling points in the frequency domain channel, the characteristics of the frequency domain signal can be captured more precisely. Insufficient sampling may result in the loss of some important signal information. Equally spaced sampling helps ensure that the frequency information of the frequency domain signal is fully captured, providing accurate data for subsequent calculations of the arrival time and path amplitude of multiple propagation paths.

[0055] Step 102: Determine the number of propagation paths of the transmitted signal in the ground-based navigation system based on the signal spectrum.

[0056] In this embodiment, ground-based navigation systems typically traverse multiple propagation paths during signal transmission, such as direct paths, reflection paths, and refraction paths. The existence of these propagation paths leads to multipath effects when the signal reaches the receiver, thus requiring accurate determination of the number of propagation paths. By analyzing the signal spectrum, the contribution of different paths to the signal can be extracted, and the number of paths can be determined accordingly.

[0057] For example, the signal spectra of multiple acquired frequency domain signals are converted into spectral vectors; the product of the spectral vector and its conjugate transpose is expected to obtain the spectral autocorrelation matrix; starting from the estimated number of propagation paths plus 1 and ending with the number of eigenvalues ​​of the effective eigenvalues ​​of the spectral autocorrelation matrix, the eigenvalues ​​of the spectral autocorrelation matrix are selected as the first eigenvalues; the effective eigenvalues ​​are non-zero values; each first eigenvalue is exponentially raised to obtain the second eigenvalues; the sums of the second eigenvalues ​​are obtained to obtain the geometric mean; the sum of the first eigenvalues ​​is multiplied by... The arithmetic mean is obtained by taking the reciprocal of the difference between the number of features and the estimated number of propagation paths. The logarithmic mean is obtained by taking the logarithm of the ratio between the geometric mean and the arithmetic mean. The first target multipath function for the estimated number of propagation paths is obtained by multiplying the negative of the logarithmic mean by a weighting term. The weighting term is the difference between the number of features and the estimated number of propagation paths multiplied by the number of frequency domain sampling points. The minimum value of the first target multipath function is calculated to determine the value of the estimated number of propagation paths. The estimated number of propagation paths is the number of propagation paths of the transmitted signal in the ground-based navigation system.

[0058] The first objective multipath function is expressed as:

[0059] ;

[0060]

[0061]

[0062] in, Let be the first objective multipath function, d be the estimated number of propagation paths, and M be the number of effective eigenvalues ​​of the spectral autocorrelation matrix. The first eigenvalue, The second eigenvalue, For weighted terms, For the spectrum vector, For the signal spectrum, The autocorrelation matrix is ​​the spectrum. d is the conjugate transpose of the spectrum vector, N is the number of frequency sampling points, and M is usually greater than d and less than N.

[0063] In this embodiment of the invention, the sum between the first objective multipath function and the complexity penalty term can also be used as the second objective multipath function; the minimum value of the second objective multipath function is used as the objective to determine the value of the estimated number of propagation paths.

[0064] The second objective multipath function is expressed as:

[0065] ;

[0066] in, For the second objective multipath function, For the first objective multipath function, This is a complexity penalty term. M represents the estimated number of propagation paths, M is the number of effective eigenvalues ​​of the spectral autocorrelation matrix, and N is the number of frequency sampling points.

[0067] In this embodiment, the number of propagation paths can be estimated using the Akaike Information-theory Criteria (AIC) or the Minimum Description Length (MDL).

[0068] AIC (Akaike Information Criterion) is a model selection criterion designed to balance goodness of fit with model complexity. AIC seeks a balance between goodness of fit and the number of model parameters; a lower AIC value indicates a more suitable model.

[0069] Minimum Description Length (MDL) is an information-theoretic approach that aims to avoid overfitting by selecting the model that most effectively compresses the data. The MDL criterion considers not only the complexity of the model but also its adaptability to the data, ultimately choosing a model that requires the least amount of information to describe the data.

[0070] Step 103: Construct a first objective function based on the discrete frequency domain channel impulse response model, with the goal of optimizing the arrival time and path amplitude of multiple propagation paths of the ground-based navigation system.

[0071] In this embodiment, a first objective function is constructed based on the discrete frequency domain channel impulse response model. The goal of this first objective function is to optimize the arrival time and path amplitude of multiple propagation paths in the ground-based navigation system. By accurately constructing the function and optimizing the arrival time and path amplitude of multiple propagation paths, the positioning accuracy and signal quality at the user end can be improved. During the propagation process of the ground-based navigation system signal, due to the superposition of multiple propagation paths, the signal experiences different time delays and path amplitude attenuation, all of which directly affect the performance of the ground-based navigation system. The first objective function helps the ground-based navigation system to more accurately calculate the characteristics of each propagation path, thereby effectively improving the accuracy and stability of the ground-based navigation system.

