A direction finding method and device for a terminal device, a device and a storage medium

Abstract

The application discloses a direction finding method and device for a terminal device, equipment and a storage medium, the method comprises the following steps: in response to a direction finding instruction for a target terminal device, obtaining a received signal and spatial spectrum estimation information corresponding to the received signal; performing spectrum peak effectiveness identification on the spatial spectrum estimation information to obtain target spectrum peak identification information; performing direction finding confidence analysis based on the target spectrum peak identification information to obtain direction finding confidence information; and in the case that the direction finding confidence information meets a preset confidence condition, obtaining direction finding information of the target terminal device based on the spatial spectrum estimation information. The technical scheme provided by the application can solve the problem of how to use a spectrum estimation algorithm to direction find a terminal device in the case that the number of interference signal sources is unknown, and improve the applicability and accuracy of the direction finding method for the terminal device.

Description

Technical Field

[0001] This application relates to the field of wireless communication, specifically to a direction finding method, apparatus, device, and storage medium for terminal devices. Background Technology

[0002] Among traditional direction-finding algorithms, the MUSIC (Multiple Signal Classification) spectrum estimation algorithm has the highest direction-finding resolution. In an interference-free environment, as long as a very weak signal is received, the MUSIC algorithm can accurately determine the wave direction. Furthermore, the MUSIC algorithm can simultaneously measure the direction of multiple signal sources, as long as the number of signal sources is less than the number of antennas.

[0003] In a 5G public network environment, interference between cells is severe, primarily including downlink base station interference and uplink user terminal interference. However, using the MUSIC direction-finding algorithm requires prior knowledge of the number of signal sources at the time of measurement. In the context of multi-cell interference in a 5G public network, it is difficult to directly obtain the current number of signal sources. For example, at cell edges, the direction-finding device may receive co-channel interference from user terminals in adjacent cells, making it impossible to determine how many user terminals are simultaneously transmitting co-channel signals. Furthermore, due to the high-resolution nature of the MUSIC algorithm, interference from distant, non-adjacent cells can significantly impact the direction-finding results. Therefore, a more versatile technical solution is needed. Summary of the Invention

[0004] This application provides a direction-finding method, apparatus, device, and storage medium for terminal devices, which can solve the problem of how to use a spectrum estimation algorithm to find the direction of a terminal device when the number of interference signal sources is unknown, thereby improving the applicability and accuracy of the direction-finding method for terminal devices. The technical solution of this application is as follows:

[0005] On the one hand, a direction finding method for a terminal device is provided, the method comprising:

[0006] In response to a direction finding command for a target terminal device, the received signal and the spatial spectrum estimation information corresponding to the received signal are acquired;

[0007] The spatial spectrum estimation information is used to identify the validity of spectral peaks to obtain target spectral peak identification information;

[0008] Direction finding confidence analysis is performed based on the target spectral peak identification information to obtain direction finding confidence information;

[0009] When the direction finding confidence information meets the preset confidence conditions, the direction finding information of the target terminal device is obtained based on the spatial spectrum estimation information.

[0010] On the other hand, a direction-finding device for a terminal device is provided, the device comprising:

[0011] The signal acquisition module is used to acquire the received signal and the spatial spectrum estimation information corresponding to the received signal in response to the direction finding command for the target terminal device.

[0012] The spectral peak validity identification module is used to identify the spectral peak validity of the spatial spectrum estimation information to obtain target spectral peak identification information;

[0013] The direction finding confidence analysis module is used to perform direction finding confidence analysis based on the target spectral peak identification information to obtain direction finding confidence information;

[0014] The direction finding information determination module is used to obtain the direction finding information of the target terminal device based on the spatial spectrum estimation information, provided that the direction finding confidence information meets the preset confidence conditions.

[0015] On the other hand, a direction finding device for a terminal device is provided, the device including a processor and a memory, the memory storing at least one instruction or at least one program, the at least one instruction or the at least one program being loaded and executed by the processor to implement the direction finding method for the terminal device as described above.

[0016] On the other hand, a computer-readable storage medium is provided, wherein at least one instruction or at least one program is stored therein, the at least one instruction or the at least one program being loaded and executed by a processor to implement the direction finding method for a terminal device as described above.

[0017] This application provides a direction-finding method, apparatus, device, and storage medium for terminal devices, which has the following technical advantages:

[0018] This application obtains target peak identification information by identifying the validity of the spectral peaks in the spatial spectrum estimation information corresponding to the received signal, and then performs direction finding confidence analysis based on the target spectral peak identification information to obtain direction finding confidence information. When the direction finding confidence information meets the preset confidence conditions, the direction finding information is obtained based on the spatial spectrum estimation results. This solves the problem of how to use the spatial spectrum estimation algorithm to find the direction of terminal equipment when the number of interference signal sources is unknown, and improves the applicability and accuracy of the direction finding method for terminal equipment. Attached Figure Description

[0019] To more clearly illustrate the technical solutions and advantages in the embodiments of this application 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 only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of an application environment provided in an embodiment of this application;

[0021] Figure 2 This is a flowchart illustrating a direction-finding method for a terminal device provided in an embodiment of this application;

[0022] Figure 3 This is a schematic diagram of a process for identifying the validity of spectral peaks in spatial spectral estimation information to obtain target spectral peak identification information, provided in an embodiment of this application.

