Target positioning method, device, storage medium and program product

Abstract

The application discloses a target positioning method and device, a storage medium and a program product, relates to the technical field of communication and perception integration, and discloses a target positioning method, which is applied to a communication base station and includes the following steps: sending a perception signal to at least one target object; receiving a return wave signal of the perception signal reflected by the at least one target object; acquiring prior information of the at least one target object, and processing the return wave signal based on the prior information to obtain an angle measurement value and a distance measurement value of the at least one target object; and determining positioning information of the at least one target object according to the angle measurement value and the distance measurement value. According to the technical scheme, the calculation complexity of the positioning information measurement scheme can be reduced while accurately positioning multiple targets, and a better balance between positioning performance and complexity is achieved.

Description

Technical Field

[0001] This application relates to the field of integrated communication and sensing technology, and in particular to a target positioning method, device, storage medium, and program product. Background Technology

[0002] Integrating the communication and sensing functions of mobile communication systems is an important research direction in the industry. Existing sensing schemes for locating passive objects within this integrated communication and sensing framework can be broadly categorized into two types: joint measurement schemes for object angles and distances, and independent measurement schemes.

[0003] However, when using joint measurement schemes to locate multiple targets, the echo signals from these targets overlap, causing phase difference information to intertwine and making it impossible to distinguish the angular distance parameters of different targets. This limits their applicability to single-target object localization scenarios. While independent measurement schemes support multi-target localization, they still suffer from high computational complexity. Common MUSIC algorithms require a full traversal of spectral peaks for searching. Although iterative optimization algorithms (such as the dung beetle algorithm) reduce complexity, they are highly sensitive to parameters and prone to performance-complexity imbalances when the localization scenario changes.

[0004] Therefore, existing technologies lack solutions that balance the accuracy and complexity of multi-target positioning.

[0005] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0006] The main objective of this application is to provide a target positioning method, device, storage medium, and program product, aiming to solve the technical problem that the existing technology lacks a solution that balances the accuracy and complexity of multi-target positioning.

[0007] To achieve the above objectives, this application proposes a target positioning method, which is applied to a communication base station, and the method includes:

[0008] Send a sensing signal to at least one target object;

[0009] Receive the echo signal reflected by the sensing signal after passing through the at least one target object;

[0010] Acquire prior information about the at least one target object, and process the echo signal based on the prior information to obtain the angle measurement value and distance measurement value of the at least one target object;

[0011] Based on the angle measurement value and the distance measurement value, the positioning information of the at least one target object is determined.

[0012] In one embodiment, the step of obtaining prior information about the at least one target object includes:

[0013] Obtain the neighbor perception information of the at least one target object;

[0014] Based on the neighbor perception information, the prior information of the at least one target object is determined, and the prior information includes at least the target object's position and velocity information.

[0015] In one embodiment, the step of processing the echo signal based on the prior information to obtain the angle measurement value and distance measurement value of the at least one target object includes:

[0016] Based on the prior information, at least one spatial domain of the target object is constructed, and the spatial domain includes at least one of a two-dimensional angle domain and a position domain.

[0017] Based on the echo signal, determine the received signal matrix;

[0018] Based on the spatial domain union of the at least one target object, the received signal matrix is ​​processed using a multiple signal classification algorithm to obtain the angle measurement value of the at least one target object.

[0019] Beamforming is performed on the echo direction corresponding to the angle measurement value of at least one target object in the echo signal to obtain at least one single-path echo signal.

[0020] Based on the single-path echo signal and the sensing signal, construct the observation matrix of the at least one target object;

[0021] Based on the spatial domain of the target object, the observation matrix is ​​processed using a multiple signal classification algorithm to obtain the distance measurement value of at least one target object.

[0022] In one embodiment, the step of constructing at least one spatial domain of the target object based on the prior information includes:

[0023] Based on the target object's position and velocity information, determine the target object's maximum acceleration information;

[0024] Based on the target object's position information, velocity information, and maximum acceleration information, determine the spherical region of the target object in a preset spherical coordinate system;

[0025] The location domain of the target object is determined based on the center position and radius of the spherical region.

[0026] In one embodiment, the step of constructing at least one spatial domain of the target object based on the prior information further includes:

[0027] The conical angle domain in the preset spherical coordinate system is determined based on the spherical region.

[0028] The two-dimensional angle domain of the target object is determined based on the half-apex angle of the conical angle domain and the two-dimensional angle of the center of the spherical region.

[0029] In one embodiment, the step of processing the received signal matrix using a multiple signal classification algorithm based on the spatial domain union of the at least one target object to obtain the angle measurement value of the at least one target object includes:

[0030] The union of the two-dimensional angular domains of the at least one target object is used as the first spatial spectrum range of the multiple signal classification algorithm;

[0031] The received signal matrix is ​​processed using the aforementioned multiple signal classification algorithm to construct an angle spectrum function;

[0032] Based on the first spatial spectrum range, a spectral peak search is performed on the angle spectrum function to determine the angle measurement value of the at least one target object.

[0033] In one embodiment, the step of processing the observation matrix using a multiple signal classification algorithm based on the spatial domain of the target object to obtain the distance measurement value of at least one target object includes:

[0034] For each target object, the second spatial spectrum range of the multiple signal classification algorithm is determined based on the location domain of the target object;

[0035] The observation matrix is ​​processed using the aforementioned multiple signal classification algorithm to construct a time delay spectrum function;

[0036] Based on the second spatial spectrum range, a spectral peak search is performed on the time delay spectrum function to obtain the propagation time of the echo signal corresponding to the target object;

[0037] The distance measurement of the target object is determined based on the propagation time and the speed of light.

