Unmanned aerial vehicle detection and positioning method and system based on sensing integration

Abstract

The invention discloses an unmanned aerial vehicle detection and positioning method and system based on inductance integration, and relates to the technical field of electrical digital data processing, and the method comprises the steps: obtaining a transmitting linear array and a receiving linear array, and enabling the transmitting linear array to be provided with a plurality of antenna units; integrating the scanning beams, obtaining a plurality of echo signals, generating a plurality of distance data according to the plurality of echo signals, and forming a distance sequence; obtaining an absolute difference value between adjacent distance data in the distance sequence, obtaining a motion mutation rate, obtaining a correction parameter, carrying out increment on the first number based on the correction parameter and generating a second number, and carrying out reconstruction enhancement on the scanning beam based on a plurality of sensing beams of the second number of antenna units; and acquiring a real-time echo signal reflected by the target unmanned aerial vehicle at the current moment, acquiring a real-time distance of the target unmanned aerial vehicle according to the real-time echo signal, and generating a positioning report. The method has the advantages of self-adaptive correction, accurate detection and directional addition to avoid redundant energy consumption.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of digital data processing, in particular to a method and system for detecting and positioning unmanned aerial vehicles based on integrated sensing and communication. BACKGROUND

[0002] In the field of detecting and positioning unmanned aerial vehicles based on integrated sensing and communication, especially in the detection of unmanned aerial vehicles with integrated wireless communication and sensing functions, the existing methods have the problem of serious decline in detection accuracy caused by high-speed maneuvering of unmanned aerial vehicles.

[0003] The main performance is that the number of fixedly configured transmitting linear array antenna units and the static scanning beam strength cannot adapt to the rapid motion changes of the target unmanned aerial vehicle in real time. For example, when the unmanned aerial vehicle suddenly accelerates, makes a sharp turn or changes in altitude, etc., the distance between it and the communication base station will fluctuate dramatically in a short time, resulting in large absolute difference changes in the distance sequence generated based on the received linear array echo signals. At the same time, due to the inherent rigidity of beam strength and angle, the scanning beam cannot be dynamically enhanced within the preset time period to adapt to these rapid changes, and the echo signal is easily weakened or partially lost at the motion mutation point, resulting in distorted distance data and inaccurate motion trend analysis, which further affects the real-time positioning. Secondly, the existing technology lacks an effective online motion mutation evaluation mechanism, which cannot guide beam reconstruction according to the instantaneous fluctuation of the distance sequence (such as the proportion of absolute difference value exceeding the standard change distance). This non-adaptive adjustment makes it difficult to distinguish between real motion and noise interference in complex environments or multipath interference, and the cumulative deviation of the motion mutation rate amplifies the propagation delay estimation error of the real-time echo signal, especially in high dynamic scenarios. The beam synthesis of fixed antenna unit number cannot improve the capture ability of weak echo signals, the detection sensitivity is restricted, and the scanning strength cannot be dynamically optimized according to the mutation rate, resulting in position deviation and trajectory tracking interruption. SUMMARY

[0004] In view of the technical problems in the above background art, the present application provides a method and system for detecting and positioning unmanned aerial vehicles based on integrated sensing and communication.

[0005] The application discloses an unmanned aerial vehicle detection and positioning method based on a sense integration, and the method comprises the following steps: acquiring a transmitting linear array and a receiving linear array of a communication base station, wherein the transmitting linear array is configured with a plurality of antenna units, and the antenna units are configured to generate a sensing beam containing a plurality of subcarriers; a plurality of sensing beams based on a first number of antenna units are integrated into a scanning beam, a plurality of echo signals reflected by a target unmanned aerial vehicle at a plurality of detection time points in a preset time period before a current time are acquired based on the receiving linear array, a plurality of distance data are generated according to the plurality of echo signals, and the plurality of distance data are sequentially arranged in time sequence to form a distance sequence; an absolute difference value between each adjacent distance data in the distance sequence is acquired, a motion mutation rate is acquired according to all the absolute difference values in the distance sequence, a correction parameter is acquired according to the motion mutation rate, the first number is incremented based on the correction parameter to generate a second number, and a plurality of sensing beams based on the second number of antenna units are used to reconstruct and enhance the scanning beam; a real-time echo signal reflected by the target unmanned aerial vehicle at the current time is acquired based on the scanning beam after the reconstruction and enhancement, a real-time distance of the target unmanned aerial vehicle is acquired according to the real-time echo signal, and a positioning report is generated.

[0006] Optionally, acquiring the motion mutation rate according to all the absolute difference values in the distance sequence comprises: acquiring a standard change distance, acquiring a number of absolute difference values in the distance sequence that exceed the standard change distance and recording the number as a to-be-processed number; and dividing the to-be-processed number by a number of absolute difference values in the distance sequence to obtain the motion mutation rate.

[0007] Optionally, acquiring the correction parameter according to the motion mutation rate comprises: if the motion mutation rate exceeds a basic ratio, taking the motion mutation rate as the correction parameter; or if the motion mutation rate does not exceed the basic ratio, taking the basic ratio as the correction parameter.

