Object detection method, object detection device, electronic device, storage medium

Abstract

The present disclosure provides an object detection method, an object detection device, an electronic device and a computer readable storage medium, which belong to the technical field of wireless communication. The method comprises: receiving a first echo signal of a first probe signal sent by a first base station to a detected object; analyzing the first echo signal to determine communication awareness information; eliminating offset information in the communication awareness information to determine intermediate data; performing feature decomposition based on the intermediate data to determine a signal transmission posture parameter of a second probe signal sent to the detected object; sending the second probe signal to the detected object according to the signal transmission posture parameter, and receiving a second echo signal of the second probe signal to determine an object detection result of the detected object according to the second echo signal. The present disclosure can accurately and effectively detect the detected object through multiple base stations.

Description

Technical Field

[0001] This disclosure relates to the field of wireless communication technology, and in particular to an object detection method, an object detection device, an electronic device, and a computer-readable storage medium. Background Technology

[0002] Traditional multi-radar cooperative sensing algorithms, such as those using distributed fully coherent radar, place extremely stringent requirements on the synchronization accuracy and deployment location of multiple radars, making them unsuitable for direct application in cooperative sensing between multiple communication base stations. When locating surrounding airborne objects, traditional algorithms largely assume perfect clock synchronization between transceivers. While 3GPP (3rd Generation Partnership Project) TS 38.104 (a technical report or specification) stipulates that clock deviations between base stations cannot exceed 3 μs, even low clock skews on the order of tens of nanoseconds can significantly degrade positioning performance, making the time constraints for sensing far more stringent than those for communication. Currently, most operators rely solely on satellite time synchronization to address the issue, meeting the time synchronization requirements of the base station system by installing GPS (Global Positioning System) satellite receiver modules at base stations. However, using GPS time synchronization not only presents long-term security risks but also suffers from high installation requirements, high costs, and high failure rates.

[0003] Furthermore, existing technologies for collaborative object sensing using multiple base stations typically require good line-of-sight signals between the sensing base stations. When no line-of-sight signal exists between base stations, it becomes difficult to effectively and accurately detect the object being detected. Figure 1 As shown, when base station 1 and base station 2 are blocked by buildings, it is difficult to accurately perceive information such as the location and distance of the drone.

[0004] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] This disclosure provides an object detection method, an object detection device, an electronic device, and a computer-readable storage medium, thereby overcoming, to at least a certain extent, the problem in the prior art that the detected object cannot be accurately perceived when there is no line-of-sight signal between base stations.

[0006] Other features and advantages of this disclosure will become apparent from the following detailed description, or may be learned in part by practice of this disclosure.

[0007] According to one aspect of this disclosure, an object detection method is provided, comprising: receiving a first echo signal of a first detection signal sent by a first base station to a detected object; parsing the first echo signal to determine communication sensing information; eliminating offset information in the communication sensing information to determine intermediate data; performing feature decomposition based on the intermediate data to determine signal transmission attitude parameters for sending a second detection signal to the detected object; sending the second detection signal to the detected object according to the signal transmission attitude parameters, and receiving a second echo signal of the second detection signal, so as to determine an object detection result of the detected object based on the second echo signal.

[0008] In an exemplary embodiment of this disclosure, there are multiple objects to be detected, and each object receives a first echo signal after the first base station sends a first detection signal to it. Receiving the first echo signal of the first detection signal sent by the first base station to the object to be detected includes: receiving the first echo signal of the first detection signal sent by the first base station to the multiple objects to be detected through multiple antennas. Eliminating the offset information in the communication sensing information and determining intermediate data includes: transforming each first echo signal to the frequency domain based on the communication sensing information to determine the spectral data of each first echo signal in the frequency domain; performing cross-correlation operation on the spectral data of the multiple antennas of the second base station to eliminate the offset information in the communication sensing information to determine the intermediate data. The intermediate data includes a first component and a second component.

[0009] In an exemplary embodiment of this disclosure, the step of transforming each first echo signal to the frequency domain based on the communication sensing information and determining the spectral data of each first echo signal in the frequency domain includes: constructing an orthogonal frequency division multiplexing (OFDM) signal waveform of the first detection signal; determining the modulation symbol of the first detection signal based on the OFDM signal waveform; performing a Fourier transform on the first echo signal based on the communication sensing information, and determining the spectral data of each first echo signal in the frequency domain based on the modulation symbol.

[0010] In one exemplary embodiment of this disclosure, the step of performing cross-correlation operation on the spectrum data of multiple antennas of the second base station to eliminate offset information in the communication sensing information and determine the intermediate data includes: performing a dot product between the spectrum data of any antenna in the second base station other than the reference antenna and the spectrum data of the reference antenna to determine the intermediate data; the intermediate data does not contain clock offset information and subcarrier frequency offset information.

[0011] In an exemplary embodiment of this disclosure, after eliminating the offset information in the communication sensing information to determine the intermediate data, the method further includes: filtering the intermediate data using a filter to extract the second component; the step of performing feature decomposition based on the intermediate data to determine the signal transmission attitude parameters for sending the second detection signal to the detected object includes: performing feature decomposition on the second component to determine the signal transmission attitude parameters for sending the second detection signal to each of the detected objects.

[0012] In an exemplary embodiment of this disclosure, the signal transmission attitude parameters include angle of arrival parameters; the step of performing feature decomposition on the second component to determine the signal transmission attitude parameters for transmitting the second detection signal to each of the detected objects includes: acquiring a direction response vector, a coefficient matrix, and array noise; constructing a target signal matrix based on the second component, the direction response vector, the coefficient matrix, and the array noise; constructing a spatial spectrum based on the target signal matrix; and determining the angle of arrival parameters for transmitting the second detection signal to each of the detected objects by solving the spatial spectrum.