[0072] For example, the discrete frequency domain channel impulse response model is transformed into matrix form; once the matrix form transformation is completed, a first objective function is constructed to optimize the arrival time and path amplitude of each propagation path of the ground-based navigation system by minimizing the square of the residual energy between the signal spectrum and the discrete frequency domain channel impulse response model.

[0073] The matrix form is expressed as follows:

[0074]

[0075]

[0076]

[0077]

[0078] The first objective function is expressed as:

[0079] =

[0080] in, Let x be the residual energy vector and x be the spectrum vector. As the guide vector, The number of paths in the propagation path. The path amplitude of the propagation path described in the k-th rule. The residual energy corresponding to L frequency sampling points, Let L be the signal spectrum corresponding to L frequency sampling points, where j is the imaginary unit. For the center frequency, For frequency intervals, The arrival time of the propagation path described in the k-th path. Let be the first objective function. The residual energy is the additive white Gaussian noise of the channel, and the steering vector is the impulse response of the channel, both of which can be obtained by theoretical calculation or measurement.

[0081] Step 104: Construct a second objective function based on the first objective function, with the objective of calculating the arrival time and path amplitude of a single propagation path.

[0082] In this embodiment, a second objective function is constructed based on a first objective function to optimize the arrival time and path amplitude of a single propagation path. This process simplifies the optimization problem of multiple propagation paths into the optimization problem of a single propagation path, thereby enabling gradual adjustment of the arrival time and path amplitude of each propagation path. In a multipath environment, signal propagation paths have different arrival times and path amplitudes. Directly optimizing the parameters of all propagation paths leads to computational complexity and difficulty in convergence. However, by constructing a second objective function, the complex multipath optimization problem can be decomposed into path-by-path optimization, making the optimization process more efficient. It can gradually correct the arrival time and path amplitude of each propagation path until the global optimum converges. This helps improve the accuracy and speed of computation and avoids the problem of getting trapped in local optima that may occur when directly performing complex optimization on all propagation paths.

[0083] For example, the difference between the linear superposition components of the spectral vector and other propagation paths is used as the remaining spectral vector; the other propagation paths are the determined propagation paths other than the propagation paths whose arrival time and path amplitude are to be calculated; the first objective function is modified into a second objective function based on the remaining spectral vector, with the objective of calculating the arrival time and path amplitude of a single propagation path.

[0084] The second objective function is expressed as:

[0085]

[0086]

[0087] in, Let x be the remaining spectrum vector, and let x be the spectrum vector. For linear superposition components of other propagation paths, For the number of paths, Let the path amplitude be the k-th propagation path. As the guide vector, The second objective function is... The path amplitude of the propagation path to be optimized. This is the guide vector for the propagation path to be optimized.

[0088] Step 105: By gradually increasing the number of propagation paths and the second objective function, the arrival time and path amplitude of all propagation paths are alternately corrected until the first objective function converges, so as to obtain the target arrival time and target path amplitude of each propagation path of the ground-based navigation system.

[0089] In this embodiment, gradually increasing the number of propagation paths allows for a more comprehensive analysis of each path. The gradual convergence process is an iterative optimization process, with each optimization step attempting to reduce the gap between the calculated results and the actual signal until convergence is achieved (i.e., the error is sufficiently small). Through this alternating correction, it is ensured that the arrival time and path amplitude of all propagation paths are optimally adjusted, thereby improving the accuracy and reliability of the entire ground-based navigation system.

[0090] In one embodiment of the present invention, step 105 may include the following steps:

[0091] Step 1051: By traversing the arrival time search range of the propagation path, randomly add an initial arrival time to each propagation path.

[0092] In this embodiment, an initial arrival time is set for each propagation path so that the path amplitude can be calculated subsequently, and the arrival time of the propagation path can be optimized based on the path amplitude. The arrival time of each propagation path may be different; random initialization helps to avoid getting trapped in local minima and increases the chance of global optimization.

[0093] Step 1052: If the number of propagation paths is 1, calculate the arrival time and path amplitude of the first propagation path.

[0094] In this embodiment, when iteratively optimizing the arrival time and path magnitude of each propagation path using multiple propagation paths, it is preferentially assumed that the number of propagation paths is 1, and the arrival time and path magnitude of the first propagation path are calculated. This is a fundamental step to ensure that the characteristic parameters of the propagation path can be accurately calculated in the initial case (i.e., only one propagation path), forming the starting point of the optimization process. This facilitates alternating optimization with the added propagation paths when subsequent propagation paths are added. Prioritizing the calculation of the arrival time and path magnitude of the first propagation path also provides a data foundation for the iterative process. The first propagation path is the propagation path when the number of propagation paths is 1.

[0095] For example, if the number of propagation paths is 1, the steering vector corresponding to the initial arrival time of the first propagation path is obtained; the path amplitude of the first propagation path is obtained by dividing the product of the conjugate transpose of the steering vector corresponding to the initial arrival time of the first propagation path and the remaining spectral vector of the first propagation path by the product of the conjugate transpose of the steering vector corresponding to the initial arrival time of the first propagation path and the steering vector corresponding to the initial arrival time; with the goal of minimizing the second objective function, the initial arrival time is optimized by the path amplitude to obtain the arrival time of the first propagation path.