[0008] Optionally, incrementing the first number based on the correction parameter to generate the second number comprises: multiplying one half of the first number by the correction parameter to obtain an increment ratio; and adding the increment ratio to one half of the first number to obtain the second number.

[0009] Optionally, reconstructing and enhancing the scanning beam based on the plurality of sensing beams of the second number of antenna units comprises: reconstructing the scanning beam under the first number according to the plurality of sensing beams of the second number of antenna units to form an enhanced scanning beam.

[0010] Optionally, acquiring the real-time distance of the target unmanned aerial vehicle according to the real-time echo signal and generating a positioning report comprises: analyzing a propagation delay of the real-time echo signal to determine a real-time distance between the target unmanned aerial vehicle and the communication base station, and generating a positioning report containing the real-time distance of the target unmanned aerial vehicle.

[0011] A drone detection and positioning system based on integrated sensing is also provided, comprising: a detection module for acquiring the transmitting and receiving linear arrays of a communication base station, wherein each transmitting linear array is configured with multiple antenna elements, and the antenna elements are configured to generate a sensing beam containing multiple subcarriers; and a data generation module for integrating the multiple sensing beams of the first number of antenna elements into a scanning beam, acquiring multiple echo signals reflected by the scanning beam from the target drone at multiple detection time points within a preset time period before the current time based on the receiving linear array, generating multiple distance data based on the multiple echo signals, and arranging the multiple distance data in chronological order. The distance sequence is formed by arranging the data in sequence. The correction and enhancement module is used to obtain the absolute difference between each adjacent distance data in the distance sequence, obtain the motion mutation rate based on all the absolute differences in the distance sequence, obtain the correction parameter based on the motion mutation rate, increment the first quantity based on the correction parameter and generate a second quantity, and reconstruct and enhance the scanning beam based on the multiple sensing beams of the second quantity of antenna elements. The positioning generation module is used to obtain the real-time echo signal reflected by the target UAV at the current moment based on the reconstructed and enhanced scanning beam, obtain the real-time distance of the target UAV based on the real-time echo signal and generate a positioning report.

[0012] Optionally, the correction and enhancement module is also used to: obtain the standard variation distance, obtain the number of absolute differences in the distance sequence that exceed the standard variation distance and record them as the number to be processed; divide the number to be processed by the number of absolute differences in the distance sequence and obtain the motion mutation rate.

[0013] Optionally, the correction enhancement module is also used to: if the motion mutation rate exceeds the baseline ratio, use the motion mutation rate as a correction parameter; if the motion mutation rate does not exceed the baseline ratio, use the baseline ratio as a correction parameter.

[0014] Optionally, the correction enhancement module is also used to: multiply half of the first quantity by the correction parameter to obtain the increment ratio; add half of the first quantity to the increment ratio to obtain the second quantity.

[0015] The beneficial effects of this invention are reflected in: In the entire sensor-integrated UAV detection and positioning method, firstly, by analyzing the distribution characteristics of the absolute difference between adjacent ranging values ​​in the historical distance sequence in real time, the motion mutation rate index of the target UAV is quantified. This index directly reflects the intensity of the UAV's maneuvering behavior. Furthermore, based on this mutation rate, the incremental parameter of the number of antenna elements is dynamically calculated, expanding the finite number of elements (first quantity) used in the initial transmission array to more elements (second quantity) to participate in coordinated transmission. Without changing the scanning area, the beam energy density, main lobe gain, and beam pointing accuracy are controllably improved by increasing the synthetic aperture resources. Further, This on-demand enhancement mechanism enables timely strengthening of the scanning beam intensity when a sudden target maneuver is detected (manifested as continuous large fluctuations in the range sequence). This improves the effective signal radiation intensity and echo signal-to-noise ratio in the target direction, helps reduce signal scattering loss and multipath interference during the rapid displacement of highly dynamic targets, and enhances the quality and integrity of real-time echo signals. Ultimately, the improved signal quality reduces ranging deviations caused by weak echoes or signal distortion in the real-time target range data obtained through propagation delay analysis, thereby improving the positioning reliability during the maneuver phase, providing more accurate position nodes for continuous trajectory tracking, and improving resource utilization. Attached Figure Description