[0013] In one exemplary embodiment of this disclosure, constructing a spatial spectrum based on the target signal matrix includes: performing eigenvalue decomposition on the covariance matrix of the target signal matrix to obtain eigenvectors of the noise space; constructing a noise matrix based on the eigenvectors of the noise space; and constructing a spatial spectrum based on the noise matrix.

[0014] According to one aspect of this disclosure, an object detection apparatus is provided, applied to a second base station, comprising: a signal receiving module for receiving a first echo signal of a first detection signal sent by a first base station to a detected object; an information determination module for parsing the first echo signal to determine communication sensing information; an information elimination module for eliminating offset information in the communication sensing information to determine intermediate data; a parameter determination module for performing feature decomposition based on the intermediate data to determine signal transmission attitude parameters for sending a second detection signal to the detected object; and an object detection module for sending the second detection signal to the detected object according to the signal transmission attitude parameters and receiving a second echo signal of the second detection signal to determine an object detection result of the detected object based on the second echo signal.

[0015] According to one aspect of this disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the method described in any of the preceding methods by executing the executable instructions.

[0016] According to one aspect of this disclosure, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method described in any of the preceding claims.

[0017] The exemplary embodiments disclosed herein have the following beneficial effects:

[0018] The method involves receiving a first echo signal of a first detection signal sent by a first base station to a detected object; parsing the first echo signal to determine communication sensing information; eliminating offset information in the communication sensing information to determine intermediate data; performing feature decomposition based on the intermediate data to determine signal transmission attitude parameters for sending a second detection signal to the detected object; sending a second detection signal to the detected object according to the signal transmission attitude parameters; and receiving a second echo signal of the second detection signal to determine the object detection result based on the second echo signal. On one hand, this exemplary embodiment proposes a method for object detection through multi-base station active-passive collaboration. It processes the first echo signal of the first detection signal sent by the first base station to determine the signal transmission attitude parameters, and then actively sends a second detection signal to the detected object. The detection of the detected object is achieved based on the second echo signal. Even when there are obstacles between base stations and no line-of-sight signal, the object detection process can still be executed accurately and effectively, making it widely applicable. On the other hand, this exemplary embodiment avoids the problem of object detection accuracy being affected by asynchronous information between base stations by removing offset information, further ensuring the accuracy of object detection.

[0019] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0020] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure. It is obvious that the drawings described below are merely some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0021] Figure 1 This diagram illustrates a scenario involving a base station and a detected object.

[0022] Figures 2-3 This schematic diagram illustrates a system architecture of an object detection method in this exemplary embodiment.

[0023] Figure 4 This schematically illustrates a flowchart of an object detection method in this exemplary embodiment;

[0024] Figure 5 This schematically illustrates a system architecture diagram of another object detection method in this exemplary embodiment;

[0025] Figure 6 A sub-flowchart of an object detection method in this exemplary embodiment is illustrated schematically.

[0026] Figure 7 This schematically illustrates another sub-flowchart of an object detection method in this exemplary embodiment;

[0027] Figure 8 This schematically illustrates another sub-flowchart of an object detection method in this exemplary embodiment;

[0028] Figure 9 The diagram illustrates the interaction flowchart of an object detection method in this exemplary embodiment.

[0029] Figure 10 A schematic diagram of a spatial spectrum in this exemplary embodiment is shown.

[0030] Figure 11 A range-velocity radar graph is schematically illustrated in this exemplary embodiment.

[0031] Figure 12 This schematic diagram illustrates a structural block diagram of an object detection device in this exemplary embodiment.

[0032] Figure 13 An electronic device for implementing the above method is illustrated in this exemplary embodiment. Detailed Implementation

[0033] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that this disclosure will be more comprehensive and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0034] Exemplary embodiments of this disclosure first provide an object detection method. Figure 2 and Figure 3 A schematic diagram of the system architecture of the operating environment of this exemplary embodiment is shown, with reference to... Figure 2As shown, the system 200 may include a first base station 210, a second base station 220, and a detected object 230. The detected object 230 may be a drone, an aircraft, or other object requiring sensing and detection. There is no line-of-sight signal between the first base station 210 and the second base station 220, for example, due to obstruction by an obstacle, preventing direct signal communication between them. In this exemplary embodiment, the first base station 210 may first send a first detection signal to the detected object 230. The second base station 220 then passively senses the detected object 230 based on the first echo signal of the first detection signal to determine the signal transmission attitude parameters. Further, as... Figure 3 As shown, the second base station 220 can send a second detection signal to the object being detected 230 based on the signal transmission attitude parameters to perform active sensing and determine the object detection result of the object being detected 230.

[0035] It should be understood that Figure 1 The data for each device shown are merely illustrative. Any number of base stations or objects to be detected can be set up as needed.

[0036] Based on the above description, the method in this exemplary embodiment can be applied to... Figure 2 or Figure 3 The second base station 220 shown.

[0037] The following is in conjunction with the appendix Figure 4 The exemplary embodiments will be further described as follows: Figure 4 As shown, the object detection method may include the following steps S410 to S450:

[0038] Step S410: Receive the first echo signal of the first detection signal sent by the first base station to the object being detected.

[0039] In this context, a base station refers to an interface device through which a mobile device accesses the Internet. It can transmit information with the mobile device via a mobile communication switching center within a certain radio coverage area. The first base station can be an adjacent base station to the second base station, such as the base station closest to the second base station in a straight line. Alternatively, the first base station can be any base station near the second base station, such as a base station with a preset direction and distance from the second base station. The first echo signal refers to the signal received after reflection following the first base station sending a first detection signal to the detected object. In this exemplary embodiment, multiple antennas can be configured on the base station for signal transmission and reception. For example, the first base station can send the first detection signal to the detected object through multiple antennas, and the second base station can receive the first echo signal through an idle antenna among the configured multiple antennas.

