Test method, device and system for performance of low-altitude target monitoring equipment

Abstract

The application relates to the technical field of device performance monitoring, and discloses a test method for the performance of a low-altitude target monitoring device, which comprises the following steps: controlling a flight platform serving as a test target to fly along a preset route in a monitoring airspace of the low-altitude target monitoring device to be tested; obtaining target detection track data collected by the low-altitude target monitoring device to be tested during the flight of the flight platform along the preset route, and synchronously obtaining real track data output by a high-precision positioning device; wherein the high-precision positioning device is integrated in the flight platform; performing time-space alignment on the target detection track data and the real track data; and determining a detection error of the target detection track data relative to the real track data under the time-space alignment benchmark. The test method improves the accuracy and confidence of the performance test result of the low-altitude target monitoring device. The application also discloses a test device and system for the performance of a low-altitude target monitoring device.

Description

Technical Field

[0001] This application relates to the field of performance testing technology for monitoring equipment, and for example to a testing method, apparatus and system for the performance of low-altitude target monitoring equipment. Background Technology

[0002] With the popularization of drone technology and the booming development of the low-altitude economy, activities in low-altitude airspace are becoming increasingly frequent. At the same time, the security threats posed by "low, small, and slow" targets, such as unauthorized flights, illegal intrusions, and terrorist attacks, are becoming increasingly prominent, posing a serious challenge to public and national safety. To effectively manage low-altitude airspace and achieve timely detection and handling of illegal targets, various low-altitude target monitoring equipment (such as low-altitude surveillance radar, radio detection equipment, and 5G-A integrated sensing base stations) have been extensively developed and deployed. Accurate, objective, and quantifiable evaluation of the core detection performance indicators—such as target positioning accuracy, velocity measurement accuracy, and tracking stability—is an indispensable part of ensuring equipment quality and operational effectiveness during the development, standardization, factory inspection, on-site installation and acceptance, and long-term operation and maintenance of low-altitude target monitoring equipment.

[0003] The common testing method in the existing technology is to directly use the positioning data output by the flight control system of the UAV platform itself as the reference benchmark for spatial position and speed; and to directly compare the target track point detected by the low-altitude target monitoring equipment under test with the latitude, longitude, elevation and speed information of the corresponding time point recorded in the flight control log of the UAV platform itself, calculate the difference between the two, and use it as the detection error of the low-altitude target monitoring equipment under test.

[0004] In the process of implementing the embodiments of this disclosure, at least the following problems were found in the related art: Simply performing spatial distance calculations on two sets of heterogeneous data from the UAV platform's own flight control system and the low-altitude target monitoring equipment under test can easily lead to inaccurate performance test results for the low-altitude target monitoring equipment.

[0005] 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 application, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] To provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended as a general commentary, nor is it intended to identify key / important components or describe the scope of protection of these embodiments, but rather as a prelude to the detailed description that follows.

[0007] This disclosure provides a method, apparatus, and system for testing the performance of low-altitude target monitoring equipment, thereby improving the accuracy of performance test results for low-altitude target monitoring equipment.

[0008] In some embodiments, a method for testing the performance of a low-altitude target monitoring device includes: controlling a flight platform, which is the test target, to fly along a preset route within the monitoring airspace of the low-altitude target monitoring device under test; obtaining target detection trajectory data collected by the low-altitude target monitoring device under test during the flight of the flight platform along the preset route, and simultaneously obtaining real trajectory data output by a high-precision positioning device; wherein the high-precision positioning device is integrated into the flight platform; performing spatiotemporal alignment of the target detection trajectory data and the real trajectory data; and determining the detection error of the target detection trajectory data relative to the real trajectory data under the spatiotemporal alignment reference.

[0009] Optionally, spatiotemporal alignment of the target detection track data and the real track data is performed, including: temporal alignment of the target detection track data and the real track data; and / or spatial alignment of the target detection track data and the real track data.

[0010] Optionally, the target detection track data and the real track data are time aligned, including: after converting both the real track data and the target detection track data to the Coordinated Universal Time (UTC) time base, the high-sampling-rate real track data is interpolated to calculate the precise time corresponding to each detection point of the target detection track data.

[0011] Optionally, the target detection track data and the actual track data are time-aligned, including: mounting a cooperative beacon synchronized with the clock of the high-precision positioning equipment on the flight platform; transmitting the data packets containing timestamp information received by the cooperative beacon and generated by the high-precision positioning equipment to the external timing input terminal of the low-altitude target monitoring equipment under test, so as to force synchronization of the internal clock of the low-altitude target monitoring equipment under test.