[0023] Figure 4 This is a schematic diagram of spatial spectrum estimation information provided in an embodiment of this application;

[0024] Figure 5 This is a flowchart illustrating another direction-finding method for terminal devices provided in an embodiment of this application;

[0025] Figure 6 This is a schematic diagram of a process for analyzing the number of signal sources based on received signals to obtain the number of potential signal sources, provided in an embodiment of this application.

[0026] Figure 7 This is a schematic diagram of a process for analyzing the number of signal sources based on a target number of feature values ​​to obtain the number of potential signal sources, provided in an embodiment of this application.

[0027] Figure 8 This is a schematic diagram of another process provided in this application embodiment for analyzing the number of signal sources based on received signals to obtain the number of potential signal sources;

[0028] Figure 9 This is a schematic diagram of a process for determining the number of potential signal sources by comparing spectral estimation information using different numbers of signal sources, provided in an embodiment of this application.

[0029] Figure 10 This is a flowchart illustrating a process for obtaining direction finding confidence information by performing direction finding confidence analysis based on the number of potential signal sources and target spectral peak identification information, as provided in an embodiment of this application.

[0030] Figure 11 This is a flowchart illustrating a direction-finding method for a terminal device under interference conditions, provided in an embodiment of this application.

[0031] Figure 12 This is a schematic diagram of a direction-finding device for a terminal device provided in an embodiment of this application;

[0032] Figure 13 This is a hardware structure block diagram of a server for a direction finding method for terminal devices provided in an embodiment of this application. Detailed Implementation

[0033] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0034] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application 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 application 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 server 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 devices.

[0035] Please see Figure 1 , Figure 1 This is a schematic diagram of an application environment provided in an embodiment of this application, such as... Figure 1 As shown, the above application environment includes user equipment 01 and direction finding equipment 02. Optionally, the above application environment can be a 5G public network environment.

[0036] Specifically, user equipment 01 may include mobile terminals such as smartphones, desktop computers, tablets, laptops, digital assistants, and smart wearable devices. Specifically, user equipment 01 can transmit uplink signals.

[0037] Specifically, direction finding device 02 can be a multi-antenna direction finding device, which may include a base station, a direction finding vehicle, or a handheld direction finding device. Specifically, direction finding device 02 can, in response to a direction finding command for a target terminal device, acquire the received signal and the corresponding spatial spectrum estimation information; perform signal source quantity analysis based on the received signal to obtain the number of potential signal sources; identify the validity of spectral peaks in the spatial spectrum estimation information to obtain target spectral peak identification information; perform direction finding confidence analysis based on the number of potential signal sources and the target spectral peak identification information to obtain direction finding confidence information; and, if the direction finding confidence information meets preset confidence conditions, obtain the direction finding information of the target terminal device based on the spatial spectrum estimation information.

[0038] In practical applications, when the number of interference source signals around user equipment 01 is unknown, direction finding device 02 can respond to direction finding commands for the target terminal device, acquire the received signal and the corresponding spatial spectrum estimation information, then perform signal source number analysis based on the received signal to obtain the number of potential signal sources, then perform spectral peak validity identification on the spatial spectrum estimation information to obtain target spectral peak identification information, and then perform direction finding confidence analysis based on the number of potential signal sources and target spectral peak identification information to obtain direction finding confidence information. If the direction finding confidence information meets the preset confidence conditions, the direction finding information of the target terminal device can be obtained based on the spatial spectrum estimation information.

[0039] The following describes a direction-finding method for terminal devices provided by embodiments of this application. Figure 2 This is a flowchart illustrating a direction-finding method for a terminal device provided in an embodiment of this application. It should be noted that this specification provides the operational steps of the method described in the embodiments or flowcharts, but based on conventional or non-inventive labor, more or fewer operational steps may be included. The order of steps listed in the embodiments is merely one possible execution order among many steps and does not represent the only execution order. In actual systems or products, the methods can be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment) as shown in the embodiments or accompanying drawings. Specifically, as... Figure 2 As shown, the above method may include:

[0040] S201, in response to a direction finding command for a target terminal device, acquires the received signal and the corresponding spatial spectrum estimation information.

[0041] In the embodiments of this specification, the target terminal device can be a wireless signal transmitting terminal; specifically, the target terminal device can include a mobile terminal.

[0042] In the embodiments of this specification, the received signal can be a signal obtained by the signal receiving module receiving the signal transmitted by the terminal. Specifically, the signal receiving module may include a multi-antenna receiving module.