[0040] Step S420: Analyze the first echo signal to determine the communication sensing information.

[0041] The communication sensing information can be the information carried in the first echo signal, such as sensing information or an information matrix. After receiving the first echo signal, the second base station can analyze the first echo signal by stripping the communication information from each symbol of the first echo signal to determine the communication sensing information, including the information matrix. The phase of different timing symbols and subcarrier symbols in the sensing symbols of the first echo signal can retain information such as the target distance and radial velocity of the detected object. Through further processing of the communication sensing information, the detection of the detected object can be achieved.

[0042] Step S430: Eliminate the offset information in the communication sensing information and determine the intermediate data.

[0043] Considering the potential information differences between different base stations—for example, when sensing a detected object, even assuming perfect clock synchronization between base stations, a certain clock deviation will still exist, and even a small clock offset can significantly reduce the positioning performance of the detected object—this exemplary embodiment, after determining the communication sensing information, can eliminate the offset information to determine the intermediate data after eliminating the offset information. The offset information may include clock offset information or frequency offset information, etc.

[0044] Step S440: Perform feature decomposition based on intermediate data to determine the signal transmission attitude parameters for sending the second detection signal to the detected object.

[0045] In this embodiment, the second detection signal refers to the detection signal sent by the second base station to the detected object when actively sensing and detecting the object. This exemplary embodiment can determine the signal transmission attitude parameters when sending the second detection signal to the detected object by feature decomposition of intermediate data. These signal transmission attitude parameters refer to the index parameters of how the second detection signal is transmitted, such as the angle of arrival parameter. Furthermore, when performing feature decomposition on the intermediate data, data extraction can be performed first. For example, components related to symbols and subcarriers can be extracted from the intermediate data. Then, feature decomposition is performed on these components to determine the signal transmission attitude parameters.

[0046] In an exemplary embodiment, there are multiple objects to be detected, and each object receives a corresponding first echo signal after the first base station sends a first detection signal to it; step S410 may include:

[0047] The system receives the first echo signal of the first detection signal sent by the first base station to multiple objects under test through multiple antennas.

[0048] This exemplary embodiment can be applied to scenarios where multiple objects are detected, such as... Figure 5As shown, when there are multiple drones that need to be located, the first base station 510 can send a first detection signal to each drone a, b, c. The second base station 520 can receive the first echo signal reflected by each first detection signal after it reaches drones a, b, c through multiple antennas, and process it.

[0049] like Figure 6 As shown, step S430 above may include the following steps:

[0050] Step S610: Based on the communication sensing information, transform each first echo signal to the frequency domain and determine the spectral data of each first echo signal in the frequency domain.

[0051] Step S620: Perform cross-correlation calculation on the spectrum data of multiple antennas of the second base station to eliminate offset information in the communication sensing information in order to determine intermediate data;

[0052] The intermediate data includes the first component and the second component.

[0053] This exemplary embodiment can receive a first echo signal through multiple antennas, transform the first echo signal to the frequency domain, and determine the spectral data of each antenna in the frequency domain, i.e., the spectral data of the first echo signal received by each antenna in the frequency domain. Further, through operations between the spectral data of multiple antennas, cross-correlation operations are performed on the multiple antennas to eliminate offset information in the communication sensing information and determine intermediate data. The intermediate data includes a first component and a second component, wherein the first component is a static component and the second component is a dynamic component.

[0054] In an exemplary embodiment, step S610 may include:

[0055] Construct the orthogonal frequency division multiplexed signal waveform of the first detection signal;

[0056] The modulation symbol of the first detection signal is determined based on the waveform of the orthogonal frequency division multiplexing signal;

[0057] Based on the communication sensing information, a Fourier transform is performed on the first echo signal, and the spectral data of each first echo signal in the frequency domain is determined according to the modulation symbol.

[0058] This exemplary embodiment can first construct the OFDM (Orthogonal Frequency Division Multiplexing) signal waveform of the object being detected based on the first detection signal sent by the first base station to the object being detected, and determine the modulation symbol of the first detection signal.

[0059] Specifically, in the OFDM signal waveform that constructs the first probe signal, the m-th preamble symbol at time t can be represented as:

[0060]

[0061] Where x[m, g] represents the modulation symbol transmitted on the g-th subcarrier of the m-th preamble symbol. Indicates a length of T+T C A rectangular window, where G is the number of subcarriers and the subcarrier spacing is... T represents the length of the OFDM symbol. An OFDM symbol is a frequency domain sequence composed of points and energies with different components; it is the basic unit for transmitting information on subcarriers. Due to multipath delay, OFDM symbols may experience inter-symbol interference upon arrival at the receiver. Furthermore, different subcarriers arriving at the receiver may not maintain absolute orthogonality, resulting in inter-carrier interference. Therefore, in this exemplary embodiment, each OFDM symbol can have a period of T. C The CP (Cyclic Prefix) is a prefix that copies a segment from the end of each OFDM symbol to the beginning of the symbol to reduce inter-symbol interference.