[0096] The formula for calculating path amplitude can be expressed as:

[0097]

[0098] in, Let be the path amplitude of the i-th propagation path, where i starts from 0. When i=0, it represents the first propagation path. This is the steering vector corresponding to the initial arrival time of the propagation path. This is the conjugate transpose of the steering vector corresponding to the initial arrival time of the propagation path. This is the remaining spectrum vector.

[0099] For example, by substituting the path magnitude calculation formula into the second objective function, the initial arrival time is optimized by minimizing the second objective function, thus obtaining the arrival time of the propagation path. The formula for calculating the arrival time can be expressed as:

[0100]

[0101] in, For the arrival time of the propagation path, The remaining spectrum vector of the propagation path. This is the steering vector corresponding to the initial arrival time of the propagation path. It is the conjugate transpose of the steering vector corresponding to the initial arrival time of the propagation path.

[0102] Step 1053: Based on the determined propagation path, the arrival time and path amplitude of the first propagation path, add a propagation path and obtain the steering vector corresponding to the initial arrival time of the newly added propagation path.

[0103] In this embodiment, by adding a new propagation path based on the already determined propagation path, and initializing the initial arrival time of the new propagation path and obtaining the steering vector corresponding to the initial arrival time, a new reference is provided for subsequent calculations and optimizations.

[0104] Step 1054: Based on the product of the conjugate transpose of the steering vector corresponding to the initial arrival time of the newly added propagation path and the remaining spectral vector of the newly added propagation path, divide by the product of the conjugate transpose of the steering vector corresponding to the initial arrival time of the newly added propagation path and the steering vector at the initial arrival time to obtain the path amplitude of the newly added propagation path.

[0105] In this embodiment, the path amplitude of the newly added propagation path is calculated. The path amplitude affects the signal strength and propagation effect, and is directly related to the accuracy of the optimization process. The calculation of the path amplitude provides a data basis for subsequent optimization of arrival time.

[0106] Step 1055: With the goal of calculating the minimum value of the second objective function, optimize the newly added initial arrival time based on the path amplitude of the newly added propagation path to obtain the arrival time of the newly added propagation path.

[0107] In this embodiment, the arrival time of the newly added propagation path is optimized by minimizing the second objective function and the path amplitude calculated in the previous step, ensuring that the arrival time of each propagation path can be optimized, thereby further improving the accuracy of the entire ground-based navigation system.

[0108] Step 1056: Based on the arrival time, path amplitude, and parameter alternation update strategy of the newly added propagation path, the arrival time and path amplitude of the determined propagation path are repeatedly updated until the first objective function converges.

[0109] In this embodiment, the arrival time and path magnitude of the propagation paths are repeatedly adjusted and optimized until the model's results stabilize and reach the optimal solution. Specifically, the arrival time and path magnitude of newly added propagation paths are optimized through alternating updates with those of already determined propagation paths. This alternating update strategy ensures that the parameters of each propagation path are optimally adjusted while considering other paths. Since multiple propagation paths influence each other, changes in the arrival time and path magnitude of one path may affect other paths; therefore, these interactions need to be considered during the update process. Through repeated adjustments, the first objective function converges, indicating that the value of the objective function no longer changes significantly, reaching the optimal solution. This alternating optimization avoids local optima and ultimately finds a globally optimal solution, improving the accuracy of arrival time calculation.

[0110] For example, the arrival time and path amplitude of the newly added propagation path are fixed, and the arrival time and path amplitude of the already determined propagation paths other than the newly added propagation path are re-optimized, and the target value of the first objective function is calculated; if the optimization is completed, the arrival time and path amplitude of the propagation paths other than the newly added propagation path are fixed, and the arrival time and path amplitude of the newly added propagation path are re-optimized, and the target value of the first objective function is calculated; the arrival time and path amplitude of all propagation paths under the current number of paths are repeatedly and alternately optimized until the difference between two adjacent target values ​​is less than a preset threshold, then it is determined that the arrival time and path amplitude of the already determined propagation paths have converged.

[0111] Step 1057: Determine whether the current number of propagation paths has reached the number of propagation paths of the ground-based navigation system; if yes, proceed to step 1058; if no, return to step 1053.

[0112] In this embodiment, it is determined whether the target number of propagation paths required for the ground-based navigation system to be estimated has been reached. If the target number of paths has been reached, the process proceeds to the next step, executing step 1058, to determine the final arrival time and path amplitude of each propagation path. If the target number of paths has not been reached, the process returns to step 1053 to continue adding new propagation paths and performing optimization. If the number of paths is insufficient, further optimization and the addition of new propagation paths are necessary to ensure that the ground-based navigation system can identify and process all propagation paths. By continuously increasing the number of propagation paths, the ground-based navigation system's ability to identify multiple propagation paths can be improved, ultimately enabling the estimation of a sufficient number of propagation paths to complete the solution of the navigation signal.