[0016] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0017] Figure 1 This is a schematic diagram illustrating the steps of the UAV detection and positioning method based on integrated sensing according to the present invention; Figure 2 This is a schematic diagram of part of step S3 in the UAV detection and positioning method based on integrated sensing of the present invention; Figure 3 This is a schematic diagram of another part of step S3 in the UAV detection and positioning method based on integrated sensing of the present invention; Figure 4 This is a schematic diagram of another part of step S3 in the UAV detection and positioning method based on integrated sensing of the present invention; Figure 5 This is a schematic diagram of part of step S4 in the UAV detection and positioning method based on integrated sensing of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0019] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0020] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0021] like Figure 1 As shown, a method for UAV detection and localization based on integrated sensing is provided. In one embodiment, the method includes: S1. Obtain the transmitting linear array and receiving linear array of the communication base station, wherein each transmitting linear array is configured with multiple antenna elements, and the antenna elements are configured to generate a sensing beam containing multiple subcarriers. S2. Based on the first number of antenna elements, multiple sensing beams are integrated into a scanning beam. Based on the receiving linear array, multiple echo signals reflected by the target UAV at multiple detection time points within a preset time period before the current time are obtained from the scanning beam. Multiple distance data are generated based on the multiple echo signals, and the multiple distance data are arranged in chronological order to form a distance sequence. S3. Obtain the absolute difference between each adjacent distance data in the distance sequence, obtain the motion mutation rate based on all the absolute differences in the distance sequence, obtain the correction parameter based on the motion mutation rate, increment the first quantity based on the correction parameter and generate a second quantity, and reconstruct and enhance the scanning beam based on the multiple sensing beams of the antenna elements of the second quantity. S4. Based on the reconstructed and enhanced scanning beam, obtain the real-time echo signal reflected by the target UAV at the current moment, obtain the real-time distance of the target UAV based on the real-time echo signal, and generate a positioning report.

[0022] In this embodiment, it should be noted that in S1, the existing antenna array resources of the communication base station are acquired and configured. Specifically, this involves defining the linear array structure used by the base station transmitter and the linear array structure used by the receiver. The transmitter linear array is not a single transmitting point, but rather consists of a large number of antenna elements arranged linearly in space. The key configuration lies in activating these transmitter antenna elements and driving them to work together to generate a sensing beam. This sensing beam differs from conventional communication beams used only for data transmission. Its significant characteristic is that the energy and information carried within it are distributed across multiple independent subcarriers. These subcarriers are discrete, orthogonal, and densely arranged in the frequency domain, collectively constituting the spectral structure of the beam. This means that a single sensing beam itself contains rich frequency diversity characteristics.

[0023] Furthermore, this configuration enables the beam to simultaneously perform two functions: on the one hand, it utilizes its electromagnetic wave characteristics (especially the good orthogonality and resolution of each subcarrier) as a detection signal source, and when the beam is directed at the target UAV, the energy of its different frequency components will be scattered or reflected; on the other hand, these subcarriers themselves can carry data transmission, meeting the communication task requirements of the communication base station, thereby achieving deep integration and resource sharing of wireless communication function and environmental perception (in this case, UAV detection) function at the hardware and waveform levels, laying the physical and signal foundation for subsequent steps to complete the detection task using the beam.

[0024] Furthermore, the number of antenna elements in S1 directly determines the transmitter's flexible control capability in the airspace, providing hardware support for subsequent steps to form scanning beams with different coverage areas or resolutions. The sensing beam contains multiple subcarriers, utilizing technologies widely used in modern broadband communication to ensure that each subcarrier component propagates and carries information with minimal mutual interference. Reusing this existing communication waveform structure for sensing tasks is particularly beneficial for extracting target information by processing echo signals (such as in step S2), because the differences in frequency response and phase changes generated by different subcarriers after reflection are important clues for analyzing target distance and motion characteristics.

[0025] For example, in urban environments, base station antenna arrays using this configuration can, even when facing multiple possible reflection paths, leverage the fine resolution of multiple subcarrier signals to more effectively separate and identify the actual reflected signals from the target UAV at the receiving end, enhancing the target signal-to-noise ratio under complex multipath interference. Therefore, S1 completes a crucial step from acquiring basic hardware to generating specific sensing waveforms, forming an integrated sensing transmitter with both communication and detection capabilities.

[0026] In S2, only a pre-defined subset of antenna elements in the transmitting array—the initial number of antenna elements—is utilized. Instead of activating all antenna elements simultaneously for omnidirectional transmission, the multiple sensing beams generated by these initial antenna elements, each pointing in a specific direction, are spatially synthesized and their energy integrated to ultimately form a scanning beam with a specific coverage area and directionality. This integration process involves adjusting the phase and amplitude weights of each antenna element so that the final synthesized scanning beam can achieve detection within a certain range.

[0027] Subsequently, based on the receiving linear array, the detection results within a certain time window are collected. This preset time period is immediately preceding the current moment and covers multiple discrete detection time points. At each time point, the echo signal of the aforementioned scanning beam reflected back by the target UAV is captured by the receiving array. These echo signals carry information about signal changes caused by variations in the relative distance between the UAV and the base station and the UAV's reflection characteristics. By processing and analyzing the echo signals captured at each moment (primarily based on the physical characteristic of signal propagation time delay), the straight-line distance between the target UAV and the base station at each corresponding detection time point can be calculated.

[0028] Finally, these distance data acquired chronologically are arranged in an orderly manner to form a data sequence that evolves and changes in chronological order, namely, a distance sequence. This sequence faithfully records the dynamic historical trajectory of the drone's distance from the base station within a specific time period that has just passed.