[0038] In addition, to achieve the above objectives, this application also proposes a target positioning device, the device comprising: a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the target positioning method as described above.

[0039] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the target localization method described above.

[0040] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the target localization method described above.

[0041] One or more technical solutions proposed in this application have at least the following technical effects:

[0042] The target positioning method, device, storage medium, and program product proposed in this application specifically involve sending a sensing signal to at least one target object; receiving the echo signal reflected by the sensing signal after passing through the at least one target object; acquiring prior information of the at least one target object; processing the echo signal based on the prior information to obtain the angle measurement value and distance measurement value of the at least one target object; and determining the positioning information of the at least one target object based on the angle measurement value and distance measurement value.

[0043] This application utilizes a communication base station to send sensing communication signals to one or more target objects and receive one or more echo signals reflected by the target objects. By acquiring prior information about the target objects and processing the echo signals, angle and distance measurements of one or more target objects are obtained. By combining this with the location information of the communication base station, accurate positioning of one or more target objects can be achieved. At the same time, utilizing prior information can effectively reduce the computational complexity in the angle and distance measurement process, thus ensuring accurate positioning of multiple targets while reducing the computational complexity of the positioning information measurement scheme, achieving a better balance between positioning performance and complexity. Attached Figure Description

[0044] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0045] To more clearly illustrate the technical solutions 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, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 This is a flowchart illustrating an embodiment of the target location method of this application.

[0047] Figure 2 This is a flowchart illustrating Embodiment 2 of the target location method of this application;

[0048] Figure 3This is a flowchart illustrating Embodiment 3 of the target location method of this application;

[0049] Figure 4 This is a schematic diagram of the device structure of the hardware operating environment involved in the target localization method in this application embodiment;

[0050] Figure 5 This is a geometric model of an object positioning scene involved in Embodiment 2 of this application.

[0051] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0052] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0053] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0054] The main solution of this application embodiment is: sending a sensing signal to at least one target object; receiving the echo signal reflected by the sensing signal after passing through the at least one target object; obtaining prior information of the at least one target object, and processing the echo signal based on the prior information to obtain the angle measurement value and distance measurement value of the at least one target object; and determining the positioning information of the at least one target object based on the angle measurement value and distance measurement value.

[0055] Technical terms used in this application:

[0056] Integrated Sensing and Communication (ISAC): ISAC is a key technology in the 5G / 6G field, aiming to enable communication systems to simultaneously support high-speed data transmission and environmental perception (such as target detection, localization, and speed measurement) through collaborative hardware and software design. Its core lies in sharing spectrum, hardware, and channel resources, breaking down the functional boundaries between traditional communication and radar / sensing systems. For example, in vehicle-to-everything (V2X) systems, base stations can simultaneously transmit data and sense vehicle locations, improving resource utilization. Advantages include reduced equipment costs, enhanced system reliability, and a technological foundation for future intelligent transportation and smart cities.

[0057] Multiple Signal Classification (MUSIC) is a signal processing technique based on high-resolution spectral estimation, used to separate and identify multiple signal sources in complex environments. Its principle is to decompose a mixed signal into independent components by calculating the orthogonality between the signal subspace and the noise subspace. Typical applications include radar multi-target identification, interference suppression in wireless communication, and medical imaging. The algorithm achieves accurate classification through feature extraction (such as time-frequency domain analysis) and machine learning models (such as deep learning), performing particularly well in low signal-to-noise ratio environments and significantly improving the system's adaptability to multipath effects and multi-user concurrency scenarios.

[0058] In this embodiment, for ease of description, the target positioning device will be used as the execution subject in the following description.

[0059] Integrating the communication and sensing functions of mobile communication systems is a key research direction in the industry. Existing research reports on the integration of communication and sensing indicate that future applications include smart factories, smart transportation, smart living, and drone surveillance.

[0060] In the integration of communication and sensing, various sensing services are mainly based on state parameters such as object position, velocity, and acceleration. Therefore, the sensing performance of object state parameters is the main factor affecting the quality of sensing services.

[0061] Localization of passive objects is a crucial component of the sensing function in integrated communication and sensing. Existing sensing schemes for the localization of passive objects mainly fall into two categories: joint measurement schemes for object angles and distances, and independent measurement schemes.

[0062] While the joint measurement scheme for object angle and distance can measure angle and distance information simultaneously, its drawback is that it can only locate a single object. When multiple objects exist in the scene, their echo signals overlap, making it impossible to distinguish the angle and distance information between each object and the base station. Therefore, this type of scheme is not suitable for locating multiple objects.

[0063] Independent measurement schemes can be used to simultaneously locate multiple objects in a scene, thus broadening their application scope. These schemes typically begin by measuring the angles of the received echo signals. Existing angle measurement algorithms include conventional beamforming and MUSIC algorithms. Then, based on the direction of each object relative to the base station obtained from the angle measurement, beamforming is performed in each direction. This effectively retains only the signal from the echo direction of each object, filtering out the received signals from other directions, thereby selecting the echo signals of each object. Then, algorithms such as Inverse Fourier Transform (IFT) and MUSIC can be used to measure the distance between each individual object and the base station. Considering the lower resolution and susceptibility to interference, the MUSIC algorithm is more commonly used.

[0064] However, the spectrum construction and peak search process of the MUSIC algorithm requires a large amount of computation. Even if the peak search process that traverses all samples is modified to be implemented through iterative optimization algorithms, such as the dung beetle algorithm, genetic algorithm, and Newton descent algorithm, to reduce the computational complexity, the computational complexity of iterative optimization algorithms is highly dependent on the preset parameters. If the parameters are not appropriate, it will lead to problems such as performance degradation or insignificant reduction in computational complexity. When locating changes in the scene, performance-complexity imbalance is likely to occur.