[0113] Step 1058: Determine the arrival time and path amplitude of each propagation path as the target arrival time and target path amplitude, respectively.

[0114] In this embodiment, once the predetermined number of propagation paths is reached, the ground-based navigation system enters the final calculation stage. After multiple optimizations, the arrival time and path amplitude of each propagation path have been repeatedly corrected and optimized in previous steps. At this point, the parameters of each propagation path are close to the optimal solution, and these arrival times and path amplitudes can be considered as the final target arrival time and target path amplitude.

[0115] This process not only confirms the propagation path estimate but also concludes the entire optimization process. Through this step, the ground-based navigation system obtains accurate propagation path estimates, which are crucial for subsequent positioning or navigation calculations. In a ground-based navigation system, accurate propagation path parameters directly affect the positioning accuracy at the user end. Accurately calculating the arrival time and path amplitude of each propagation path ensures the stability and efficiency of the ground-based navigation system.

[0116] For example, the optimization process of arrival time and path amplitude for multiple propagation paths is demonstrated by the following example:

[0117] Step A: Assume =0, =0 indicates that there is only one propagation path. The arrival time and path amplitude of the first propagation path are calculated first. The arrival time and path amplitude of the first propagation path are expressed as... .

[0118] Step B: Assume =1, obtained from step A Calculate the remaining spectrum vector of the second propagation path. Then, the result obtained from the calculation get The value of the first objective function is calculated based on the arrival time and path amplitude of the two propagation paths. Then, the value is fixed. Calculate the remaining spectrum vector of the first propagation path. And then from what was obtained Recalculation Next, the value of the first objective function is calculated. Steps A and B are repeated until convergence is achieved. Convergence specifically refers to the state where the difference between two consecutive iterations of the first objective function is less than a predetermined threshold value.

[0119] Step C: Assume =2, obtained from step B The remaining spectrum vector of the third propagation path is obtained. ,according to estimate Calculate the value of the first objective function. Then, based on... Seeking Then by Re-estimation And calculate the value of the first objective function, based on Seeking , and then from calculate Next, calculate the value of the first objective function. Repeat steps A, B, and C until convergence. Continue in this manner until the number of propagation paths equals the number of paths, then stop adding new propagation paths.

[0120] In this embodiment, the weighted relaxation algorithm (WRELAX) is used to calculate the arrival time and path amplitude of multiple propagation paths in a ground-based navigation system. The principle of WRELAX is to estimate and adjust system variables (such as the arrival time and path amplitude of propagation paths) through an iterative optimization process. The core idea of ​​WRELAX is to introduce weights to weight the contributions of different paths and gradually adjust the estimated values ​​through relaxation operations to minimize the system's objective function (such as error or deviation). In each iteration, the arrival time and path amplitude are gradually optimized by updating the values ​​of variables and calculating the relationships between paths until convergence, thereby improving the estimation accuracy and the overall performance of the system.

[0121] Figure 2 A schematic diagram of a multipath TOA calculation system based on a ground-based navigation system provided in this embodiment of the invention is shown below. Figure 2 As shown, the system includes:

[0122] The signal spectrum acquisition module is used to acquire the signal spectrum transmitted by the ground-based navigation system and superimposed after passing through multiple propagation paths in the frequency domain channel of the ground-based navigation system, and to construct a discrete frequency domain channel impulse response model related to the signal spectrum;

[0123] The path number acquisition module is used to determine the number of propagation paths of the transmitted signal in the ground-based navigation system based on the signal spectrum.

[0124] The first objective function construction module is used to construct a first objective function based on the discrete frequency domain channel impulse response model, with the objective of optimizing the arrival time and path amplitude of multiple propagation paths of the ground-based navigation system.

[0125] The second objective function construction module is used to construct a second objective function based on the first objective function, with the objective of calculating the arrival time and path amplitude of a single propagation path.

[0126] The target parameter acquisition module is used to alternately correct the arrival time and path amplitude of all the propagation paths by gradually increasing the number of propagation paths and the second objective function until the first objective function converges, so as to obtain the target arrival time and target path amplitude of each propagation path of the ground-based navigation system.

[0127] In one embodiment of the present invention, the signal spectrum acquisition module includes:

[0128] The time-domain signal acquisition module is used to acquire time-domain signals received by the mobile terminal, transmitted by the ground-based navigation system, and superimposed after passing through multiple propagation paths in the time-domain channel.

[0129] A frequency domain signal conversion module is used to perform a Fourier transform operation on the time domain signal to convert the time domain signal into a frequency domain signal;

[0130] The signal spectrum sampling module is used to perform sampling operations on the frequency domain signal at multiple equally spaced frequency sampling points in the frequency domain channel to obtain the signal spectrum of the frequency domain signal.