[0062] Performing a Fourier transform on the first echo signal allows its communication sensing information to be transformed into the frequency domain, determining the spectral data of the first echo signal in the frequency domain. When multiple first echo signals exist, multiple spectral data can be determined accordingly. The determination of the spectral data can include x[m, g]. Specifically, when the second base station receives the first echo signals reflected from L detected objects between itself and the first base station, such as NLOS (Non-Line of Sight) path signals, it transforms them into the frequency domain. The spectral data expression of the first echo signal received through the nth antenna is as follows:

[0063]

[0064]

[0065] The above equation is the frequency domain expression obtained by removing the cyclic prefix from the time-domain signal of the received first echo signal and then performing a G-point Fast Fourier Transform on the first echo signal. The second base station can use a uniform linear array (ULA) of N antennas to receive the preamble. α l f D，l τ l and θ lLet represent the channel gain, Doppler frequency, propagation delay, and AoA (Angle-of-Arrival) of the l-th echo signal path (e.g., the first echo signal reflected from the l-th detected object). Since there is usually no clock-level synchronization between base stations, the received signal also exhibits unknown time-varying characteristics, denoted as δ. τ (m). Due to the asynchronous carrier frequencies, the received signal also has an unknown frequency offset, denoted as δ. f (m). Where y n [m, g] represents the received frequency domain signal on the g-th subcarrier at the n-th receiving antenna of the m-th OFDM preamble symbol, Z. n [m, g] has zero mean and variance σ. 2 Additive white Gaussian noise. d is the antenna spacing, λ is the wavelength, and θ is the antenna spacing. l Let AoA be the l-th object being detected. Consider |x[m, g]| 2 The actual value has little impact on subsequent operations, and in this exemplary embodiment, it can be assumed to be |x[m, g]|. 2 =1.

[0066] In an exemplary embodiment, step S620 described above may include:

[0067] Multiply the spectrum data of any antenna in the second base station (excluding the reference antenna) with the spectrum data of the reference antenna to determine the intermediate data;

[0068] Intermediate data does not include clock offset information and subcarrier frequency offset information.

[0069] In this exemplary embodiment, the second base station may include n+1 antennas, from the 0th antenna to the nth antenna, for receiving the first echo signal. The reference antenna may be one of a plurality of antennas used to receive the first echo signal; it may be a random antenna or a designated antenna, such as the 0th antenna. Cross-correlation processing is performed between any antenna other than the reference antenna and the reference antenna. For example, cross-correlation processing can be performed between the 1st antenna and the 0th antenna, the 2nd antenna and the 0th antenna, or the 3rd antenna and the 0th antenna, etc., thereby eliminating offset information in the communication sensing information and determining intermediate data. It is possible that all antennas other than the reference antenna are cross-correlated with the reference antenna individually, or that some of the antennas other than the reference antenna are cross-correlated with the reference antenna individually; this disclosure does not specifically limit this approach.

[0070] Taking the cross-correlation processing of the nth antenna and the 0th antenna as an example, the explanation is as follows: the nth antenna can be any antenna. By performing a dot product operation between the spectrum data of the nth antenna and the spectrum data of the 0th antenna, the intermediate data ρ can be determined. n (m, g), the expression is as follows:

[0071]

[0072] Among them, f l，x =f D，l -f D，x , τ l，x =τ l -τ x Based on the cross-correlation calculation of the antennas described above, the second component... Clock offset information δ in the phase portion τ (m), and subcarrier frequency offset information δ f (m) were all eliminated.

[0073] In an exemplary embodiment, after eliminating offset information in the communication-aware information to determine intermediate data, the target detection method described above may further include:

[0074] The intermediate data is filtered using a filter to extract the second component;

[0075] Step S440 above may include:

[0076] The second component is subjected to feature decomposition to determine the signal transmission attitude parameters for sending the second detection signal to each detected object.

[0077] Considering the second component in the intermediate data It is a dynamic component related to m and g, and its 2D-FFT also has a pulse shape, while the first component... Since it is independent of m and g, this exemplary embodiment can extract the dynamic second component using a second-order filter with respect to m and g. Subsequent signal processing is then performed. Furthermore, the signal transmission attitude parameters, such as the angle of arrival parameter, for sending the second probe signal to the detected object can be estimated using eigenvalue decomposition.

[0078] Figure 7 A sub-flowchart of an object detection method in this exemplary embodiment is shown, which may specifically include the following steps:

[0079] Step S710: The first base station transmits OFDM signal waveforms to multiple detected objects;

[0080] Step S720: The second base station receives the first echo signal reflected by multiple detected objects between itself and the first base station;

[0081] Step S730: Perform cross-correlation calculation on the spectrum data of the nth antenna and the reference antenna in the second base station to determine intermediate data, so as to eliminate the influence of clock offset information and frequency offset information in the communication sensing information on the phase.

[0082] Step S740: Filter the intermediate data using a second-order filter;

[0083] Step S750: Filter out the first component, which is a static component;

[0084] Step S760: Extract the second component, which is a dynamic component;

[0085] Step S770: Perform subsequent signal processing based on the second component.

[0086] In an exemplary embodiment, the signal transmission attitude parameters include the angle of arrival parameter; therefore, the above-mentioned feature decomposition of the second component to determine the signal transmission attitude parameters for transmitting the second detection signal to each detected object may include:

[0087] Obtain the directional response vector, coefficient matrix, and array noise;

[0088] Construct the target signal matrix based on the second component, the direction response vector, the coefficient matrix, and the array noise;

[0089] Construct a spatial spectrum based on the target signal matrix;

[0090] By solving the spatial spectrum, the angle of arrival parameters for sending the second detection signal to each detected object are determined.

[0091] This exemplary embodiment can construct the target signal matrix P based on the second component, the direction response vector, the coefficient matrix, and the array noise, which can be specifically expressed by the following formula:

[0092] P = AS + N (4)

[0093] Where P is the output of the array element, A is the directional response vector, N represents the array noise, S is the coefficient matrix, and P is determined by the second component of the first echo signal received by different antennas.