[0065] Therefore, existing technologies lack solutions that balance the accuracy and complexity of multi-target positioning.

[0066] This application provides a solution that utilizes a communication base station to send sensing communication signals to one or more target objects and receive one or more echo signals reflected by the target objects. By acquiring prior information about the target objects, the echo signals are processed to obtain angle and distance measurements of one or more target objects. By combining this with the location information of the communication base station, accurate positioning of one or more target objects can be achieved. At the same time, utilizing prior information can effectively reduce the computational complexity in the angle and distance measurement process, thus ensuring accurate positioning of multiple targets while reducing the computational complexity of the positioning information measurement scheme, achieving a better balance between positioning performance and complexity.

[0067] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device or target positioning device capable of performing the above functions. The following description uses a target positioning device as an example to illustrate this embodiment and the subsequent embodiments.

[0068] Based on this, embodiments of this application provide a target localization method, referring to... Figure 1 , Figure 1This is a flowchart illustrating the first embodiment of the target location method of this application.

[0069] In this embodiment, the target positioning method is applied to a communication base station, and the target positioning method includes steps S10 to S40:

[0070] Step S10: Send a sensing signal to at least one target object;

[0071] Step S20: Receive the echo signal reflected by the sensing signal after passing through the at least one target object;

[0072] Since this application is applied to the integrated communication and sensing scenario, the target localization method is applied to a communication base station. The communication base station first sends a sensing signal to one or more passive objects (i.e., target objects) to be sensed in the current sensing scenario through steps S10 and S20, and receives the echo signal reflected by the target object. Then, the localization information of the target object, including position, direction, velocity, acceleration and other state parameters, is obtained by processing the echo signal reflected by the target object.

[0073] Furthermore, in the context of integrated communication and sensing, the sensing signal should be a signal used for communication, including FBMC (Filter Bank Multi-Carrier) waveforms, OTFS (Orthogonal Time Frequency Space) waveforms, OFDM (Orthogonal Frequency-Division Multiplexing) waveforms, and other communication signals. Since the widely used 4G and 5G mobile communication systems both use OFDM waveforms, the most compatible design approach is to use a portion of the resource elements (REs) in the OFDM signal for sensing. This integrates sensing functionality into the communication system without significantly altering the mobile communication equipment, reducing system upgrade costs. Therefore, in this embodiment, the sensing signal or echo signal is preferably an ODFM signal.

[0074] It should be understood that when the location information of the target object is unknown, and there are multiple target objects in the sensing scene, the target positioning device can transmit sensing signals to multiple target objects by radiating uniform OFDM signals into space, and at the same time receive multiple echo signals reflected by each target object in the sensing scene.

[0075] Step S30: Obtain prior information of the at least one target object, and process the echo signal based on the prior information to obtain the angle measurement value and distance measurement value of the at least one target object;

[0076] It should be noted that prior information includes, but is not limited to, prior knowledge such as predicted motion state data of the target object and environmental map data. Angle measurements refer to the azimuth and / or elevation angle measurements of the target object relative to the sensing system (i.e., the communication base station), while distance measurements characterize the straight-line distance between the target object and the sensing system.

[0077] Specifically, the target positioning device needs to acquire prior information about a target object before processing the echo signal reflected from it. If there are multiple target objects, prior information about all of them needs to be acquired beforehand. Then, by combining the prior information of all target objects, the device performs multi-level signal processing on the echo signal, including echo signal preprocessing, time-frequency domain analysis, direction-of-arrival (DOA) calculation (i.e., angle calculation of the target object), and distance calculation, to achieve angle and distance measurement of the target object.

[0078] A common way to combine prior information is to use the target object velocity information in the prior information to correct the frequency offset of the echo signal during the preprocessing of the echo signal, thereby improving the accuracy of distance measurement. In addition, after obtaining the preliminary angle measurement value and distance measurement value by calculation, the prior information can be used to further optimize them and improve the positioning accuracy of the object.

[0079] The core of calculating the direction of arrival (DOA) lies in inferring the spatial angle of the signal source by the phase difference of the received signals from multiple channels. This can be achieved using subspace decomposition algorithms (such as the MUSIC algorithm and rotation-invariant subspace algorithm), deep learning algorithms, compressed sensing and sparse reconstruction algorithms, and conventional beamforming algorithms.

[0080] The core of calculating the distance to a target object lies in calculating the time delay difference between the sensed signal and the echo signal, which can be achieved using algorithms such as the inverse Fourier transform algorithm and the MUSIC algorithm.

[0081] In one feasible implementation, the step of obtaining prior information of the at least one target object may include steps A301 to A302:

[0082] Step A301: Obtain the neighbor perception information of the at least one target object;

[0083] Step A302: Based on the adjacent perception information, determine the prior information of the at least one target object, wherein the prior information includes at least the target object's position and velocity information.

[0084] It should be noted that adjacent sensing information refers to the temporally adjacent sensing information of the target object in the previous sensing information of the communication base station before the current sensing during the continuous sensing process of the target object. The sensing information includes the target object's distance, speed, angle, position information, etc.

[0085] In this embodiment, before sensing the target object, the target positioning device needs to obtain the perception information of all target objects in the current perception scene in the previous n perceptions, and then determine the position, velocity, acceleration and trajectory of the target object based on the perception information, which constitutes the prior information of the target object. It should be understood that the number of n is not specifically limited.

[0086] It should be understood that this embodiment does not limit the method of obtaining the adjacent sensing information of the target object. It can be obtained by the current communication base station, one or more other communication base stations through the angle-distance-Doppler three-dimensional joint super-resolution method, or by superimposing the object Doppler frequency shift analysis method (such as maximum likelihood estimation or extended Kalman filtering) on ​​common joint measurement schemes and independent measurement schemes.