[0029] Furthermore, forming the distance sequence is a key output of S2, providing the necessary and direct data foundation for subsequent steps to evaluate abrupt changes in the UAV's motion state. Each distance data point represents a measurement of the relative position of the UAV and the base station at a historical instant. When the UAV performs maneuvers such as sudden acceleration, sharp turns, or rapid altitude changes as described in S1, its position changes drastically between adjacent detection time points. This non-linear and rapid change in physical spatial position is directly reflected in the distance sequence, manifested as a large positive or negative variation in the difference between adjacent distance data points (the next point minus the previous point). The magnitude of the absolute value of this difference (i.e., the "absolute difference") essentially quantifies the drastic degree of distance change of the UAV between adjacent detection times.

[0030] Therefore, this distance sequence, based on actual detection, although not a direct measurement of the UAV's speed and acceleration, can effectively reveal the smoothness or abruptness of the UAV's trajectory by analyzing the changing patterns of the absolute differences between adjacent points in the sequence. For example, if the changes between most adjacent distance points in a distance sequence are gradual and regular, their absolute differences are small and tend to be consistent; however, if multiple large absolute differences appear consecutively within a certain period, this may correspond to the UAV performing maneuvers such as obstacle avoidance sharp turns, full-speed acceleration, or descent. The distance sequence established in this step is the raw input data for the subsequent S3 step of quantifying the UAV's motion abrupt change rate. By statistically processing the degree and frequency of these actual distance jumps in the sequence, it provides an objective basis for determining whether and how to dynamically enhance the scanning beam.

[0031] In S3, the intensity of the target UAV's maneuvers is assessed, and detection capabilities are adaptively enhanced accordingly to cope with high-speed movement. Specifically, for the distance sequence generated in S2, which records the continuous distance changes of the target UAV relative to the base station over a historical time period, S3 first analyzes the absolute value of the difference between the distance data corresponding to each two adjacent time points in the distance sequence (called the absolute difference). The magnitude of each absolute difference intuitively represents the amount of change in the UAV's distance from the base station between adjacent detection times, essentially quantifying the smoothness or abruptness of the UAV's trajectory in a short period of time—when the UAV performs highly maneuverable actions such as rapid acceleration or sharp turns, this absolute difference usually increases significantly.

[0032] Subsequently, a predefined standard change distance is introduced. This standard value is used to distinguish between normal, predictable distance changes and abnormally large changes that may be caused by violent motion. Next, S3 calculates the number of absolute differences in the distance sequence that exceed this standard change distance (i.e., the number to be processed), and divides this number by the total number of absolute differences in the entire distance sequence (i.e., the sequence length minus one) to obtain a ratio, which is the motion mutation rate. The magnitude of the motion mutation rate directly reflects the frequency or degree of unexpected and violent changes (i.e., mutations) in the UAV's motion state within the observation window. For example, if more than half of the adjacent points in the sequence have distance changes greater than the standard change distance, the mutation rate is high, suggesting that the UAV is performing intensive, non-stationary maneuvers.

[0033] Next, based on the calculated motion abrupt change rate, a correction parameter for adjusting beam resources is determined according to specific rules: if the abrupt change rate is greater than a preset baseline ratio, it indicates that the UAV's motion state is highly unstable and more resources need to be invested in detection enhancement; in this case, the larger abrupt change rate itself is directly used as the correction parameter. Conversely, if the abrupt change rate does not exceed the baseline ratio, it indicates that the current motion is relatively stable and no excessive enhancement is needed; in this case, the baseline ratio is used as the correction parameter. The generation of the correction parameter is the most critical control variable for subsequent adaptive adjustment of the detection beam intensity.

[0034] Furthermore, after obtaining the correction parameters, S3 begins to perform substantial adaptive adjustment, that is, dynamically increasing the number of antenna elements participating in the detection to enhance the energy and focusing capability of the scanning beam, solving the problem in the technical background that fixed antenna element configurations cannot respond to rapid motion changes. The adjustment strategy is not simply to change the initially set total number of antenna elements. The operation is to first divide the first number by two as a base, and then multiply this base by the correction parameters to obtain an increment ratio. Then, this increment ratio is added to the previous base to obtain a new second number of antenna elements.

[0035] Specifically, the base number represents the baseline level of resource investment; while the incremental ratio is dynamically scaled according to the assessed motion mutation rate (reflected by the correction parameter). When the motion mutation rate is high (the correction parameter is large), the incremental ratio increases accordingly, resulting in the second number being significantly larger than the first number. This means that more antenna elements that might have been dormant or performing other tasks will be activated and integrated to participate in the current detection task. When the motion mutation rate is low, the incremental ratio is also small, with the second number being close to 1.5 times the first number (because the base number is about half of the first number, plus the base ratio multiplied by the base number, the base ratio is usually less than 1), indicating that resource investment only increases slightly or remains at a reasonable level.

[0036] Finally, based on the newly determined second number, these antenna elements are driven to work together to generate their own sensing beams (each beam still contains multiple subcarriers), and these additional sensing beams are again integrated in a manner similar to step S2, but this time with the support of more resources.