[0043] In practical applications, spatial spectrum estimation technology has the ability to resolve multiple signals and can effectively solve the direction finding problem of multiple signals at the same frequency.

[0044] In the embodiments of this specification, the multi-antenna direction-finding device can perform spatial spectrum estimation on the acquired received signal to obtain spatial spectrum estimation information. Specifically, the spatial spectrum estimation information can characterize the estimation result of a signal spectrum.

[0045] In a specific embodiment, the method for obtaining the above-mentioned spatial spectrum estimation information may include:

[0046] The received signal is subjected to multi-signal classification spectrum estimation processing to obtain spatial spectrum estimation information.

[0047] Specifically, the Multiple Signal Classification (MUSIC) spectrum estimation algorithm uses the covariance matrix of the received data to perform eigenvalue decomposition, separating the signal subspace and the noise subspace. It then uses the orthogonality between the signal direction vector and the noise subspace to construct a spatial scanning spectrum, performs a global search for spectral peaks, and thus achieves signal parameter estimation.

[0048] S202, perform spectral peak validity identification on the spatial spectrum estimation information to obtain target spectral peak identification information.

[0049] In the embodiments of this specification, the target spectral peak identification information can characterize the effectiveness of spectral peak value identification.

[0050] In one specific embodiment, target spectral peak identification information can be obtained by analyzing the spatial spectrum estimation information of the received signal with a default signal source of 1.

[0051] In a specific embodiment, such as Figure 3 As shown, the above-mentioned identification of the effectiveness of spectral peaks in spatial spectral estimation information to obtain target spectral peak identification information may include:

[0052] S301, perform peak-to-peak identification on the spatial spectrum estimation information to obtain multiple peak-to-peak values.

[0053] S302, determine the first peak value and the second peak value among multiple spectral peak values.

[0054] Specifically, the value of the first spectral peak can be the maximum value among multiple spectral peak values, and the value of the second spectral peak can be the second largest value among multiple spectral peak values.

[0055] Specifically, the peak values ​​of multiple spectral peaks in the spatial spectrum estimation information are determined, and the maximum value M1 and the second largest value M2 are found. The maximum value M1 is taken as the first peak value, and the second largest value M2 is taken as the second peak value.

[0056] S303, based on the peak values ​​of the first and second spectral peaks, an effectiveness analysis is performed to obtain target spectral peak identification information.

[0057] Specifically, the target spectral peak identification information D can be 10log(M1 / M2), where M1 represents the peak value of the first spectral peak and M2 represents the peak value of the second spectral peak.

[0058] See Figure 4 ,by Figure 4 Taking the spatial spectrum estimation information shown as an example, M1 is 0 dB (decibels) = 1, M2 is -8 dB = -0.9, and D = 10log(M1 / M2) = 10log(1 / 0.9) = 1.

[0059] In one specific embodiment, the target spectral peak identification information can be calculated from the points where the derivative is zero in the spatial spectrum estimation information. Optionally, the target spectral peak identification information can be the quotient obtained by dividing the maximum value among the points where the derivative is zero by the second largest value among the points where the derivative is zero; alternatively, the target spectral peak identification information can be the dB value of the quotient obtained by dividing the maximum value among the points where the derivative is zero by the second largest value among the points where the derivative is zero.

[0060] As can be seen from the above embodiments, by analyzing the spectral peaks of the spatial spectrum estimation information of the received signal, the validity of the spectral peak values ​​can be identified, so as to determine the confidence level of the measurement results based on the validity of the spectral peak values.

[0061] S203, direction finding confidence analysis is performed based on target spectral peak identification information to obtain direction finding confidence information.

[0062] In the embodiments of this specification, direction-finding confidence information can characterize the reliability of direction-finding information obtained based on the spatial spectrum estimation information. Specifically, direction-finding confidence information may include: direction-finding confidence level.

[0063] In a specific embodiment, direction finding confidence analysis based on target spectral peak identification information can yield direction finding confidence information including:

[0064] 1) Perform direction finding confidence analysis based on target spectral peak identification information and reference spectral peak identification information to generate initial direction finding confidence information.

[0065] Specifically, the reference peak identification information can serve as a benchmark value for evaluating the target peak identification information. The initial direction finding confidence information can characterize the confidence level of the corresponding direction finding result under single signal source identification conditions.

[0066] In practical applications, the reference peak identification information can be preset in conjunction with the accuracy of the direction finding confidence analysis in the practical application. Optionally, the reference peak identification information can be 5.

[0067] 2) In the case of single signal source identification, the initial direction finding confidence information is used as the direction finding confidence information.

[0068] Specifically, single signal source identification means that the number of potential signal sources is 1. When the number of potential signal sources is 1, the initial direction finding confidence information is used as the direction finding confidence information.