[0131] In one embodiment of the present invention, the path count acquisition module includes:

[0132] A spectrum vector conversion module is used to convert the signal spectrum of the multiple acquired frequency domain signals into a spectrum vector;

[0133] The spectral autocorrelation matrix calculation module is used to perform expectation operation on the product between the spectral vector and the conjugate transpose of the spectral vector to obtain the spectral autocorrelation matrix;

[0134] The first eigenvalue calculation module is used to select the eigenvalues ​​of the spectral autocorrelation matrix as the first eigenvalues, starting from the estimated number of propagation paths plus 1 and ending with the number of eigenvalues ​​of the effective eigenvalues ​​of the spectral autocorrelation matrix; the effective eigenvalues ​​are non-zero values.

[0135] The second eigenvalue calculation module is used to perform exponentiation on each of the first eigenvalues ​​to obtain the second eigenvalue;

[0136] The geometric mean calculation module is used to add up the individual second characteristic values ​​to obtain the geometric mean;

[0137] The arithmetic mean calculation module is used to multiply the sum of each of the first feature values ​​by the reciprocal of the difference between the number of features and the estimated number of propagation paths to obtain the arithmetic mean.

[0138] The logarithmic mean calculation module is used to perform a logarithmic operation on the ratio between the geometric mean and the arithmetic mean to obtain the logarithmic mean;

[0139] The first target multipath function acquisition module is used to multiply the negative of the logarithmic mean by a weighting term to obtain the first target multipath function of the propagation path number estimate; the weighting term is the difference between the number of features and the propagation path number estimate multiplied by the number of frequency domain sampling points;

[0140] The path number calculation module is used to calculate the minimum value of the first target multipath function to determine the value of the propagation path number estimate; the value of the propagation path number estimate is the number of propagation paths of the transmitted signal in the ground-based navigation system.

[0141] or,

[0142] The second objective multipath function construction module is used to take the sum between the first objective multipath function and the complexity penalty term as the second objective multipath function;

[0143] The multipath quantity calculation module is used to determine the value of the estimated number of propagation paths with the objective of calculating the minimum value of the second target multipath function.

[0144] In one embodiment of the present invention, the first objective function construction module includes:

[0145] The matrix form conversion module is used to convert the discrete frequency domain channel impulse response model into matrix form;

[0146] The first objective function acquisition module is used to construct a first objective function to optimize the arrival time and path amplitude of each propagation path of the ground-based navigation system by minimizing the square of the residual energy between the signal spectrum and the discrete frequency domain channel impulse response model after completing the matrix form transformation.

[0147] The matrix form is expressed as follows:

[0148]

[0149]

[0150]

[0151]

[0152] The first objective function is expressed as:

[0153] = ;

[0154] in, Let x be the residual energy vector and x be the spectrum vector. As the guide vector, The number of paths in the propagation path. The path amplitude of the propagation path described in the k-th rule. The residual energy corresponding to L frequency sampling points, Let L be the signal spectrum corresponding to L frequency sampling points, where j is the imaginary unit. For the center frequency, For frequency intervals, The arrival time of the propagation path described in the k-th path. Let be the first objective function.

[0155] In one embodiment of the present invention, the second objective function construction module includes:

[0156] The remaining spectrum vector calculation module is used to take the difference between the spectrum vector and the linear superposition components of other propagation paths as the remaining spectrum vector; other propagation paths are the determined propagation paths other than the propagation paths whose arrival time and path amplitude are to be calculated.

[0157] The second objective function acquisition module is used to modify the first objective function into a second objective function based on the remaining spectrum vector, with the objective of calculating the arrival time and path amplitude of a single propagation path.

[0158] The second objective function is expressed as:

[0159]

[0160]

[0161] in, The remaining spectrum vector, The spectrum vector, For linear superposition components of other propagation paths, The number of paths. Let the path amplitude be the k-th propagation path. The guide vector, Let the second objective function be... The path amplitude of the propagation path to be optimized. This is the guide vector for the propagation path to be optimized.

[0162] In one embodiment of the present invention, the target parameter acquisition module includes:

[0163] The initial arrival time addition module is used to randomly add an initial arrival time to each of the propagation paths by traversing the arrival time search range of the propagation paths.

[0164] The first propagation path calculation module is used to calculate the arrival time and path amplitude of the first propagation path if the number of propagation paths is 1; the first propagation path is the propagation path when the number of propagation paths is 1.

[0165] The propagation path addition module is used to add a propagation path based on the established propagation path, the arrival time of the first propagation path, and the path amplitude, and to obtain the steering vector corresponding to the initial arrival time of the newly added propagation path.

[0166] The path amplitude calculation module is used to calculate the path amplitude of the newly added propagation path by dividing the product of the conjugate transpose of the steering vector corresponding to the initial arrival time of the newly added propagation path and the remaining spectral vector of the newly added propagation path by the product of the conjugate transpose of the steering vector corresponding to the initial arrival time of the newly added propagation path and the steering vector at the initial arrival time.