[0037] Specifically, the scanning beam originally generated by the first number of antenna elements is recombined according to the increased number of antenna elements (the second number). This reconstruction does not change the coverage area or basic direction of the scanning beam, but rather improves the beamforming accuracy, focusing gain, and transmit energy density of the synthesized scanning beam by deploying more transmit elements. For example, when tracking a drone performing evasive maneuvers over a city, an assessment shows that a high mutation rate will trigger the deployment of more antenna elements. The recombined enhanced scanning beam can emit a more concentrated and narrower beam, effectively overcoming signal scattering loss and multipath interference enhancement caused by rapid target movement, improving the effective signal strength in the target direction, and providing a more powerful and adaptable signal guarantee for the upcoming real-time detection (S4 step), thus alleviating the problem of decreased detection sensitivity when the fixed beam configuration is at a maneuvering point.

[0038] In S4, the scanning beam dynamically enhanced by a second number of antenna elements based on S3 is used. This enhanced beam has adjusted physical characteristics compared to the initial beam synthesized by a first number of antenna elements used in S2: by incorporating more antenna elements for synthesis, the enhanced beam possesses superior beamforming capabilities, such as higher energy concentration, narrower main lobe width, or higher sidelobe suppression in the desired detection direction. At this moment, this enhanced scanning beam is projected towards the airspace where the target UAV is located. When this beam illuminates the target UAV, the electromagnetic wave energy it carries (containing multiple subcarrier components) is scattered or reflected by the target surface. The receiving linear array of the communication base station then focuses on capturing the real-time echo signal reflected back from the target UAV, belonging to this specific enhanced beam. Thanks to the enhanced transmit energy density and target-direction focusing characteristics of the enhanced beam, the real-time echo signal reflected back at the critical moment when the UAV may be performing maneuvers has a higher intensity and signal-to-noise ratio than when using the initial weak beam, which is more conducive to the effective acquisition and processing by the receiver. This reduces the risk of the signal being weakened, submerged in noise, or partially lost in highly maneuverable or complex environments.

[0039] Furthermore, upon receiving the real-time echo signal, time delay analysis is immediately performed. Utilizing the physical law of the constant speed of electromagnetic wave propagation, the total propagation time (i.e., round-trip time) required for the signal to travel from the base station, be reflected by the drone, and return to the base station is measured. This propagation time directly corresponds to the total distance the electromagnetic wave travels between the base station and the drone. Dividing this total distance by 2 yields the straight-line distance between the target drone and the communication base station at the current detection moment.

[0040] Finally, the calculated straight-line distance at this current moment is organized into a positioning report. The core content of this report is the real-time distance information of the target UAV relative to the base station. This report provides timely updates on the UAV's position parameters after a possible maneuvering phase, providing crucial instantaneous positional information for applications such as trajectory tracking or collision avoidance. Through adaptive beam augmentation in S3, step S4 ensures that even during target maneuvering, the measurement of this real-time distance value is closer to the true value due to the potential improvement in echo signal quality, which helps mitigate the position estimation bias caused by signal weakening.

[0041] In summary, in the entire sensor-integrated UAV detection and positioning method, by analyzing the distribution characteristics of the absolute difference between adjacent ranging values ​​in the historical distance sequence in real time, the motion mutation rate index of the target UAV is quantified. This index directly reflects the intensity of the UAV's maneuvering behavior. Furthermore, based on this mutation rate, the incremental parameter of the number of antenna elements is dynamically calculated, expanding the finite number of elements (first quantity) used in the initial transmission array to more elements (second quantity) to participate in coordinated transmission. Without changing the scanning area, the beam energy density, main lobe gain, and beam pointing accuracy are controllably improved by increasing the synthetic aperture resources. This on-demand enhancement mechanism enables timely enhancement of the scanning beam intensity when a sudden target maneuver is detected (manifested as continuous large fluctuations in the range sequence), improving the effective signal radiation intensity and echo signal-to-noise ratio in the target direction. This helps reduce signal scattering loss and multipath interference during the rapid displacement of highly dynamic targets, improving the quality and integrity of real-time echo signals. Ultimately, the improved signal quality reduces ranging deviations caused by weak echoes or signal distortion in the real-time target range data obtained through propagation delay analysis, thereby improving the positioning reliability during the maneuver phase, providing more accurate position nodes for continuous trajectory tracking, and improving resource utilization.

[0042] like Figure 2 As shown, in one embodiment, obtaining the motion mutation rate based on all absolute differences in the distance sequence in S3 includes: S31. Obtain the standard variation distance, and record the number of absolute differences in the distance sequence that exceed the standard variation distance as the number to be processed. S32. Divide the number to be processed by the number of absolute differences in the distance sequence to obtain the motion mutation rate.

[0043] In this embodiment, it should be noted that in S31, after obtaining the distance sequence generated in S2, the primary task of S31 is to set a judgment criterion to distinguish which distance changes belong to normal, gentle movements and which may be abnormal and large changes caused by violent maneuvers. This criterion is called the standard change distance, which is a preset distance difference threshold. The standard change distance is determined based on the maximum expected displacement of the target UAV within a preset time period (e.g., 0.1 seconds). For example, in a low-altitude urban scenario, the expected speed of the small UAV is within the standard speed (approximately 2 m / s). Taking a 0.1-second detection interval as an example, the maximum displacement is approximately 2 × 0.1 ≈ 0.2 meters. This displacement of 0.2 constitutes the standard change distance threshold.