[0069] In a specific embodiment, such as Figure 5 As shown, before performing direction finding confidence analysis based on target spectral peak identification information to obtain direction finding confidence information, the above method may further include:

[0070] S205, Analyze the number of signal sources based on the received signal to obtain the number of potential signal sources;

[0071] Accordingly, the direction finding confidence analysis based on the target spectral peak identification information yields the following direction finding confidence information:

[0072] S206. Direction finding confidence analysis is performed based on the number of potential signal sources and target spectral peak identification information to obtain direction finding confidence information.

[0073] In the embodiments of this specification, the number of potential signal sources can be the number of signal sources that may exist in the area where the multi-antenna direction-finding device is located.

[0074] As can be seen from the above embodiments, direction finding confidence analysis based on target spectral peak identification information and the number of potential signal sources can generate direction finding confidence information, which can further improve the accuracy of direction finding confidence information.

[0075] In an optional embodiment, the number of potential signal sources can be obtained by the distribution pattern of the eigenvalues ​​of the autocorrelation function Rx of the received signal, specifically, as shown in... Figure 6 As shown, the above analysis of the number of signal sources based on the received signal can yield the following potential signal source counts:

[0076] S601 generates the autocorrelation matrix of the received signal.

[0077] S602, calculate the target number of eigenvalues ​​corresponding to the autocorrelation matrix.

[0078] In practical applications, the target number of eigenvalues ​​can be preset in conjunction with the accuracy of the signal source number analysis. Optionally, the target number can be 4.

[0079] S603, based on the target number of feature values, analyze the number of signal sources to obtain the number of potential signal sources.

[0080] In a specific embodiment, taking a target quantity of 4 as an example, see [link to example]. Figure 7 The above analysis of the number of signal sources based on the target number of feature values ​​yields the following potential signal source counts:

[0081] The four feature values ​​are sorted in ascending order to obtain the sequence Y = {Y(1), Y(2), Y(3), Y(4)}. After normalizing Y, the normalized sequence feature value Z = {Y(1) / sum(Y), Y(2) / sum(Y), Y(3) / sum(Y), Y(4) / sum(Y)} = {Z(1), Z(2), Z(3), Z(4)} is obtained. Based on the sequence Z, the first quantity discrimination parameter A, the second quantity discrimination parameter B, and the third quantity discrimination parameter C are calculated. If A is the largest among the three parameters, the number of potential signal sources is determined to be 1. If B is the largest among the three parameters, the number of potential signal sources is determined to be 2. If C is the largest among the three parameters, the number of potential signal sources is determined to be 3.

[0082] In one specific embodiment, the first quantity discrimination parameter can be used to determine whether the number of potential signal sources is 1, the second quantity discrimination parameter can be used to determine whether the number of potential signal sources is 2, and the third quantity discrimination parameter can be used to determine whether the number of potential signal sources is 3.

[0083] Optionally, the first quantity discrimination parameter can be: (1 / Z(1)+1 / Z(2)+1 / Z(3))×Z(4) / 2.5; the second quantity discrimination parameter can be: (1 / Z(1)+1 / Z(2))×Z(4)×Z(3)×1.9; the third quantity discrimination parameter can be: (1 / Z(1))×Z(4)×Z(3)×Z(2)×15.

[0084] As can be seen from the above embodiments, by analyzing the number of signal sources based on the eigenvalues ​​corresponding to the autocorrelation matrix of the received signal, the number of potential signal sources can be obtained, which can effectively identify the number of potential signal sources in the environment where the direction finding equipment is located.

[0085] In another alternative embodiment, the number of potential signal sources can be obtained by comparing spatial spectrum estimation information obtained after spectrum estimation using different numbers of signal sources, specifically, as follows: Figure 8 As shown, the above analysis of the number of signal sources based on the received signal can yield the following potential signal source counts:

[0086] S801 performs spatial spectrum estimation on the received signal based on the preset number of signal sources to obtain initial spatial spectrum estimation information.

[0087] Specifically, the preset number of signal sources can be set in advance based on the accuracy of signal source quantity analysis in actual applications. Optionally, the preset number of signal sources can be 1.

[0088] S802, perform spectral peak identification on the initial spatial spectrum estimation information to obtain the number of initial spectral peaks.

[0089] S803, if the initial number of spectral peaks is greater than zero, increases the preset number of signal sources to obtain the updated number of signal sources.

[0090] S804, based on the updated number of signal sources, repeatedly executes the process of spatial spectrum estimation of the received signal based on the preset number of signal sources, obtaining initial spatial spectrum estimation information, and then performing peak identification on the initial spatial spectrum estimation information to obtain the initial number of peaks, until the current number of peaks is less than or equal to the number of peaks obtained in the previous peak identification process.

[0091] S805 uses the number of signal sources in the previous peak identification process as the number of potential signal sources.