[0167] The arrival time calculation module is used to optimize the initial arrival time of the newly added propagation path based on the path amplitude of the newly added propagation path with the goal of minimizing the second objective function, so as to obtain the arrival time of the newly added propagation path.

[0168] The parameter update module is used to repeatedly update the arrival time and path amplitude of the determined propagation path based on the arrival time, path amplitude, and parameter alternation update strategy of the newly added propagation path until the first objective function converges.

[0169] The path quantity determination module is used to determine whether the current number of propagation paths has reached the number of propagation paths of the ground-based navigation system; if yes, the target parameter determination module is executed; if no, the process returns to the propagation path addition module.

[0170] The target parameter determination module is used to determine the arrival time and path amplitude of each of the propagation paths as the target arrival time and target path amplitude, respectively.

[0171] In one embodiment of the present invention, the first propagation path calculation module includes:

[0172] The steering vector acquisition module is used to acquire the steering vector corresponding to the initial arrival time based on the initial arrival time of the first propagation path if the number of propagation paths is 1.

[0173] The path strength calculation module is used to obtain the path amplitude of the first propagation path by dividing the product of the conjugate transpose of the steering vector corresponding to the initial arrival time of the first propagation path and the remaining spectral vector of the first propagation path by the product of the conjugate transpose of the steering vector corresponding to the initial arrival time of the first propagation path and the steering vector corresponding to the initial arrival time.

[0174] The arrival time determination module is used to optimize the initial arrival time by means of the path amplitude with the goal of calculating the minimum value of the second objective function, so as to obtain the arrival time of the first propagation path.

[0175] In one embodiment of the present invention, the parameter update module includes:

[0176] The first parameter fixing module is used to fix the arrival time and path amplitude of the newly added propagation path, re-optimize the arrival time and path amplitude of the determined propagation paths other than the newly added propagation path, and calculate the target value of the first objective function.

[0177] The second parameter fixing module is used to fix the arrival time and path amplitude of the propagation paths other than the newly added propagation paths if optimization is completed, re-optimize the arrival time and path amplitude of the newly added propagation paths, and calculate the target value of the first objective function.

[0178] The alternating update module is used to repeatedly and alternately optimize the arrival time and path amplitude of all propagation paths under the current number of paths until the difference between two adjacent target values ​​is less than a preset threshold. Then, it is determined that the arrival time and path amplitude of the determined propagation path have converged.

[0179] The multipath TOA calculation system based on a ground-based navigation system provided in this embodiment of the invention can execute the multipath TOA calculation method based on a ground-based navigation system provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the multipath TOA calculation method based on a ground-based navigation system.

[0180] Figure 3This is a schematic diagram of an electronic device provided for an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0181] like Figure 3 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer programs stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, the ROM 12, and the RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0182] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0183] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as multipath TOA calculation methods based on ground-based navigation systems.

[0184] In some embodiments, the multipath TOA calculation method based on a ground-based navigation system can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via read-only memory ROM 12 and / or communication unit 19. When the computer program is loaded into random access memory RAM 13 and executed by processor 11, one or more steps of the multipath TOA calculation method based on a ground-based navigation system described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the multipath TOA calculation method based on a ground-based navigation system by any other suitable means (e.g., by means of firmware).

[0185] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0186] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0187] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0188] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer device having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0189] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0190] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0191] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the multipath TOA calculation method based on a ground-based navigation system as provided in any embodiment of this invention.