[0044] Furthermore, the absolute value of the difference between all adjacent distance points in the distance sequence is calculated, and then each of these absolute values ​​is checked to see how many exceed the "standard variation distance". The number of these abnormal variation points identified as exceeding the standard is recorded as the "number to be processed". This number to be processed essentially counts the number of times the UAV's motion state underwent significant abrupt changes (manifested as drastic jumps in distance between adjacent detection points) during the observation period, providing a basic count for subsequent quantification of the overall degree of change.

[0045] In S32, based on the number of pending data points counted in S31 and all distance variation data points provided by the distance sequence (i.e., the total number of absolute differences), S32 calculates a proportional index. Specifically, the number of pending data points (i.e., the number of abnormal variation points exceeding the normal variation threshold) is divided by the total number of adjacent distance point pairs available for comparison in the entire sequence (equivalent to the sequence length minus one). This calculated proportional value is the motion mutation rate. It objectively reflects the frequency or prevalence of unexpectedly large changes in the motion state of the target UAV within the analysis time window. For example, a mutation rate of 0.6 means that the displacement between 60% of adjacent detection points exceeded the predetermined standard variation distance during the observation period, indicating dense non-stationary maneuvering behavior.

[0046] like Figure 3 As shown, in one embodiment, obtaining the correction parameter based on the motion mutation rate in S3 includes: S33. If the mutation rate of the movement exceeds the baseline ratio, the mutation rate of the movement will be used as a correction parameter. S34. If the mutation rate of the movement does not exceed the baseline ratio, then the baseline ratio shall be used as the correction parameter.

[0047] In this embodiment, it should be noted that in S33, after calculating the motion mutation rate, S33 is responsible for evaluating whether the mutation rate has reached a level requiring significant enhancement of detection. It compares the calculated mutation rate with a preset baseline ratio. The baseline ratio is determined by analyzing a limited number of historical UAV flight trajectory data. During stable flight, if a significant change occurs in the distance between adjacent detection points (exceeding the standard change distance) at a certain proportion, this proportion is used as the baseline ratio. For example, during straight-line cruising, the probability of a significant change in the distance between adjacent detection points (exceeding the standard change distance) is typically less than 0.3 (i.e., 30% of adjacent point pairs experience significant changes).

[0048] Furthermore, if the calculated motion mutation rate is greater than the baseline ratio, it indicates that the target UAV is currently in a very intense maneuvering state with high motion instability, and the existing beam configuration is at risk of insufficient detection. In this case, to better match the rapidly changing detection requirements, this larger, actually calculated motion mutation rate value is directly designated as the correction parameter for subsequent antenna resource increment calculations, and its magnitude directly corresponds to the expected enhancement amplitude.

[0049] In S34, when the comparison in S33 shows that the calculated motion mutation rate is less than or equal to the preset baseline ratio, it means that the target UAV's motion is relatively stable during the current observation period, without any dense or violent anomalous maneuvers. Although small fluctuations may still exist, the overall state is within a predictable range. To avoid excessive resource consumption for unnecessary enhancements in a stable state, a lower measured mutation rate value is not directly used as a correction parameter.

[0050] Instead, it uses a preset baseline ratio representing basic support requirements as a correction parameter. This ensures that even during stable flight, a basic level of resource enhancement is maintained to guarantee basic detection performance while preventing unnecessary resource consumption.

[0051] like Figure 4 As shown, in one embodiment, S3, which increments the first quantity based on the correction parameter and generates the second quantity, includes: S35. Multiply half of the first quantity by the correction parameter to obtain the increment ratio; S36. Add half of the first quantity to the increment ratio to obtain the second quantity.

[0052] In this embodiment, it should be noted that in S35, S35 begins to calculate how many additional antenna element resources are needed. First, the initial number of antenna elements used (the first number) is divided by two to obtain a baseline value (base number), which represents a basic order of magnitude in the initial resource configuration.

[0053] Next, the correction parameter obtained in S33 / S34 (whose magnitude reflects the degree of abrupt change in target motion and the required enhancement) is multiplied by this calculated base. The result of this multiplication operation is the "increment ratio." It directly represents the proportion of additional resources needed based on the baseline resource quantity, as assessed based on the current target motion state (reflected by the correction parameter). The magnitude of the increment ratio dynamically scales with changes in the correction parameter; the more intense the motion, the larger the relative increase required.

[0054] In S36, the final number of antenna elements participating in the transmitted scanning beam (the second number) is determined based on the increment ratio calculated in S35. It adds the increment ratio obtained in S35 to the baseline amount of initial resources (i.e., the base number obtained by dividing the first number by two). The result of this addition is the new total number of antenna elements. This calculation method ensures that: when the target maneuvers smoothly (the correction parameter is the base ratio), the second number will be slightly larger than the initial first number (approximately 1.5 times it), providing basic enhancement; when the target motion changes drastically (the correction parameter is a high change rate value), the second number will be significantly larger than the first number (the base number plus a larger increment ratio), deploying more antenna elements to provide stronger beamforming capabilities.