[0092] Taking a preset signal source quantity of 1 as an example, refer to Figure 9 As shown, Figure 9 This application provides a flowchart illustrating a process for determining the number of potential signal sources by comparing spectral estimation information with different numbers of signal sources. The specific steps are as follows:

[0093] Step 1: Initially, the number of signal sources is P=1. Spatial spectrum estimation is performed to obtain the initial spatial spectrum estimation information.

[0094] Step 2: If there are no identifiable spectral peaks in the initial spatial spectrum estimation information, then P = P-1, and the current P is 0, which means that the number of potential signal sources is 0 and direction finding is not possible.

[0095] Step 3: If there are identifiable spectral peaks in the initial spatial spectrum estimation information, then P is increased by 1, and spatial spectrum estimation continues.

[0096] Step 4: If increasing P by 1 increases the number of identifiable peaks, return to Step 3 and repeat the process. Otherwise, set the number of signal sources P = P - 1 and end the loop.

[0097] As can be seen from the above embodiments, by comparing the spectral estimation information using different numbers of signal sources to determine the number of potential signal sources, the number of potential signal sources in the environment where the direction finding equipment is located can be effectively identified.

[0098] In a specific embodiment, such as Figure 10 As shown, the direction finding confidence analysis based on the number of potential signal sources and target spectral peak identification information can yield direction finding confidence information including:

[0099] S1001, based on the target spectral peak identification information and the reference spectral peak identification information, performs direction finding confidence analysis to generate initial direction finding confidence information.

[0100] Specifically, the reference peak identification information can serve as a benchmark value for evaluating the target peak identification information. The initial direction finding confidence information can characterize the confidence level of the corresponding direction finding result under single signal source identification conditions.

[0101] In practical applications, the reference peak identification information can be preset in conjunction with the accuracy of the direction finding confidence analysis in the practical application. Optionally, the reference peak identification information can be 5.

[0102] S1002, based on the initial direction finding confidence information and the number of potential signal sources, performs direction finding confidence analysis to generate direction finding confidence information.

[0103] Optionally, when the peak identification degree D of the spectral estimation is greater than or equal to the peak identification information F of the reference spectrum, the confidence degree of a single signal source when the number of signal sources P is 1 is considered to be 1 (or 100%). In this case, the initial direction finding confidence information is equal to D / F.

[0104] Optionally, after considering the number of potential signal sources P, the direction finding confidence information can be equal to D / (F×P).

[0105] As can be seen from the above embodiments, first performing direction finding confidence analysis based on target spectral peak identification information and reference spectral peak identification information to generate initial direction finding confidence information under single signal source identification conditions, and then performing direction finding confidence analysis based on the initial direction finding confidence information and the number of potential signal sources to generate direction finding confidence information, can effectively improve the accuracy of direction finding confidence information.

[0106] S204. Under the condition that the direction finding confidence information meets the preset confidence conditions, the direction finding information of the target terminal device is obtained based on the spatial spectrum estimation information.

[0107] In one specific embodiment, the preset information condition can be a preset information threshold.

[0108] Specifically, the preset confidence threshold can be set in advance based on the direction finding accuracy requirements of the actual application. Optionally, the preset confidence threshold can be 60%.

[0109] In a specific embodiment, obtaining the direction finding information of the target terminal device based on the spatial spectrum estimation information when the direction finding confidence information meets the preset confidence conditions may include: obtaining the direction finding information of the target terminal device based on the spatial spectrum estimation information when the direction finding confidence information is greater than the preset confidence threshold.

[0110] For example, if the confidence information of a certain direction finding result is greater than a preset confidence threshold of 60%, the direction finding result is used for subsequent processing.

[0111] In the embodiments of this specification, after performing direction finding confidence analysis based on the number of potential signal sources and target spectral peak identification information to obtain direction finding confidence information, the above method may further include: discarding spatial spectrum estimation information if the direction finding confidence information does not meet the preset confidence conditions.

[0112] In one specific embodiment, spatial spectrum estimation information is discarded when the direction finding confidence information is less than a preset confidence threshold.

[0113] See Figure 11 , Figure 11 This is a flowchart illustrating a direction-finding method for a terminal device under interference conditions, as provided in an embodiment of this application. The specific steps are as follows:

[0114] Step 1: The default number of signal sources is 1. Perform MUSIC spectrum estimation based on the autocorrelation function Rx of the signals received by each antenna.

[0115] Step 2: Determine the number P of potential signal sources.

[0116] Step 3: Calculate the target spectral peak identification information D based on the spectral estimation results in Step 1, including the following steps:

[0117] Step 3.1 Find all points in the results where the first derivative is 0, and find the maximum value M1 and the second largest value M2 among them;

[0118] Step 3.2 Calculate the target spectral peak identification information D = 10log(M1 / M2).

[0119] Step 4: Calculate the direction finding confidence information R based on the number of potential signal sources P and the target spectral peak identification information D. Let F be the reference spectral peak identification information, and the initial direction finding confidence information corresponding to a single signal source identification be 100%. Then the direction finding confidence information is: R = D / (F × P).