[0192] In implementing the computer program product, computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0193] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0194] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A multipath TOA calculation method based on a ground-based navigation system, characterized in that, The method includes: In the frequency domain channel of the ground-based navigation system, the signal spectrum transmitted by the ground-based navigation system and superimposed after passing through multiple propagation paths is collected, and a discrete frequency domain channel impulse response model related to the signal spectrum is constructed. The number of propagation paths for the transmitted signal in the ground-based navigation system is determined based on the signal spectrum. Based on the discrete frequency domain channel impulse response model, a first objective function is constructed with the aim of optimizing the arrival time and path amplitude of multiple propagation paths of the ground-based navigation system. Based on the first objective function, a second objective function is constructed with the objective of calculating the arrival time and path amplitude of a single propagation path. By gradually increasing the number of propagation paths and the second objective function, the arrival time and path amplitude of all propagation paths are alternately corrected until the first objective function converges, so as to obtain the target arrival time and target path amplitude of each propagation path of the ground-based navigation system. The first objective function, constructed based on the discrete frequency domain channel impulse response model to optimize the arrival time and path amplitude of multiple propagation paths of the ground-based navigation system, includes: The discrete frequency domain channel impulse response model is transformed into matrix form; If the matrix form transformation is completed, a first objective function is constructed to optimize the arrival time and path amplitude of each propagation path of the ground-based navigation system by minimizing the square of the residual energy between the signal spectrum and the discrete frequency domain channel impulse response model. The matrix form is expressed as follows: ； ； ； ； The first objective function is expressed as: = ； in, Let x be the residual energy vector and x be the spectrum vector. As the guide vector, The number of paths in the propagation path. Let the path amplitude be the k-th propagation path. The residual energy corresponding to L frequency sampling points, Let L be the signal spectrum corresponding to L frequency sampling points, where j is the imaginary unit. For the center frequency, For frequency intervals, Let k be the arrival time of the propagation path. Let the first objective function be ; The construction of a second objective function based on the first objective function, which aims to calculate the arrival time and path amplitude of a single propagation path, includes: The difference between the spectral vector and the linear superposition components of other propagation paths is taken as the remaining spectral vector; the other propagation paths are the determined propagation paths other than the propagation paths whose arrival time and path amplitude are to be calculated. Based on the remaining spectrum vector, the first objective function is modified into a second objective function that aims to calculate the arrival time and path amplitude of a single propagation path; The second objective function is expressed as: ； in, The remaining spectrum vector, The spectrum vector, For linear superposition components of other propagation paths, The number of paths. For the first The path amplitude of each propagation path, As the guide vector, Let the second objective function be... The path amplitude of the propagation path to be optimized. This is the guide vector for the propagation path to be optimized.

2. The method according to claim 1, characterized in that, The acquisition of the signal spectrum transmitted by the ground-based navigation system and superimposed after passing through multiple propagation paths in the frequency domain channel of the ground-based navigation system includes: The time-domain signal received by the mobile terminal, transmitted by the ground-based navigation system, and superimposed after passing through multiple propagation paths is acquired in the time-domain channel. Perform a Fourier transform operation on the time-domain signal to convert the time-domain signal into a frequency-domain signal; In the frequency domain channel, a sampling operation is performed on the frequency domain signal at multiple equally spaced frequency sampling points to obtain the signal spectrum of the frequency domain signal.

3. The method according to claim 2, characterized in that, Determining the number of propagation paths of the transmitted signal in the ground-based navigation system based on the signal spectrum includes: The signal spectra of the multiple frequency domain signals collected are converted into spectrum vectors; The product of the spectrum vector and its conjugate transpose is expected to obtain the spectrum autocorrelation matrix. Starting with the estimated number of propagation paths plus 1 and ending with the number of features of the effective eigenvalues ​​of the spectral autocorrelation matrix, the eigenvalues ​​of the spectral autocorrelation matrix are selected as the first eigenvalues; the effective eigenvalues ​​are non-zero values. The second eigenvalue is obtained by exponentiation of each of the first eigenvalues; The geometric mean is obtained by summing the individual second eigenvalues. Multiply the sum of each of the first feature values ​​by the reciprocal of the difference between the number of features and the estimated number of propagation paths to obtain the arithmetic mean. The logarithmic mean is obtained by taking the logarithm of the ratio between the geometric mean and the arithmetic mean. The first target multipath function is obtained by multiplying the negative of the logarithmic mean by a weighting term; the weighting term is the difference between the number of features and the estimated number of propagation paths multiplied by the number of frequency domain sampling points. The minimum value of the first target multipath function is calculated to determine the value of the propagation path number estimate; the value of the propagation path number estimate is the number of propagation paths of the transmitted signal in the ground-based navigation system. or, The sum between the first objective multipath function and the complexity penalty term is used as the second objective multipath function; The goal is to calculate the minimum value of the second target multipath function to determine the value of the estimated number of propagation paths.

4. The method according to claim 1, characterized in that, The step of gradually increasing the number of propagation paths and the second objective function, and alternately correcting the arrival time and path amplitude of all propagation paths until the first objective function converges, to obtain the target arrival time and target path amplitude of each propagation path of the ground-based navigation system, includes: By traversing the arrival time search range of the propagation paths, an initial arrival time is randomly added to each of the propagation paths; If the number of propagation paths is 1, then calculate the arrival time and path amplitude of the first propagation path; the first propagation path is the propagation path when the number of propagation paths is 1. Based on the established propagation path, the arrival time and path amplitude of the first propagation path, add a propagation path and obtain the steering vector corresponding to the initial arrival time of the newly added propagation path. The path amplitude of the newly added propagation path is obtained by dividing the product of the conjugate transpose of the steering vector corresponding to the initial arrival time of the newly added propagation path and the remaining spectral vector of the newly added propagation path by the product of the conjugate transpose of the steering vector corresponding to the initial arrival time of the newly added propagation path and the steering vector at the initial arrival time. With the goal of minimizing the second objective function, the initial arrival time of the newly added propagation path is optimized based on the path amplitude of the newly added propagation path to obtain the arrival time of the newly added propagation path. Based on the arrival time and path magnitude of the newly added propagation path, a parameter alternation update strategy is adopted to repeatedly update the arrival time and path magnitude of the determined propagation path until the first objective function converges. Determine whether the current number of propagation paths has reached the total number of propagation paths of the ground-based navigation system; if yes, determine that the arrival time and path amplitude of each propagation path are the target arrival time and target path amplitude, respectively; if no, return to the step of adding a propagation path based on the already determined first propagation path, and obtain the remaining spectrum vector of the newly added propagation path.