[0087] Step S40: Determine the positioning information of the at least one target object based on the angle measurement value and the distance measurement value.

[0088] Specifically, in a spatial coordinate system with the current communication base station as the origin, the target positioning device can obtain the three-dimensional coordinates of each target object in the current perception scene by combining the angle measurement value and the distance measurement value of each target object, that is, the positioning information of the target object.

[0089] This embodiment provides a target localization method. It utilizes a communication base station to send sensing communication signals to one or more target objects and receives one or more echo signals reflected by the target objects. By acquiring prior information about the target objects, the echo signals are processed to obtain angle and distance measurements of one or more target objects. By combining this with the location information of the communication base station, accurate localization of one or more target objects can be achieved. Simultaneously, utilizing prior information effectively reduces the computational complexity in the angle and distance measurement process, ensuring accurate localization of multiple targets while reducing the computational complexity of the localization information measurement scheme, achieving a better balance between localization performance and complexity.

[0090] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 2The step of processing the echo signal based on the prior information to obtain the angle measurement value and distance measurement value of the at least one target object includes steps S31 to S36:

[0091] Step S31: Based on the prior information, construct at least one spatial domain of the target object, wherein the spatial domain includes at least one of a two-dimensional angle domain and a position domain;

[0092] It should be noted that the spatial domain refers to the description of the possible distribution characteristics of the target object in physical space within the time interval t0 between the previous perception and the current perception, including but not limited to the two-dimensional angle domain and the position domain. Specifically, the two-dimensional angle domain refers to the range of possible azimuth and pitch angles of the target object within t0, while the position domain refers to the three-dimensional spatial range that the target object may exist within t0.

[0093] Specifically, the target localization device needs to construct one or more spatial domains of the target object using the aforementioned prior information, that is, to construct the two-dimensional angular domain and / or position domain of the target object. By constructing the spatial domain of the target object, the possible motion state characteristics of the target object at the time of the current perception can be transformed into quantifiable spatial parameters, thereby improving the robustness of angle and distance measurements.

[0094] In one feasible implementation, when the spatial domain is a location domain, step S31 may include steps A311 to A313:

[0095] Step A311: Based on the position and velocity information of the target object, determine the maximum acceleration information of the target object;

[0096] First, when constructing the position domain of the target object, it is possible to select a three-dimensional Cartesian coordinate system with the current communication base station as the origin. The maximum acceleration of the target object in the previous continuous sensing process can be determined by using the historical position and velocity information of the target object in the prior information. Then, using a dynamic model, such as a uniform acceleration model or a maneuvering target model, the maximum acceleration that the target object may generate in the current motion state can be further adjusted and obtained by adding acceleration noise values ​​that can be freely set according to the actual scene, or by setting the frequency of acceleration change.

[0097] Step A312: Based on the target object's position information, velocity information, and maximum acceleration information, determine the spherical region of the target object in a preset spherical coordinate system;

[0098] Step A313: Determine the location domain of the target object based on the center position and radius of the spherical region.

[0099] It should be noted that the preset spherical coordinate system is a three-dimensional coordinate system with the current communication base station as the center.

[0100] Reference Figure 5 The diagram illustrates a geometric model of an object localization scenario (i.e., a perception scenario). In a three-dimensional Cartesian coordinate system with the center of the antenna array plane as the origin, the target localization device first uses the position, velocity, and maximum acceleration information of each target object from prior information to determine the possible distribution area of ​​the target object in the current perception three-dimensional Cartesian coordinate system. Since the origin of the aforementioned three-dimensional Cartesian coordinate system coincides with that of a preset spherical coordinate system, the possible distribution area in the three-dimensional Cartesian coordinate system is converted into spherical coordinates for representation, i.e., a spherical region of the target object in the preset spherical coordinate system. Based on the center position and radius of this spherical region, the distance range between the target object and the current communication base station is determined, i.e., the location domain of the target object.

[0101] It should be noted that the target perception method in this application mainly considers the perception scenario of a single communication base station. The following explanation will take a static communication base station as an example.

[0102] Reference Figure 5 In the geometric model, the antenna array plane (representing the communication base station) is located in the YOZ plane, and the center of the array is located at the origin O of the coordinate system. There are N objects in the scene. The distance between the objects and the antenna array is much greater than the spacing between the antennas. Therefore, when the base station transmits signals to the objects and receives echo signals, the echo signals can be regarded as far-field signals, that is, the direction of the echo signals received by each antenna is approximately the same.

[0103] The elevation angle of the echo signal of the nth object is θ. n azimuth angle is θ n ∈[-90°, 90°], The object's position coordinates are (x... n ,y n ,z n The velocity of the motion is v n , n∈{1,2,...,N}.

[0104] In this object localization scenario, object perception is a continuous process. Let t0 be the time interval between the transmission of the previous perception signal and the current perception signal, and let the result of the previous position perception of the nth object be... The result of the previous speed perception was The maximum acceleration of the object measured during continuous sensing was

[0105] It should be understood that since the speed of radio signals is much greater than the speed of moving objects, t0 can be approximated as the time interval between the reception of the echo signals corresponding to the previous sensing signal and the current sensing signal by the communication base station. Both the previous position sensing and the previous velocity sensing are performed in three-dimensional space, allowing us to obtain values ​​for position and velocity in different dimensions.