[0120] Step 5: If the direction finding confidence information of a certain direction finding result is greater than the preset confidence threshold S (e.g., 60%), use the direction finding result for subsequent processing. Otherwise, discard the direction finding result.

[0121] As can be seen from the embodiments of the direction-finding method for terminal devices provided in this application, the technical solution provided in this application can be used to analyze the number of signal sources based on the eigenvalues ​​corresponding to the autocorrelation matrix of the received signal, thereby obtaining the number of potential signal sources. Alternatively, the number of potential signal sources can be determined by comparing spectral estimation information using different numbers of signal sources, effectively identifying the number of potential signal sources in the environment where the direction-finding device is located. Furthermore, by analyzing the spectral peaks of the spatial spectral estimation information of the received signal, the validity of the spectral peak values ​​can be identified, facilitating subsequent determination of the confidence level of the measurement results based on the validity of the spectral peak values. Direction finding confidence analysis is performed based on target and reference spectral peak identification information to generate initial direction finding confidence information under single signal source identification conditions. Then, direction finding confidence analysis is performed based on the initial direction finding confidence information and the number of potential signal sources to generate direction finding confidence information, which can effectively improve the accuracy of direction finding confidence information. When the direction finding confidence information meets the preset confidence conditions, direction finding information is obtained based on the spatial spectrum estimation results. This solves the problem of how to use spatial spectrum estimation algorithms to perform direction finding on terminal devices when the number of interference signal sources is unknown, and improves the applicability and accuracy of direction finding methods for terminal devices.

[0122] This application provides a direction-finding device for terminal devices, such as... Figure 12 As shown, the above-mentioned device may include:

[0123] The signal acquisition module 1210 is used to acquire the received signal and the corresponding spatial spectrum estimation information in response to the direction finding command for the target terminal device;

[0124] The spectral peak validity identification module 1220 is used to identify the validity of spectral peaks in spatial spectrum estimation information to obtain target spectral peak identification information.

[0125] The direction finding confidence analysis module 1230 is used to perform direction finding confidence analysis based on target spectral peak identification information to obtain direction finding confidence information;

[0126] The direction finding information determination module 1240 is used to obtain the direction finding information of the target terminal device based on the spatial spectrum estimation information, provided that the direction finding confidence information meets the preset confidence conditions.

[0127] In one specific embodiment, the signal acquisition module 1210 described above may include:

[0128] The multi-signal classification spectrum estimation unit is used to perform multi-signal classification spectrum estimation processing on the received signal to obtain spatial spectrum estimation information.

[0129] In one specific embodiment, the above-mentioned peak validity identification module 1220 may include:

[0130] The peak-to-peak value identification unit is used to identify the peak-to-peak value of the spatial spectrum estimation information and obtain multiple peak-to-peak values.

[0131] A peak value determination unit is used to determine the first peak value and the second peak value among multiple peak values.

[0132] The validity analysis unit is used to perform validity analysis based on the peak values ​​of the first and second spectral peaks to obtain target spectral peak identification information.

[0133] In one specific embodiment, the above-described apparatus may further include:

[0134] The signal source quantity analysis module is used to analyze the number of signal sources based on the received signal to obtain the number of potential signal sources.

[0135] Accordingly, the aforementioned direction finding confidence analysis module 1230 may include:

[0136] The first direction finding confidence analysis unit is used to perform direction finding confidence analysis based on the number of potential signal sources and target spectral peak identification information to obtain direction finding confidence information.

[0137] In an optional embodiment, the signal source quantity analysis module described above may include:

[0138] The autocorrelation matrix generation unit is used to generate the autocorrelation matrix of the received signal;

[0139] The eigenvalue calculation unit is used to calculate the target number of eigenvalues ​​corresponding to the autocorrelation matrix;

[0140] The signal source quantity analysis unit is used to perform signal source quantity analysis based on the target number of feature values ​​to obtain the potential signal source quantity.

[0141] In another optional embodiment, the signal source quantity analysis module described above may include:

[0142] The spatial spectrum estimation unit is used to perform spatial spectrum estimation on the received signal based on a preset number of signal sources to obtain initial spatial spectrum estimation information.

[0143] The peak identification unit is used to identify the peaks in the initial spatial spectrum estimation information to obtain the number of initial peaks.

[0144] The preset signal source quantity increase unit is used to increase the preset signal source quantity when the initial number of spectral peaks is greater than zero, so as to obtain the updated signal source quantity;

[0145] The repeated execution unit is used to repeatedly execute the process of spatial spectrum estimation of the received signal based on the preset number of signal sources, from obtaining initial spatial spectrum estimation information to identifying spectral peaks based on the initial spatial spectrum estimation information, until the current number of spectral peaks is less than or equal to the number of spectral peaks obtained in the previous execution of the spectral peak identification process.

[0146] The potential signal source quantity unit is used to take the number of signal sources in the previous spectral peak identification process as the potential signal source quantity.