[0094] Specifically, the array element output P, ​​coefficient matrix S, array noise N, and directional response vector A are determined by the following formulas:

[0095]

[0096] S = [S0, S1, ..., S...] L-1 ] T (6)

[0097] N = [n0(t), n1(t), ..., n N-1 (t)] T (7)

[0098] in,

[0099]

[0100]

[0101]

[0102] In an exemplary embodiment, constructing the spatial spectrum based on the target signal matrix may include:

[0103] The covariance matrix of the target signal matrix is ​​decomposed into eigenvalues ​​to obtain the eigenvectors of the noise space.

[0104] Construct a noise matrix based on the eigenvectors of the noise space;

[0105] Construct the spatial spectrum based on the noise matrix.

[0106] This exemplary embodiment can obtain the eigenvectors of the noise space by decomposing the eigenvalues ​​of the covariance matrix in the target signal matrix P, and then construct the resulting noise matrix. Specifically, the covariance matrix R of the target signal matrix P is obtained according to the covariance formula. p It can be represented as:

[0107] R p =E(PP) H ) = AR S A H +R N (12)

[0108] By utilizing the property that signal and noise are independent, the covariance matrix R can be... p It is divided into two parts: the signal subspace part and the AR part. S A H and noise subspace part R N =σ 2 I.

[0109] The obtained covariance matrix R p Eigenvalue decomposition can include calculating the rank and eigenvalues ​​of the output matrix, constructing the eigenvectors and diagonal matrix of the covariance matrix from the eigenvalues, which can be represented as:

[0110] R P =U S ∑ s U S H+U N ∑ N U N H (13)

[0111] Among them, R p There are N eigenvalues ​​{λ1, λ2, ..., λ3} N} and the corresponding feature vectors {v1, v2, ..., v N}, sorted by the magnitude of the eigenvalues. Noise energy is much smaller than signal energy; therefore, the L largest eigenvalues ​​{λ1, λ2, ..., λ} are... L For L signals, the remaining NL smallest eigenvalues ​​{λ} L+1 , λ L+2 、...,λ N} Corresponding noise.

[0112] Among them, R S It is the signal correlation matrix, R N It is a noise-correlated array, and R N =σ 2 I, σ 2 It is the noise power, I is the N×N identity matrix, and λ L+1 =λ L+2 =...=λ N =σ 2 ≈0.

[0113] Furthermore, the noise matrix U can be constructed using the noise eigenvectors obtained from eigenvalue decomposition. n The noise matrix can be used to construct a spatial spectrum. Constructing the noise matrix may involve treating the NL noise eigenvalues ​​and noise eigenvectors obtained from the eigenvalue decomposition in the previous step as the noise partial space, and constructing the noise matrix U. n The noise space and the signal space satisfy the orthogonality condition:

[0114] U n =[v L v L+1 , ..., v N-l (14)

[0115] Among them, A H v i =0, i=L+1, L+2,...,N.

[0116] In this exemplary embodiment, after the spatial spectrum is constructed, the orthogonality between the signal space and the noise space can be used to solve for the angle of arrival θ of the signal. When there are l objects to be detected, multiple angles of arrival can be solved accordingly, denoted as θ. l .

[0117] The spatial spectrum can be constructed using the following formula:

[0118]

[0119] In the above formula, the denominator is the inner product of the signal vector and the noise matrix, when a(θ) and U n When all columns are orthogonal, the denominator is zero. However, due to the presence of noise, the noise spectrum P(θ) will exhibit sharp peaks. The θ corresponding to these peaks is an estimate of the signal's direction of arrival. By varying θ according to this equation and searching for the peaks of the spatial spectral function, the angle of arrival θ of each propagation path of the signal can be estimated. l .

[0120] Figure 8 A sub-flowchart of another object detection method in this exemplary embodiment is shown, which may specifically include the following steps:

[0121] In step S810, the second base station determines intermediate data for eliminating clock offset information and subcarrier frequency offset information through joint cross-correlation calculation of multiple antennas;

[0122] Step S820: Filter the intermediate data to determine the dynamic component, i.e., the second component;

[0123] Step S830: Construct the target signal matrix based on the dynamic components;

[0124] Step S840: Perform eigenvalue decomposition on the covariance matrix of the target signal matrix to obtain the eigenvectors of the noise space;

[0125] Step S850: Construct a noise matrix using the feature vectors of the noise space;

[0126] Step S860: Construct a spatial spectrum based on the noise matrix, and use the orthogonality between the signal space and the noise space to solve for the arrival angle parameters of the second detection signal, such as the direction of arrival angle.

[0127] Step S450: Send a second detection signal to the object to be detected according to the signal transmission attitude parameters, and receive the second echo signal of the second detection signal, so as to determine the object detection result of the object to be detected based on the second echo signal.

[0128] This step is the process by which the second base station actively senses the object being detected. After determining the transmission attitude parameters, the second base station can send a second detection signal to the object being detected based on these parameters to sense the object. When the second detection signal comes into contact with the object being detected, it can reflect a second echo signal. The second base station analyzes the received second echo signal, for example, by transforming it to the frequency domain. By analyzing the spectrum data, the object detection result is determined. This object detection result can include information such as the distance and flight speed of the object being detected, thereby enabling accurate positioning of the monitored object.

[0129] Based on the above description, in this exemplary embodiment, the method involves receiving a first echo signal of a first detection signal sent by a first base station to a detected object; parsing the first echo signal to determine communication sensing information; eliminating offset information in the communication sensing information to determine intermediate data; performing feature decomposition based on the intermediate data to determine signal transmission attitude parameters for sending a second detection signal to the detected object; sending a second detection signal to the detected object according to the signal transmission attitude parameters; and receiving a second echo signal of the second detection signal to determine the object detection result of the detected object based on the second echo signal. On one hand, this exemplary embodiment proposes a method for object detection through multi-base station active-passive collaboration. It processes the first echo signal of the first detection signal sent by the first base station to determine the signal transmission attitude parameters, and then actively sends a second detection signal to the detected object. The detection of the detected object is achieved based on the second echo signal. Even when there are obstacles between base stations and no line-of-sight signal, the object detection process can still be executed accurately and effectively, making it widely applicable. On the other hand, this exemplary embodiment avoids the problem of object detection accuracy being affected by asynchronous information between base stations by removing offset information, further ensuring the accuracy of object detection.