[0055] like Figure 5 As shown, in one embodiment, the reconstruction and enhancement of the scanning beam based on multiple sensing beams of a second number of antenna elements in S4 includes: S41. The scanning beam under the first number is reconstructed by multiple sensing beams of the second number of antenna elements to form an enhanced scanning beam.

[0056] In this embodiment, it should be noted that in S41, the sensing beam generated by the second number of antenna elements dynamically determined and activated in step S3 is used to substantially reconstruct and enhance the energy and spatial focusing characteristics of the scanning beam initially formed in step S2.

[0057] Specifically, the multiple sensing beams generated by the second number of antenna elements are spatially synthesized by readjusting the phase and amplitude weights of the signals from each element. The reconstructed target maintains the original spatial coverage area and pointing angle of the scanning beam, that is, continues to focus on the expected target UAV airspace direction.

[0058] The key is that by integrating the signal energy resources of more antenna elements, the resulting enhanced scanning beam can form a sharper main lobe, higher radiated energy density, and better suppression capability (reduced sidelobes) relative to the direction of interference in the original target airspace direction. For example, when a target UAV makes an emergency turn to escape, this reconstruction, even if the beam pointing angle remains unchanged, can maintain effective illumination intensity of the target reflection at a greater distance or against complex interference backgrounds due to its enhanced narrow main lobe and strong focusing.

[0059] like Figure 5 As shown, in one embodiment, step S4, which involves obtaining the real-time distance of the target UAV based on the real-time echo signal and generating a positioning report, includes: S42. Analyze the propagation delay of the real-time echo signal to determine the real-time distance between the target UAV and the communication base station, and generate a positioning report containing the real-time distance of the target UAV.

[0060] In this embodiment, it should be noted that in S42, upon receiving the real-time echo signal reflected back after the enhanced scanning beam illuminates the target, S42 immediately performs the crucial distance calculation. The complete time interval from the start of the enhanced beam transmission to the receiving array capturing the echo signal corresponding to that specific beam is measured; this is the total round-trip propagation time of the signal. Since the propagation speed is known, this total propagation time directly corresponds to the total physical path length the signal travels from the base station to the UAV target and then back to the base station. Dividing this calculated total path distance by two allows for an accurate calculation of the instantaneous straight-line distance between the target UAV and the communication base station transmission center at the current detection moment.

[0061] Finally, the calculated real-time distance value, along with necessary identification information (such as target ID and timestamp), is integrated into a clear and usable location report output.

[0062] A drone detection and positioning system based on integrated sensing is also provided, including: The detection module is used to acquire the transmitting and receiving linear arrays of the communication base station, wherein each transmitting linear array is configured with multiple antenna elements, and the antenna elements are configured to generate sensing beams containing multiple subcarriers; The data generation module is used to integrate multiple sensing beams based on a first number of antenna elements into a scanning beam, and to acquire multiple echo signals reflected by the target UAV at multiple detection time points within a preset time period before the current time based on the receiving linear array, and to generate multiple distance data based on the multiple echo signals, and to arrange the multiple distance data in chronological order to form a distance sequence. The correction and enhancement module is used to obtain the absolute difference between each adjacent distance data in the distance sequence, obtain the motion mutation rate based on all the absolute differences in the distance sequence, obtain the correction parameter based on the motion mutation rate, increment the first quantity based on the correction parameter and generate a second quantity, and reconstruct and enhance the scanning beam based on the multiple sensing beams of the second quantity of antenna elements. The positioning generation module is used to acquire the real-time echo signal reflected by the target UAV at the current moment based on the reconstructed and enhanced scanning beam, obtain the real-time distance of the target UAV based on the real-time echo signal, and generate a positioning report.

[0063] In one implementation, the correction and enhancement module is further configured to: obtain the standard variation distance, obtain the number of absolute differences in the distance sequence that exceed the standard variation distance and record them as the number to be processed; divide the number to be processed by the number of absolute differences in the distance sequence to obtain the motion mutation rate.

[0064] In one implementation, the correction enhancement module is further configured to: if the motion mutation rate exceeds the baseline ratio, use the motion mutation rate as a correction parameter; if the motion mutation rate does not exceed the baseline ratio, use the baseline ratio as a correction parameter.

[0065] In one implementation, the correction enhancement module is further configured to: multiply half of the first quantity by a correction parameter to obtain an increment ratio; and add half of the first quantity to the increment ratio to obtain a second quantity.

[0066] In this embodiment, it should be noted that the specific method of performing the operation of the above-mentioned UAV detection and positioning system based on sensor integration has been described in detail in the embodiments of the UAV detection and positioning method based on sensor integration, and will not be elaborated here.

[0067] The preferred embodiments of the present disclosure have been described in detail above with reference to the accompanying drawings. However, the present disclosure is not limited to the specific details of the above embodiments. Within the scope of the technical concept of the present disclosure, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0068] It should also be noted that the various specific technical features described in the above embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, this disclosure will not describe the various possible combinations separately.