[0147] In one specific embodiment, the first direction-finding confidence analysis unit described above may include:

[0148] The initial direction finding confidence information unit is used to perform direction finding confidence analysis based on target spectral peak identification information and reference spectral peak identification information to generate initial direction finding confidence information.

[0149] The direction finding confidence information generation unit is used to perform direction finding confidence analysis based on the initial direction finding confidence information and the number of potential signal sources, and generate direction finding confidence information.

[0150] In the embodiments described in this specification, the above-mentioned apparatus may further include:

[0151] The spatial spectrum estimation information module is used to discard spatial spectrum estimation information when the direction finding confidence information does not meet the preset confidence conditions.

[0152] It should be noted that the apparatus in the device embodiment and the method embodiment are based on the same inventive concept.

[0153] This application provides a direction finding device for a terminal device. The direction finding device for a terminal device includes a processor and a memory. The memory stores at least one instruction or at least one program. The at least one instruction or at least one program is loaded and executed by the processor to implement the direction finding method for a terminal device as provided in the above method embodiments.

[0154] Memory can be used to store software programs and modules. The processor executes these stored software programs and modules to perform various functional applications and perform direction finding for terminal devices. Memory can primarily include a program storage area and a data storage area. The program storage area can store the operating system, application programs required for functions, etc.; the data storage area can store data created based on the use of the aforementioned devices. Furthermore, memory can include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, memory can also include a memory controller to provide the processor with access to the memory.

[0155] The methods and embodiments provided in this application can be executed in a mobile terminal, computer terminal, server, or similar computing device; that is, the aforementioned computer device may include a mobile terminal, computer terminal, server, or similar computing device. Taking running on a server as an example... Figure 13 This is a hardware structure block diagram of a server for a direction-finding method for terminal devices provided in an embodiment of this application. For example... Figure 13 As shown, the server 1300 can vary significantly due to different configurations or performance. It may include one or more central processing units (CPUs) 1310 (CPUs 1310 may include, but are not limited to, microprocessors such as MCUs or programmable logic devices such as FPGAs), a memory 1330 for storing data, and one or more storage media 1320 (e.g., one or more mass storage devices) for storing application programs 1323 or data 1322. The memory 1330 and storage media 1320 may be temporary or persistent storage. The program stored in the storage media 1320 may include one or more modules, each module may include a series of instruction operations on the server. Furthermore, the CPU 1310 may be configured to communicate with the storage media 1320 and execute the series of instruction operations stored in the storage media 1320 on the server 1300. Server 1300 may also include one or more power supplies 1360, one or more wired or wireless network interfaces 1350, one or more input / output interfaces 1340, and / or one or more operating systems 1321, such as Windows Server™, MacOS X™, Unix™, Linux™, FreeBSD™, etc.

[0156] The input / output interface 1340 can be used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of server 1300. In one example, the input / output interface 1340 includes a network interface controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the input / output interface 1340 may be a radio frequency (RF) module for wireless communication with the Internet.

[0157] Those skilled in the art will understand that Figure 13 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, server 1300 may also include... Figure 13 The more or fewer components shown, or having the same Figure 13 The different configurations shown.

[0158] This application embodiment also provides a storage medium, which can be disposed in a server to store at least one instruction or at least one program related to implementing a direction finding method for a terminal device in one of the method embodiments. The at least one instruction or the at least one program is loaded and executed by the processor to implement the direction finding method for a terminal device provided in the above method embodiments.

[0159] Optionally, in this embodiment, the storage medium may be located at at least one of the multiple network servers in a computer network. Optionally, in this embodiment, the storage medium may include, but is not limited to, 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.

[0160] As can be seen from the embodiments of the direction-finding method, apparatus, device, or storage medium for terminal devices provided in this application, the technical solution provided in this application can be used to analyze the number of signal sources based on the eigenvalues ​​corresponding to the autocorrelation matrix of the received signal to obtain the number of potential signal sources, or to determine the number of potential signal sources by comparing spectral estimation information using different numbers of signal sources, thus effectively identifying the number of potential signal sources in the environment where the direction-finding device is located; and, by analyzing the spectral peaks of the spatial spectral estimation information of the received signal, the validity of the spectral peak values ​​can be identified, so as to facilitate subsequent determination of the confidence of the measurement results based on the validity of the spectral peak values. Then, based on the target spectral peak identification information and the reference spectral peak identification information, direction finding confidence analysis is performed to generate initial direction finding confidence information under the single signal source identification case. Then, based on the initial direction finding confidence information and the number of potential signal sources, direction finding confidence analysis is performed again to generate direction finding confidence information, which can effectively improve the accuracy of direction finding confidence information. When the direction finding confidence information meets the preset confidence conditions, the direction finding information is obtained based on the spatial spectrum estimation results. This solves the problem of how to use the spatial spectrum estimation algorithm to perform direction finding on terminal equipment when the number of interference signal sources is unknown, and improves the applicability and accuracy of the direction finding method for terminal equipment.