[0130] Figure 9 The diagram illustrates an interactive flowchart of an object detection method in this exemplary embodiment, which may specifically include the following steps:

[0131] The first base station 910 executes step S911, sending a first detection signal to the object being detected;

[0132] The second base station 920 executes step S921 to receive the first echo signal of the first detection signal reflected by the detected object;

[0133] Step S922: Extract communication sensing information from the first echo signal;

[0134] Step S923: Perform cross-correlation calculation on the spectrum data corresponding to multiple antennas to determine intermediate data in order to eliminate clock offset information and subcarrier frequency offset information in the communication sensing information.

[0135] Step S924: Perform feature decomposition on the intermediate data to estimate the direction of arrival angle to the detected object;

[0136] Step S925: Transmit a second detection signal along the direction of the angle of arrival and receive the second echo signal transmitted by the second detection signal;

[0137] Step S926: Extract distance and velocity information from the second echo signal to estimate the detected object.

[0138] Steps S923 to S926 are processes of multi-base station collaborative active and passive sensing of the detected object, wherein steps S923 and S924 are passive sensing processes of dual base stations, and steps S925 and S926 are active sensing processes.

[0139] by Figure 5 Taking the object detection scenario shown as an example, in an urban scene, there is no line-of-sight component (LAS) between the two integrated sensing base stations 510 and 520, i.e., no line-of-sight signal. There are three target aircraft, a, b, and c, with propagation delays of 0.2 μs, 0.3 μs, and 0.1 μs relative to the integrated sensing base station 520, corresponding to distances of 60 meters, 90 meters, and 30 meters, respectively. The velocities of the three targets are 15 m / s, 20 m / s, and -5 m / s, corresponding to Doppler frequencies of 150 Hz, 200 Hz, and -50 Hz, respectively. The AoAs of the three targets are -30°, 10°, and 60°, respectively. All target aircraft are modeled as point sources, assuming a radar cross-section of 1. The carrier frequency is 3 GHz. The number of subcarriers is G = 256. The frequency bandwidth is 128 MHz, and the OFDM symbol period T is 2 μs. The CP length is D=50 to avoid inter-symbol interference (ISI), and the CP period TC is approximately 0.4μs. The approximate interval between the two data packets TA (transmitter address) is 1 millisecond. Sensing parameter estimation is performed using the preamble in the M=128 data packet. The base station employs a ULA with N=4 antenna elements. Assuming there are no LOS (Line of Sight) paths between the base stations and three target UAVs, the receiver (i.e., the second base station) can receive the first echo signal from L=3 NLOS paths.

[0140] In this exemplary embodiment, the first base station transmits a first detection signal, such as an OFDM signal s(t|m), to the UAV. When the energy of the first echo signal reflected back to the first base station is insufficient to support the target detection task, it indicates that the target is outside the active sensing range of the first base station. When the idle antenna port of the second integrated sensing base station, which is closer to the aircraft, receives the first echo signal of the downlink first detection signal from the first base station, the second base station acts as the receiver of the first echo signal, performing passive sensing by both base stations.

[0141] This exemplary embodiment allows for sensing parameter estimation using the preamble in the M=128 data packet. The receiving array antenna of the integrated sensing and communication second base station extracts channel information including time delay and Doppler frequency shift after receiving the signal. After removing the CP from the received time-domain signal, the second base station transforms the signal to the frequency domain using a G-point Fast Fourier Transform, and determines the spectrum data using formula (2), where L=3, f D，0 =150HZ, f D，1 =200HZ, f D，2 =-50HZ, τ0=0.2μs, τ1=0.3μs, τ2=0.1μs, δ τ (m) and δ f (m) is due to random clock offset and subcarrier frequency offset introduced by clock asynchrony.

[0142] In the second base station, the intermediate data ρ is determined by cross-correlation of the spectrum data of the nth antenna and the 0th antenna. n (m, g), clock offset δ after antenna cross-correlation operation τ (m) and subcarrier frequency offset δ f (m) are all eliminated. Components are extracted using a second-order filter with respect to m and g.

[0143] Furthermore, by constructing a target signal matrix P and defining a spatial spectrum P(θ), the angle of arrival parameters for transmitting the second detection signal to the three target spacecraft are determined. When defining the spatial spectrum P(θ), the angle of arrival is estimated by varying θ and searching for peaks. Figure 10 A schematic diagram of a spatial spectrum in this exemplary embodiment is shown, showing peaks when θ is -30°, 10°, and 60°, respectively. Therefore, the estimated AOA of the three targets is -30°, 10°, and 60°, which is consistent with the actual launch angle.

[0144] After obtaining the angle of arrival parameters, the second base station can actively sense the three target aircraft by sending second detection signals in their respective directions, thus obtaining three second echo signals. The general expression is as follows:

[0145]

[0146] Since the second base station transmits and receives signals independently during active sensing, there is no clock skew. By performing FFT (Fast Fourier Transform) and IFFT (Inverse Fast Fourier Transform) on the active sensing second echo signal, a two-dimensional range-velocity radar image of the target aircraft can be obtained, such as... Figure 11 As shown, the distance and speed information of the target aircraft are further extracted.