[0069] Furthermore, various different embodiments of this disclosure can be combined in any way, as long as they do not violate the spirit of this disclosure, they should also be regarded as the content disclosed in this disclosure.

[0070] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. An unmanned aerial vehicle detection and positioning method based on sensory integration, characterized in that, The method comprises: obtaining a transmitting linear array and a receiving linear array of a communication base station, wherein the transmitting linear array is configured with a plurality of antenna elements, and the antenna elements are configured to generate a sensing beam containing a plurality of subcarriers; integrating a plurality of sensing beams of a first number of antenna elements into a scanning beam, obtaining a plurality of echo signals reflected by a target unmanned aerial vehicle at a plurality of detection time points within a preset time period before a current time based on the receiving linear array, generating a plurality of distance data based on the plurality of echo signals, and arranging the plurality of distance data in time sequence to form a distance sequence; obtaining an absolute difference value between each adjacent distance data in the distance sequence, obtaining a motion mutation rate based on all absolute difference values in the distance sequence, obtaining a correction parameter based on the motion mutation rate, incrementing the first number based on the correction parameter to generate a second number, and reconstructing and enhancing the scanning beam based on a plurality of sensing beams of the second number of antenna elements; obtaining a real-time echo signal reflected by the target unmanned aerial vehicle at the current time based on the reconstructed and enhanced scanning beam, obtaining a real-time distance of the target unmanned aerial vehicle based on the real-time echo signal, and generating a positioning report.

2. The method of claim 1, wherein, The method comprises: obtaining a standard change distance, obtaining a number of absolute difference values in the distance sequence that exceed the standard change distance, and recording the number as a to-be-processed number; dividing the to-be-processed number by the number of absolute difference values in the distance sequence to obtain the motion mutation rate. 3.The method of claim 1, wherein, The method comprises: if the motion mutation rate exceeds a basic ratio, taking the motion mutation rate as the correction parameter; if the motion mutation rate does not exceed the basic ratio, taking the basic ratio as the correction parameter.

4. The method of claim 1, wherein, The method comprises: multiplying one-half of the first number by the correction parameter to obtain an increment ratio; adding the increment ratio to one-half of the first number to obtain the second number.

5. The method of claim 1, wherein, The method comprises: reconstructing the scanning beam under the first number of antenna elements based on the second number of antenna elements to form an enhanced scanning beam.

6. The method of claim 1, wherein, The method comprises: analyzing the propagation delay of the real-time echo signal to determine the real-time distance between the target unmanned aerial vehicle and the communication base station, and generating a positioning report containing the real-time distance of the target unmanned aerial vehicle.

7. An unmanned aerial vehicle detection and positioning system based on the integration of common sense, characterized in that, The system comprises: a detection module for obtaining a transmitting linear array and a receiving linear array of a communication base station, wherein the transmitting linear array is configured with a plurality of antenna elements, and the antenna elements are configured to generate a sensing beam containing a plurality of subcarriers; a data generation module for integrating a plurality of sensing beams of a first number of antenna elements into a scanning beam, obtaining a plurality of echo signals reflected by a target unmanned aerial vehicle at a plurality of detection time points within a preset time period before a current time based on the receiving linear array, generating a plurality of distance data based on the plurality of echo signals, and arranging the plurality of distance data in time sequence to form a distance sequence; a data generation module for integrating a plurality of sensing beams of a first number of antenna elements into a scanning beam, obtaining a plurality of echo signals reflected by a target unmanned aerial vehicle at a plurality of detection time points within a preset time period before a current time based on the receiving linear array, generating a plurality of distance data based on the plurality of echo signals, and arranging the plurality of distance data in time sequence to form a distance sequence; The correction enhancement module is configured to obtain absolute differences between each pair of adjacent distance data in the distance sequence, obtain a motion mutation rate based on all the absolute differences in the distance sequence, obtain a correction parameter based on the motion mutation rate, increment the first number based on the correction parameter to generate a second number, and reconstruct the scanning beam based on the second number of the plurality of sensing beams of the antenna unit. The positioning generation module is configured to obtain a real-time echo signal reflected by the target UAV at the current time based on the reconstructed scanning beam, obtain a real-time distance of the target UAV based on the real-time echo signal, and generate a positioning report.

8. The system according to claim 7, wherein, The correction enhancement module is further configured to: obtain a standard change distance, obtain a number of absolute differences in the distance sequence that exceed the standard change distance, and record the number as a to-be-processed number; divide the to-be-processed number by a number of absolute differences in the distance sequence to obtain the motion mutation rate.

9. The system of claim 7, wherein, The correction enhancement module is further configured to: if the motion mutation rate exceeds a basic ratio, take the motion mutation rate as the correction parameter; if the motion mutation rate does not exceed the basic ratio, take the basic ratio as the correction parameter.

10. The system of claim 7, wherein, The correction enhancement module is further configured to: multiply one-half of the first number by the correction parameter to obtain an increment ratio; add the increment ratio to one-half of the first number to obtain the second number.

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