[0161] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims can be performed in a different order than that shown in the embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0162] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of apparatus, devices, and storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0163] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware, or by a program instructing the relevant hardware to implement them. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.

[0164] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A direction-finding method for terminal devices, characterized in that, The method includes: In response to a direction finding command for a target terminal device, the received signal and the spatial spectrum estimation information corresponding to the received signal are acquired; Based on the received signal, a signal source quantity analysis is performed to obtain the number of potential signal sources; the number of potential signal sources is the number of potential signal sources in the area where the direction-finding device is located. The spatial spectrum estimation information is subjected to peak-to-peak identification to obtain multiple peak-to-peak values; Determine the first peak value and the second peak value among the plurality of spectral peak values; the first peak value is the maximum value among the plurality of spectral peak values, and the second peak value is the second largest value among the plurality of spectral peak values; Based on the peak values ​​of the first and second spectral peaks, an effectiveness analysis is performed to obtain target spectral peak identification information. When the target spectral peak identification information is greater than or equal to the reference spectral peak identification information, the quotient of the target spectral peak identification information and the reference spectral peak identification information is used as the initial direction finding confidence information; the initial direction finding confidence information characterizes the confidence level of the corresponding direction finding result under the single signal source identification case; The quotient of the initial direction finding confidence information and the number of potential signal sources is taken as the direction finding confidence information; When the direction finding confidence information meets the preset confidence conditions, the direction finding information of the target terminal device is obtained based on the spatial spectrum estimation information.

2. The method according to claim 1, characterized in that, The analysis of the number of signal sources based on the received signal to obtain the number of potential signal sources includes: Generate the autocorrelation matrix of the received signal; Calculate the target number of eigenvalues ​​corresponding to the autocorrelation matrix; Based on the target number of feature values, the number of signal sources is analyzed to obtain the number of potential signal sources.

3. The method according to claim 1, characterized in that, The analysis of the number of signal sources based on the received signal to obtain the number of potential signal sources includes: Based on a preset number of signal sources, spatial spectrum estimation is performed on the received signal to obtain initial spatial spectrum estimation information; The initial spatial spectrum estimation information is used to identify spectral peaks to obtain the number of initial spectral peaks; If the initial number of spectral peaks is greater than zero, the preset number of signal sources is increased to obtain the updated number of signal sources; Based on the updated number of signal sources, the process of performing spatial spectrum estimation on the received signal based on the preset number of signal sources to obtain initial spatial spectrum estimation information is repeated until the initial spatial spectrum estimation information is used to identify spectral peaks to obtain the initial number of spectral peaks, until the current number of spectral peaks is less than or equal to the number of spectral peaks obtained in the previous spectral peak identification process. The number of signal sources in the previous spectral peak identification process is taken as the number of potential signal sources.

4. The method according to any one of claims 1 to 3, characterized in that, After using the quotient of the initial direction-finding confidence information and the number of potential signal sources as the direction-finding confidence information, the method further includes: If the direction finding confidence information does not meet the preset confidence conditions, the spatial spectrum estimation information is discarded.

5. A direction-finding device for a terminal device, characterized in that, The device includes: The signal acquisition module is used to acquire the received signal and the spatial spectrum estimation information corresponding to the received signal in response to the direction finding command for the target terminal device. The signal source quantity analysis module is used to perform signal source quantity analysis based on the received signal to obtain the number of potential signal sources; the number of potential signal sources is the number of potential signal sources in the area where the direction finding device is located. The spectral peak validity identification module is used to identify the peak values ​​of the spatial spectrum estimation information to obtain multiple peak values; determine the first peak value and the second peak value among the multiple peak values; the first peak value is the maximum value among the multiple peak values, and the second peak value is the second largest value among the multiple peak values; and perform validity analysis based on the first peak value and the second peak value to obtain target peak identification information. The direction finding confidence analysis module is used to take the quotient of the target spectral peak identification information and the reference spectral peak identification information as initial direction finding confidence information when the target spectral peak identification information is greater than or equal to the reference spectral peak identification information; the initial direction finding confidence information represents the confidence level of the corresponding direction finding result in the case of single signal source identification; and the quotient of the initial direction finding confidence information and the number of potential signal sources is taken as direction finding confidence information. The direction finding information determination module is used to obtain the direction finding information of the target terminal device based on the spatial spectrum estimation information, provided that the direction finding confidence information meets the preset confidence conditions.

6. An electronic device, characterized in that, The device includes a processor and a memory, the memory storing at least one instruction or at least one program, the at least one instruction or the at least one program being loaded and executed by the processor to implement the direction finding method for a terminal device as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The storage medium stores at least one instruction or at least one program segment, which is loaded and executed by a processor to implement the direction finding method for a terminal device as described in any one of claims 1 to 4.

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