[0106] Assume that the maximum acceleration of the nth object during this perception does not exceed If 'b' is a parameter that can be freely set according to the actual scene, then the possible location range of the object during this perception is a spherical region:

[0107]

[0108] In this system, the center of the sphere represents the target object, the radius of the sphere represents the range of positional change of the target object during this perception, and the distance between the center of the sphere and the origin of the coordinate system is also represented. and sphere radius They are expressed as follows:

[0109]

[0110] Then, during this perception, the distance d from the nth object to the origin of the coordinate system... n The range of values ​​for can be expressed as follows:

[0111]

[0112] The d represented in equation (4) above n The range of values ​​is the location domain of the target object.

[0113] In this embodiment, by first determining the maximum acceleration of the target object, and then determining the center position and radius of the spherical region of the target object in the preset spherical coordinate system, the possible distance range of the target object during this perception is obtained, which can reduce false positioning caused by multipath interference and improve the accuracy of object positioning.

[0114] Based on the above implementation method, when the spatial domain is a two-dimensional angle domain, step S31 may include steps B311 to B312:

[0115] Step B311: Determine the conical angle domain in the preset spherical coordinate system based on the spherical region;

[0116] Step B312: Determine the two-dimensional angle domain of the target object based on the half-apex angle of the conical angle domain and the two-dimensional angle of the center of the spherical region.

[0117] The target positioning device can determine the conical region, i.e., the conical angle domain, corresponding to the range of azimuth and elevation angles of the spherical region relative to the origin O of the spherical coordinate system, based on the aforementioned spherical region. This conical region is defined by taking all tangents from the origin O to the surface of the spherical region as its surface, and the ray from the origin O to the center of the sphere as its axis. The semi-apex angle α of the conical region is then... n It can be expressed as the following formula:

[0118]

[0119] The pitch angle of the line connecting the center of the ball to the origin O and azimuth This means that the target object is relative to the passage.

[0120] The elevation and azimuth angles of the base station, among which, and They can be expressed as follows:

[0121]

[0122] It should be understood that the pitch angle along the central axis of the cone is θ0, and the azimuth angle is... When the semi-vertical angle of the cone is α, the angular domain of the cone can be expressed in polar coordinates as follows:

[0123]

[0124] The pitch angle of the target object obtained above and azimuth and the semi-apex angle α of the conical region n Substituting into equation (8) above, we can obtain the two-dimensional angular domain that the nth object may exist in during this perception, which can be expressed as follows:

[0125]

[0126] In this embodiment, by determining the semi-apex angle of the conical region corresponding to the spherical region, the pitch angle and azimuth angle of the central axis of the conical region are further defined. By defining the direction of the signal source through the two-dimensional angle domain of the cone, the position range of the target can be further defined in the subsequent signal processing process, so as to reduce the computational complexity and positioning accuracy.

[0127] Step S32: Determine the received signal matrix based on the echo signal;

[0128] Step S33: Based on the spatial domain union of the at least one target object, the received signal matrix is ​​processed using a multi-signal classification algorithm to obtain the angle measurement value of the at least one target object.

[0129] It should be noted that in this embodiment, the MUSIC algorithm is used to process the echo signal. Specifically, based on the echo signals of N target objects in the current sensing scene, the two-dimensional angles of the N target objects relative to the communication base station are measured, where N is a positive integer not less than 1.

[0130] It should be understood that, in order for the communication base station to have the ability to measure two-dimensional angles, the antenna array used by the communication base station in this embodiment must contain more than three antennas, and the antennas cannot be arranged in a straight line. For the echo signals reflected by each target object received by the antenna array of the communication base station, they are arranged in a complex matrix according to the time-space dimension, that is, the received signal matrix, the dimension of which is M×K (M is the number of channels, that is, the number of antennas in the antenna array of the communication base station, and K is the number of sampling snapshots).

[0131] Specifically, the snapshots of the received signals from each antenna are arranged horizontally as row vectors, and the row vectors of different antennas are arranged vertically to form a received signal matrix, which can be expressed as follows:

[0132] Y = AS + N (10)

[0133] Among them, let Let U and V be a set of complex matrices of size U×V, where U and V are positive integers. Then the matrix... K is the number of sampling snapshots of the received signal, and M is the number of receiving antennas. Matrix A can be expanded as A = [a1, a2, ..., a...]. N ], a1, a2, ..., a N These are the steering vectors of the echo signals from the 1st, 2nd, ..., Nth target objects, with a magnitude of M×1, a n It can be expressed as the following formula:

[0134]

[0135] In the above formula, phase(m,n) is the phase difference between the signal received by the m-th antenna in the n-th steering vector and the zero-phase reference point, where m∈{1,2,...,M} and n∈{1,2,...,N}. For example, when using a uniform circular array and the zero-phase reference point is at the center of the array... Where j is the imaginary unit, r is the radius of the uniform circular array, c is the speed of light, and f0 is the center frequency of the signal. Furthermore, the matrix... To extract the phase information of the echo direction from the signal matrix, This is a Gaussian noise matrix.

[0136] By using the spatial domain union of N target objects in the current sensing scene, i.e. the two-dimensional angular domain union of N target objects, as the spatial spectrum construction and spectral peak search range of the MUSIC algorithm, the MUSIC algorithm can be used to measure the direction of the echo signal reflected by N target objects, i.e. the angular measurement value of N target objects relative to the communication base station.

[0137] Step S34: Beamforming is performed on the echo direction corresponding to the angle measurement value of at least one target object in the echo signal to obtain at least one single-path echo signal;

[0138] Step S35: Construct the observation matrix of the at least one target object based on the single-path echo signal and the sensing signal;

[0139] Step S36: Based on the spatial domain of the target object, the observation matrix is ​​processed using a multiple signal classification algorithm to obtain the distance measurement value of at least one target object.