[0147] As shown in the two-dimensional range-velocity radar chart, the distances and velocities of the three target aircraft detected through this exemplary embodiment are r1 = 60.3947 m and v1 = 15.0189 m / s; r2 = 90.3947 m and v2 = 20.0252 m / s; and r3 = 30 m and v3 = -5.0063 m / s, respectively. The actual target parameters are R1 = 60 m and V1 = 15 m / s, R2 = 90 m and V2 = 20 m / s, and R3 = 30 m and V3 = -5 m / s. The ranging error is ±0.2631 m and the velocity error is ±0.0168 m / s, which are close to the true values ​​of the perceived targets and the errors are acceptable.

[0148] An exemplary embodiment of this disclosure also provides an object detection apparatus. (Refer to...) Figure 12 The device 1200 may include: a signal receiving module 1210 for receiving a first echo signal of a first detection signal sent by a first base station to a detected object; an information determination module 1220 for parsing the first echo signal to determine communication sensing information; an information cancellation module 1230 for canceling offset information in the communication sensing information to determine intermediate data; a parameter determination module 1240 for performing feature decomposition based on the intermediate data to determine signal transmission attitude parameters for sending a second detection signal to the detected object; and an object detection module 1250 for sending a second detection signal to the detected object according to the signal transmission attitude parameters and receiving a second echo signal of the second detection signal to determine the object detection result of the detected object based on the second echo signal.

[0149] In an exemplary embodiment, there are multiple objects to be detected, and each object receives a first echo signal after the first base station sends a first detection signal to it. A signal receiving module is used to receive the first echo signals of the first detection signals sent by the first base station to the multiple objects through multiple antennas. An information cancellation module includes: a signal transformation unit, used to transform each first echo signal to the frequency domain based on communication sensing information, and determine the spectral data of each first echo signal in the frequency domain; and a cross-correlation operation unit, used to perform cross-correlation operations on the spectral data of the multiple antennas of the second base station to eliminate offset information in the communication sensing information, thereby determining intermediate data; wherein the intermediate data includes a first component and a second component.

[0150] In one exemplary embodiment of this disclosure, the signal transformation unit includes: a waveform construction subunit, configured to construct an orthogonal frequency division multiplexing (OFDM) signal waveform of a first detection signal; determine the modulation symbol of the first detection signal based on the OFDM signal waveform; perform a Fourier transform on the first echo signal based on communication sensing information; and determine the spectral data of each first echo signal in the frequency domain based on the modulation symbol.

[0151] In one exemplary embodiment of this disclosure, the cross-correlation operation unit includes: a dot product operation subunit, used to perform a dot product of the spectrum data of any antenna in the second base station other than the reference antenna and the spectrum data of the reference antenna to determine intermediate data; the intermediate data does not contain clock offset information and subcarrier frequency offset information.

[0152] In one exemplary embodiment of this disclosure, the apparatus further includes: a filtering unit, configured to eliminate offset information in the communication sensing information, and after determining intermediate data, to filter the intermediate data through a filter to extract a second component; and a parameter determination module, comprising: a parameter determination unit, configured to perform feature decomposition on the second component to determine signal transmission attitude parameters for sending the second detection signal to each detected object.

[0153] In an exemplary embodiment of this disclosure, the signal transmission attitude parameters include angle of arrival parameters; the parameter determination unit includes: a data acquisition unit for acquiring a direction response vector, a coefficient matrix, and array noise; a signal matrix construction unit for constructing a target signal matrix based on the second component, the direction response vector, the coefficient matrix, and the array noise; a spatial spectrum construction unit for constructing a spatial spectrum based on the target signal matrix; and a spatial spectrum solving unit for determining the angle of arrival parameters for transmitting the second detection signal to each detected object by solving the spatial spectrum.

[0154] In one exemplary embodiment of this disclosure, the spatial spectrum construction unit includes: an eigenvalue decomposition subunit for performing eigenvalue decomposition on the covariance matrix of the target signal matrix to obtain eigenvectors of the noise space; a noise matrix construction subunit for constructing a noise matrix based on the eigenvectors of the noise space; and a spatial spectrum construction subunit for constructing a spatial spectrum based on the noise matrix.

[0155] The specific details of each module / unit in the above-mentioned device have been described in detail in the embodiments of the method section. For any undisclosed details, please refer to the embodiments of the method section, and therefore will not be repeated here.

[0156] An exemplary embodiment of this disclosure also provides an electronic device capable of implementing the above-described method.

[0157] Those skilled in the art will understand that various aspects of this disclosure can be implemented as a system, method, or program product. Therefore, various aspects of this disclosure can be specifically implemented in the following forms: a completely hardware implementation, a completely software implementation (including firmware, microcode, etc.), or a combination of hardware and software aspects, collectively referred to herein as a "circuit," "module," or "system."

[0158] The following reference Figure 13 To describe an electronic device 1300 according to such an exemplary embodiment of the present disclosure. Figure 13 The electronic device 1300 shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments disclosed herein.

[0159] like Figure 13 As shown, the electronic device 1300 is manifested in the form of a general-purpose computing device. The components of the electronic device 1300 may include, but are not limited to: at least one processing unit 1310, at least one storage unit 1320, a bus 1330 connecting different system components (including storage unit 1320 and processing unit 1310), and a display unit 1340.

[0160] The storage unit stores program code, which can be executed by the processing unit 1310 to perform the steps described in the "Exemplary Methods" section of this specification according to various exemplary embodiments of this disclosure. For example, the processing unit 1310 can execute... Figure 4 , Figure 6 , Figure 7 , Figure 8 or Figure 9 The steps shown are as follows.

[0161] Storage unit 1320 may include readable media in the form of volatile storage units, such as random access memory (RAM) 1321 and / or cache memory 1322, and may further include read-only memory (ROM) 1323.