5. The method according to claim 4, characterized in that, If the number of propagation paths is 1, then the arrival time and path amplitude of the first propagation path are calculated, including: If the number of propagation paths is 1, the steering vector corresponding to the initial arrival time is obtained based on the initial arrival time of the first propagation path; The path amplitude of the first propagation path is obtained by dividing the product of the conjugate transpose of the steering vector corresponding to the initial arrival time of the first propagation path and the remaining spectral vector of the first propagation path by the product of the conjugate transpose of the steering vector corresponding to the initial arrival time of the first propagation path and the steering vector corresponding to the initial arrival time. With the goal of minimizing the second objective function, the initial arrival time is optimized by using the amplitude of the first propagation path to obtain the arrival time of the first propagation path.

6. The method according to any one of claims 1-5, characterized in that, The method of alternatingly updating the arrival time and path amplitude of the determined propagation path based on the arrival time, path amplitude, and parameters of the newly added propagation path, until the first objective function converges, includes: Fix the arrival time and path amplitude of the newly added propagation path, re-optimize the arrival time and path amplitude of the existing propagation paths other than the newly added propagation path, and calculate the target value of the first objective function; If the optimization is complete, fix the arrival time and path amplitude of the propagation paths other than the newly added propagation paths, re-optimize the arrival time and path amplitude of the newly added propagation paths, and calculate the target value of the first objective function; Repeatedly and alternately optimize the arrival time and path amplitude of all propagation paths under the current number of paths until the difference between two adjacent target values ​​is less than a preset threshold. Then, it is determined that the arrival time and path amplitude of the determined propagation paths have converged.

7. A multipath TOA calculation system based on a ground-based navigation system, characterized in that, The system includes: The signal spectrum acquisition module is used to acquire the signal spectrum transmitted by the ground-based navigation system after passing through multiple propagation paths and superimposed in the frequency domain channel of the ground-based navigation system, and to construct a discrete frequency domain channel impulse response model related to the signal spectrum. The path number acquisition module is used to determine the number of propagation paths of the transmitted signal in the ground-based navigation system based on the signal spectrum. The first objective function construction module is used to construct a first objective function based on the discrete frequency domain channel impulse response model, with the objective of optimizing the arrival time and path amplitude of multiple propagation paths of the ground-based navigation system. The second objective function construction module is used to construct a second objective function based on the first objective function, with the objective of calculating the arrival time and path amplitude of a single propagation path. The target parameter acquisition module is used to alternately correct the arrival time and path amplitude of all the propagation paths by gradually increasing the number of propagation paths and the second objective function until the first objective function converges, so as to obtain the target arrival time and target path amplitude of each propagation path of the ground-based navigation system. The first objective function construction module further includes: A matrix form conversion module is used to convert the discrete frequency domain channel impulse response model into matrix form; The first objective function acquisition module is used to construct a first objective function to optimize the arrival time and path amplitude of each propagation path of the ground-based navigation system by minimizing the square of the residual energy between the signal spectrum and the discrete frequency domain channel impulse response model after completing the matrix form transformation. The matrix form is expressed as follows: The first objective function is expressed as: = ； in, Let x be the residual energy vector and x be the spectrum vector. As the guide vector, The number of paths in the propagation path. The path amplitude of the propagation path described in the k-th rule. The residual energy corresponding to L frequency sampling points, Let L be the signal spectrum corresponding to L frequency sampling points, where j is the imaginary unit. For the center frequency, For frequency intervals, The arrival time of the propagation path described in the k-th path. Let the first objective function be ; The second objective function construction module also includes: The remaining spectrum vector calculation module is used to take the difference between the spectrum vector and the linear superposition components of other propagation paths as the remaining spectrum vector; other propagation paths are the determined propagation paths other than the propagation paths whose arrival time and path amplitude are to be calculated. The second objective function acquisition module is used to modify the first objective function into a second objective function based on the remaining spectrum vector, with the objective of calculating the arrival time and path amplitude of a single propagation path. The second objective function is expressed as: in, The remaining spectrum vector, The spectrum vector, For linear superposition components of other propagation paths, The number of paths. Let the path amplitude be the k-th propagation path. The guide vector, Let the second objective function be... The path amplitude of the propagation path to be optimized. This is the guide vector for the propagation path to be optimized.

8. An electronic device, characterized in that, The electronic device includes: One or more processors; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the multipath TOA calculation method based on a ground-based navigation system as described in any one of claims 1-6.

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