[0140] It should be noted that beamforming refers to enhancing the signal strength in the target direction and suppressing interference from other directions by weighted summation of signals received from multiple channels. Common beamforming algorithms include delay-sum beamforming and adaptive beamforming algorithms.

[0141] Specifically, after acquiring the two-dimensional angles of N target objects relative to the communication base station in the current sensing scene, that is, the directions of the echo signals reflected by the N target objects, the target positioning device can perform beamforming on the echo signal direction corresponding to the angle measurement value of each target object, so as to make each beam contain only one single-path echo signal. This is equivalent to retaining only the signal of the echo direction reflected by each target object and filtering out the received signals in other directions, thereby selecting the single-path echo signal corresponding to each target object.

[0142] Then, the echo signals of each target object are processed using the inverse Fourier transform algorithm and the MUSIC algorithm, and the distance between each target object and the base station is measured to obtain the distances of N target objects relative to the communication base station in the current sensing scenario.

[0143] Specifically, the target positioning device divides the RE data on the single-path echo signal corresponding to a single target object with the known RE data at the same position in the sensing signal transmitted by the aforementioned communication base station, thereby extracting the phase shift of each RE and constructing the observation matrix corresponding to the target object. For example, the observation matrix corresponding to the echo signal of the nth object is as follows:

[0144]

[0145] Where K is the number of OFDM symbols and L is the number of subcarriers. Let τ be the approximate Doppler frequency shift of the echo signal from the nth object. n Let M be the signal propagation time of the echo signal from the nth object, T be the duration of one OFDM symbol, Δf be the subcarrier spacing, and f0 be the signal start frequency. Additionally, the observation matrix M... n It can be represented as a product of a set of column vectors and row vectors. in

[0146] For a single target object, the target localization device uses the position domain of the target object represented by equation (4) above as the spatial spectrum construction and spectral peak search range of the MUSIC algorithm, and applies this range to matrix M. n The MUSIC algorithm can be used to measure the angles of N target objects relative to a communication base station.

[0147] Finally, by combining the distance measurements and two-dimensional angle measurements of each target object relative to the communication base station, the positions of N objects relative to the center of the communication base station antenna array can be obtained, and can be converted from spherical coordinates to rectangular coordinates using the following formula:

[0148]

[0149] in, The measured three-dimensional rectangular coordinates of the nth object are... Let be the spherical coordinates of the nth object obtained from the measurement.

[0150] This embodiment provides a target localization method, which involves sending a sensing signal to at least one target object and receiving echo signals reflected by the sensing signal after passing through the at least one target object; acquiring prior information about the at least one target object; constructing at least one spatial domain of the target object based on the prior information, the spatial domain including at least one of a two-dimensional angle domain and a position domain; determining a received signal matrix based on the echo signal; processing the received signal matrix using a multi-signal classification algorithm based on the union of the spatial domains of the at least one target object to obtain angle measurements of the at least one target object; performing beamforming on the echo direction corresponding to the angle measurements of the at least one target object in the echo signal to obtain at least one single-path echo signal; constructing an observation matrix of the at least one target object based on the single-path echo signal and the sensing signal; processing the observation matrix using a multi-signal classification algorithm based on the spatial domain of the target object to obtain distance measurements of the at least one target object; and determining the localization information of the at least one target object based on the angle measurements and the distance measurements.

[0151] This embodiment, through the above-described scheme, can construct the spatial domain of multiple target objects using prior information. Based on the spatial domain of multiple target objects, and combined with the MUSIC algorithm, the angle of the echo signal reflected by the target objects is first calculated. Then, beamforming is performed using the calculated angle measurement values ​​to obtain the single-path echo signal corresponding to each target object. Finally, the distance is calculated using the MUSIC algorithm based on the spatial domain of multiple target objects. Compared with existing methods that reduce the computational complexity of the MUSIC spectrum peak search process through iterative optimization algorithms, the target localization method in this application does not rely on preset parameters. It only constructs the spatial domain of the target objects based on prior perception information, thereby reducing the complexity of MUSIC algorithm spectrum construction and spectrum peak search. This achieves a better balance between positioning performance and complexity while ensuring accurate localization of multiple targets and reducing the computational complexity of the localization information measurement scheme. At the same time, since prior perception information usually changes with the scene, the target localization method in this application has stronger applicability in different scenarios.

[0152] Based on the second embodiment of this application, in the third embodiment of this application, the content that is the same as or similar to that in the second embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 3 Step S33 includes steps S331 to S333:

[0153] Step S331: The union of the two-dimensional angular domains of the at least one target object is used as the first spatial spectrum range of the multiple signal classification algorithm;

[0154] Step S332: The received signal matrix is ​​processed using the multi-signal classification algorithm to construct the angle spectrum function;

[0155] Specifically, the target localization device merges the coverage areas of all target objects in the current perception scene in the two-dimensional angle domain into a spatial range, i.e., the union of the two-dimensional angle domains. The angle value range of the nth object is shown in equation (9), with s θ and The first spatial spectrum range of the MUSIC algorithm is constructed by using the pitch and azimuth sampling intervals, which are respectively used to construct the two-dimensional angle spectrum. The first spatial spectrum range refers to the search space used to constrain the MUSIC algorithm.

[0156] It should be noted that the MUSIC algorithm decomposes the received signal matrix into a signal subspace and a noise subspace, and constructs a spatial spectrum function by utilizing the orthogonality of the two. The number of peaks in the spatial spectrum function is the same as the number of target objects, and the direction corresponding to the peaks is the direction of the echo signal reflected by the target object.