[0162] Storage unit 1320 may also include a program / utility 1324 having a set (at least one) program module 1325, such program module 1325 including but not limited to: operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0163] Bus 1330 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0164] Electronic device 1300 can also communicate with one or more external devices 1400 (e.g., keyboard, pointing device, Bluetooth device, etc.), one or more devices that enable a user to interact with electronic device 1300, and / or any device that enables electronic device 1300 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 1350. Furthermore, electronic device 1300 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 1360. As shown, network adapter 1360 communicates with other modules of electronic device 1300 via bus 1330. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 1300, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0165] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the method according to the exemplary embodiments of this disclosure.

[0166] Exemplary embodiments of this disclosure also provide a computer-readable storage medium having a program product stored thereon capable of implementing the methods described above in this specification. In some possible implementations, various aspects of this disclosure may also be implemented as a program product including program code that, when the program product is run on a terminal device, causes the terminal device to perform the steps described in the "Exemplary Methods" section of this specification according to various exemplary embodiments of this disclosure.

[0167] Exemplary embodiments of this disclosure also provide a program product for implementing the above-described method, which may employ a portable compact disc read-only memory (CD-ROM) and include program code, and may run on a terminal device, such as a personal computer. However, the program product of this disclosure is not limited thereto. In this document, a readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0168] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0169] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting programs for use by or in conjunction with an instruction execution system, apparatus, or device.

[0170] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0171] Program code for performing the operations of this disclosure can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing devices can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0172] Furthermore, the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of this disclosure and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0173] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to exemplary embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0174] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

[0175] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is defined only by the appended claims.

Claims

1. An object detection method, characterized in that, Applied to a second base station, the method includes: The system receives first echo signals of first detection signals sent by a first base station to multiple objects under detection via multiple antennas; the objects under detection are multiple, and each object under detection receives a corresponding first echo signal after the first base station sends a first detection signal to each of the objects under detection. Analyze the first echo signal to determine the communication sensing information; Based on the communication sensing information, each of the first echo signals is transformed to the frequency domain to determine the spectral data of each of the first echo signals in the frequency domain; cross-correlation operation is performed on the spectral data of multiple antennas of the second base station to eliminate the offset information in the communication sensing information to determine intermediate data; wherein, the intermediate data includes a first component and a second component; The intermediate data is filtered using a filter to extract the second component; The second component is decomposed to determine the signal transmission attitude parameters for sending the second detection signal to each of the detected objects; The second detection signal is sent to the object to be detected according to the attitude parameters of the signal, and the second echo signal of the second detection signal is received, so as to determine the object detection result of the object to be detected based on the second echo signal.

2. The method according to claim 1, characterized in that, The step of transforming each of the first echo signals to the frequency domain based on the communication sensing information and determining the spectral data of each of the first echo signals in the frequency domain includes: Construct the orthogonal frequency division multiplexing signal waveform of the first detection signal; The modulation symbol of the first detection signal is determined based on the waveform of the orthogonal frequency division multiplexing signal; Based on the communication sensing information, a Fourier transform is performed on the first echo signal, and the frequency spectrum data of each first echo signal in the frequency domain is determined according to the modulation symbol.

3. The method according to claim 1, characterized in that, The step of performing cross-correlation calculations on the spectrum data of multiple antennas of the second base station to eliminate offset information in the communication sensing information in order to determine the intermediate data includes: The intermediate data is determined by multiplying the spectrum data of any antenna in the second base station (excluding the reference antenna) with the spectrum data of the reference antenna. The intermediate data does not include clock offset information and subcarrier frequency offset information.

4. The method according to claim 1, characterized in that, The signal transmission attitude parameters include the angle of arrival parameter; the step of performing feature decomposition on the second component to determine the signal transmission attitude parameters for sending the second detection signal to each of the detected objects includes: Obtain the directional response vector, coefficient matrix, and array noise; Construct the target signal matrix based on the second component, the direction response vector, the coefficient matrix, and the array noise; Construct a spatial spectrum based on the target signal matrix; By solving the spatial spectrum, the angle of arrival parameters for sending the second detection signal to each of the detected objects are determined.

5. The method according to claim 4, characterized in that, The step of constructing a spatial spectrum based on the target signal matrix includes: The covariance matrix of the target signal matrix is ​​decomposed into eigenvalues ​​to obtain the eigenvectors of the noise space; Construct a noise matrix based on the feature vectors of the noise space; Based on the noise matrix, construct the spatial spectrum.

6. An object detection device, characterized in that, The device, applied to a second base station, includes: The signal receiving module is used to receive, through multiple antennas, the first echo signal of the first detection signal sent by the first base station to multiple objects to be detected; the objects to be detected are multiple, and each object to which the first base station sends the first detection signal will receive a corresponding first echo signal. The information determination module is used to analyze the first echo signal and determine the communication sensing information; The information cancellation module is used to transform each of the first echo signals to the frequency domain based on the communication sensing information, and determine the spectral data of each of the first echo signals in the frequency domain; perform cross-correlation operation on the spectral data of multiple antennas of the second base station to eliminate the offset information in the communication sensing information, so as to determine intermediate data; wherein, the intermediate data includes a first component and a second component; and perform filtering processing on the intermediate data through a filter to extract the second component; The parameter determination module is used to perform feature decomposition on the second component and determine the signal transmission attitude parameters for sending the second detection signal to each of the detected objects. The object detection module is used to send the second detection signal to the object to be detected according to the attitude parameters sent by the signal, and to receive the second echo signal of the second detection signal, so as to determine the object detection result of the object to be detected according to the second echo signal.

7. An electronic device, characterized in that, include: processor; as well as Memory for storing the executable instructions of the processor; The processor is configured to execute the method of any one of claims 1-5 by executing the executable instructions.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method described in any one of claims 1-5.

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