[0157] In this embodiment, the target positioning device uses the MUSIC algorithm to measure the angles of the received signal matrices of multiple target objects. Therefore, the spatial spectrum function constructed by the MUSIC algorithm is called the angle spectrum function. Specifically, it calculates the covariance matrix of the received signal matrix, performs eigenvalue decomposition on the covariance matrix, determines the signal subspace and noise subspace of the received signal matrix, and thus constructs the angle spectrum function.

[0158] Step S333: Based on the first spatial spectrum range, perform a spectral peak search on the angle spectrum function to determine the angle measurement value of the at least one target object.

[0159] Then, based on the angular search range limited by the first spatial spectrum range, with s θ and The pitch and azimuth sampling intervals are used as the peak search for the two-dimensional angle spectrum, respectively. The number of peaks in the angle spectrum function obtained by the search determines the number of target objects in the current sensing scene, and the direction of the echo signal reflected by the target object is determined by the direction corresponding to the peak.

[0160] Further, based on the above embodiments, step S36 includes steps S361 to S364:

[0161] Step S361: For each target object, determine the second spatial spectrum range of the multiple signal classification algorithm based on the location domain of the target object;

[0162] Specifically, since the single-path echo signal corresponding to the target object is usually obtained by measuring the time delay of the signal using the MUSIC algorithm, when constructing the second spatial spectrum range of the MUSIC algorithm, it is necessary to convert the position domain of each target object in the current perception scene, i.e., the position domain of the nth object corresponding to the previous equation (4), into a time delay range expression in the time domain, and use this time delay range expression as the second spatial spectrum range for the MUSIC algorithm to calculate the echo signal time delay of the target object. Here, let c be the speed of light, and τ be the propagation time of the echo signal of the nth object. n The range can be expressed as follows:

[0163]

[0164] Step S362: The observation matrix is ​​processed using the multiple signal classification algorithm to construct the time delay spectrum function;

[0165] In this embodiment, the target positioning device uses the MUSIC algorithm to measure the time delay of the observation matrix corresponding to a single target object. Therefore, the spatial spectrum function constructed by the MUSIC algorithm is called the time delay spectrum function. Specifically, it calculates the covariance matrix of the conjugate transpose of the observation matrix, performs eigenvalue decomposition on the covariance matrix, determines its signal subspace and noise subspace, and thus constructs the time delay spectrum function.

[0166] Specifically, by using the aforementioned vector m R Considered as the steering vector in the MUSIC algorithm, for M n conjugate transpose The time delay spectrum function can be constructed using the MUSIC algorithm.

[0167] Step S363: Based on the second spatial spectrum range, perform a spectral peak search on the time delay spectrum function to obtain the propagation time of the echo signal corresponding to the target object;

[0168] Step S364: Determine the distance measurement value of the target object based on the propagation time and the speed of light.

[0169] Then, based on the time delay search range limited by the second spatial spectrum range, with s τ The sampling interval, used as the peak search interval for the time delay spectrum, is used to find the time delay corresponding to the peak position in the time delay spectrum function, thus determining the propagation time of the echo signal corresponding to the target object. Multiplying half of this propagation time by the speed of light yields the distance d between the nth object and the base station. n That is, the distance measurement value of the nth target object relative to the communication base station.

[0170] This embodiment provides a target localization method that can utilize the spatial domain of multiple target objects to construct the spectral search range of the MUSIC algorithm's angle spectrum and time delay spectrum. This allows for the first calculation of angle measurements on the echo signals reflected by the target objects, followed by the calculation of distance measurements on the single-path echo signals corresponding to each target object. By reducing the complexity of MUSIC algorithm spectrum construction and peak search, this method ensures accurate localization of multiple targets while reducing the computational complexity of the localization information measurement scheme, achieving a better balance between localization performance and complexity.

[0171] It is important to emphasize that, compared to methods that do not simplify the construction and search process of the MUSIC algorithm's spatial spectrum, the target localization method in this application offers optimizations in computational complexity. The sum of the computational complexities of the MUSIC algorithm used for angle and distance measurements in this target localization method is as follows:

[0172]

[0173] The total computational complexity without simplification is as follows:

[0174]

[0175] Where P is the number of antennas in the antenna array, Q is the number of signal snapshots, and d min and d max These represent the minimum and maximum possible distances between all objects and the antenna array that need to be set in existing methods. Considering that the sensing in the applicable scenario of this application is continuous, the time interval between two adjacent sensing is generally in the sub-second range, the distribution of all objects to be sensed generally does not fill the entire range of elevation angle -90° to 90° and azimuth angle -90° to 90°, and the acceleration of objects generally does not exceed the acceleration due to gravity, and the coverage area of ​​a single base station is generally in the hundreds of meters range, the angle range and distance range of object sensing in this application can be limited by the following formula:

[0176]

[0177] In summary, the target localization method in this application reduces the computational load of the object localization process compared to existing methods. Furthermore, the greater the possible angle and distance range between the object and the base station, and the smaller the object's acceleration, the more obvious the computational complexity advantage of the target localization method in this application becomes.

[0178] This application provides a target positioning device, which includes: at least one transceiver, the transceiver being used to transmit sensing signals and receive echo signals reflected by the sensing signals after passing through a target object, at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the target positioning method in the above embodiment 1.

[0179] The following is for reference. Figure 4 This document illustrates a structural schematic diagram of a target positioning device suitable for implementing embodiments of this application. The target positioning device in this application includes a transceiver 510, a processor 500, a memory 520, and a program or instructions stored in the memory 520 and executable on the processor 500; when the processor 500 executes the computer program or instructions, it implements the aforementioned target positioning method applied to a communication base station. The transceiver 510 is used to receive and transmit data under the control of the processor 500. Wherein, in Figure 4In this configuration, the bus architecture 530 may include any number of interconnected buses and bridges, specifically linking various circuits together including transceiver 510, one or more processors represented by processor 500, and memory represented by memory 520. The bus architecture may also link various other circuits such as peripherals, voltage regulators, and power management circuitry. Transceiver 510 may consist of multiple components, including transmitters and receivers, providing a unit for communicating with various other devices over a transmission medium. Processor 500 is responsible for managing the bus architecture and general signal processing, and memory 520 may store data used by processor 500 during operation.

[0180] The target positioning device provided in this application, employing the target positioning method described in the above embodiments, can solve the technical problem of the lack of a solution in the prior art that balances the accuracy and complexity of multi-target positioning. Compared with the prior art, the beneficial effects of the target positioning device provided in this application are the same as those of the target positioning method described in the above embodiments, and other technical features of the target positioning device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0181] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0182] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0183] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the target localization method in the above embodiments.

[0184] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having 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. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0185] The aforementioned computer-readable storage medium may be included in the target positioning device; or it may exist independently and not assembled into the target positioning device.

[0186] The aforementioned computer-readable storage medium carries one or more programs that, when executed by a target positioning device, cause the target positioning device to: send a sensing signal to at least one target object; receive an echo signal reflected by the sensing signal after passing through the at least one target object; acquire prior information about the at least one target object, and process the echo signal based on the prior information to obtain an angle measurement value and a distance measurement value of the at least one target object; and determine the positioning information of the at least one target object based on the angle measurement value and the distance measurement value.

[0187] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming 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).

[0188] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0189] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0190] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described target localization method. This addresses the technical problem of the prior art lacking a solution that balances the accuracy and complexity of multi-target localization. Compared to the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the target localization method provided in the above embodiments, and will not be elaborated upon here.

[0191] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the target localization method described above.

[0192] The computer program product provided in this application can solve the technical problem that the prior art lacks a solution that balances the accuracy and complexity of multi-target positioning. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the target positioning method provided in the above embodiments, and will not be repeated here.

[0193] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A target localization method, characterized in that, The target localization method is applied to a communication base station, and the target localization method includes: Send a sensing signal to at least one target object; Receive the echo signal reflected by the sensing signal after passing through the at least one target object; Acquire prior information about the at least one target object, and process the echo signal based on the prior information to obtain the angle measurement value and distance measurement value of the at least one target object; Based on the angle measurement value and the distance measurement value, the positioning information of the at least one target object is determined; The step of obtaining prior information about the at least one target object includes: Acquire the adjacent sensing information of the at least one target object. The adjacent sensing information refers to the temporally adjacent sensing information of the target object in the previous sensing information of the communication base station before the current sensing during the continuous sensing of the target object. Based on the adjacent perception information, the prior information of the at least one target object is determined, and the prior information includes at least the target object's position and velocity information; The step of processing the echo signal based on the prior information to obtain the angle measurement value and distance measurement value of the at least one target object includes: Based on the prior information, at least one spatial domain of the target object is constructed, and the spatial domain includes at least one of a two-dimensional angle domain and a position domain. Based on the echo signal, determine the received signal matrix; Based on the spatial domain union of the at least one target object, the received signal matrix is ​​processed using a multiple signal classification algorithm to obtain the angle measurement value of the at least one target object. Beamforming is performed on the echo direction corresponding to the angle measurement value of at least one target object in the echo signal to obtain at least one single-path echo signal. Based on the single-path echo signal and the sensing signal, construct the observation matrix of the at least one target object; Based on the spatial domain of the target object, the observation matrix is ​​processed using a multiple signal classification algorithm to obtain the distance measurement value of at least one target object.

2. The target localization method as described in claim 1, characterized in that, The step of constructing at least one spatial domain of the target object based on the prior information includes: Based on the target object's position and velocity information, determine the target object's maximum acceleration information; Based on the target object's position information, velocity information, and maximum acceleration information, determine the spherical region of the target object in a preset spherical coordinate system; The location domain of the target object is determined based on the center position and radius of the spherical region.

3. The target localization method as described in claim 2, characterized in that, The step of constructing at least one spatial domain of the target object based on the prior information further includes: The conical angle domain in the preset spherical coordinate system is determined based on the spherical region. The two-dimensional angle domain of the target object is determined based on the half-apex angle of the conical angle domain and the two-dimensional angle of the center of the spherical region.

4. The target localization method as described in claim 1, characterized in that, The step of processing the received signal matrix using a multiple signal classification algorithm based on the spatial domain union of the at least one target object to obtain the angle measurement value of the at least one target object includes: The union of the two-dimensional angular domains of the at least one target object is used as the first spatial spectrum range of the multiple signal classification algorithm; The received signal matrix is ​​processed using the aforementioned multiple signal classification algorithm to construct an angle spectrum function; Based on the first spatial spectrum range, a spectral peak search is performed on the angle spectrum function to determine the angle measurement value of the at least one target object.

5. The target localization method as described in claim 1, characterized in that, The step of processing the observation matrix using a multiple signal classification algorithm based on the spatial domain of the target object to obtain the distance measurement value of at least one target object includes: For each target object, the second spatial spectrum range of the multiple signal classification algorithm is determined based on the location domain of the target object; The observation matrix is ​​processed using the aforementioned multiple signal classification algorithm to construct a time delay spectrum function; Based on the second spatial spectrum range, a spectral peak search is performed on the time delay spectrum function to obtain the propagation time of the echo signal corresponding to the target object; The distance measurement of the target object is determined based on the propagation time and the speed of light.

6. A target positioning device, characterized in that, The device includes: a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the target localization method as described in any one of claims 1 to 5.

7. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the target localization method as described in any one of claims 1 to 5.

8. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of the target localization method as described in any one of claims 1 to 5.

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