[0012] Optionally, the high-sampling-rate real track data is interpolated to the precise time corresponding to each detection point of the target detection track data, including: determining the high-sampling-rate real track data sequence of the high-precision positioning equipment and the low-sampling-rate detection point time sequence of the low-altitude target monitoring equipment; for the target detection point time in the low-sampling-rate detection point time sequence, selecting multiple real sampling points of the high-precision positioning equipment as interpolation nodes in the neighborhood before and after the target detection point time; based on the selected interpolation nodes and the position data corresponding to the interpolation nodes, calculating the target interpolated position data corresponding to the target detection point time, and using the target interpolated position data as the real track data after time alignment with the target detection track data.

[0013] Optionally, the target detection track data and the actual track data are spatially aligned, including: acquiring the first position data output by the high-precision positioning device in the first spatial coordinate system, and the second position data detected by the low-altitude target monitoring device in the second spatial coordinate system; constructing a station-centered rectangular coordinate system with the antenna phase center of the low-altitude target monitoring device as the coordinate origin; and converting the first position data and the second position data to the station-centered rectangular coordinate system based on the predetermined coordinate transformation relationship between the first spatial coordinate system, the second spatial coordinate system and the station-centered rectangular coordinate system.

[0014] Optionally, the flight platform used as the test target is controlled to fly along a preset route within the monitoring airspace of the low-altitude target monitoring equipment under test. This includes controlling the flight platform to fly in one or more of the following preset flight modes: uniform straight-line flight mode, used to test the speed measurement accuracy of the low-altitude target monitoring equipment under test on a stable flight path; uniform circular flight mode, used to test the tracking stability of the low-altitude target monitoring equipment under test under continuous large-angle maneuvers; layered flight mode at different altitudes, used to test the detection altitude accuracy of the low-altitude target monitoring equipment under test at different elevation angles and altitude levels; and variable acceleration maneuver flight mode, used to test the transient response capability of the low-altitude target monitoring equipment under sudden high-dynamic motion.

[0015] Optionally, under the spatiotemporal alignment reference, the detection error of the target detection trajectory data relative to the real trajectory data is determined, including: calculating the instantaneous position error and instantaneous velocity error of each target detection point after spatiotemporal alignment; and determining the detection error of the target detection trajectory data relative to the real trajectory data based on the instantaneous position error and instantaneous velocity error.

[0016] Optionally, the testing method for the performance of low-altitude target monitoring equipment further includes: generating a traceable test report to establish a correlation link between the detection error and the traceable metrological benchmark; wherein the traceable test report includes one or more of the following: error statistics, used to record the detection error of the target detection trajectory data calculated based on the spatiotemporal alignment benchmark relative to the real trajectory data; traceability correlation, used to store the metrological calibration certificate number of the high-precision positioning equipment; and reproduction support, used to save environmental parameter record files during the test process and an electronic flight path diagram that overlays and displays the target detection trajectory data and the real trajectory data.

[0017] In some embodiments, a testing apparatus for the performance of a low-altitude target monitoring device includes: a processor, a memory, and a computer program stored in the memory, wherein the processor, when executing the computer program, implements a testing method for the performance of the low-altitude target monitoring device.

[0018] In some embodiments, a testing system for the performance of a low-altitude target monitoring device includes: a flight platform configured to fly along a preset route within the monitoring airspace of the low-altitude target monitoring device under test; a high-precision positioning device integrated into the flight platform and configured to collect real trajectory data during the flight of the flight platform along the preset route; the low-altitude target monitoring device under test configured to collect target detection trajectory data during the flight of the flight platform along the preset route; and the aforementioned testing device for the performance of the low-altitude target monitoring device.

[0019] The testing method, apparatus, and system for low-altitude target monitoring equipment provided in this disclosure can achieve the following technical effects: In this disclosed technical solution, the real track data output by the high-precision positioning device has centimeter-level dynamic positioning accuracy and is traceable to national metrological standards. This effectively solves the inherent defects of low reference accuracy and lack of traceability caused by using ordinary flight control positioning data of UAVs as the reference true value in existing technologies. Simultaneously, by precisely aligning the target detection track data with the real track data under a unified time reference and spatial coordinate system, the mismatch error and geometric projection deviation caused by time asynchrony and coordinate definition differences are completely separated. This ensures that the final calculated detection error can truly and accurately reflect the detection performance of the tested low-altitude target monitoring device. Thus, by introducing a high-precision positioning device integrated into the flight platform as a traceable real track data source, and further performing spatiotemporal alignment processing after obtaining the target detection track data, the systematic bias introduced by insufficient reference accuracy and inconsistent spatiotemporal references of heterogeneous data in traditional testing methods is eliminated at its source. This significantly improves the accuracy and confidence of the performance test results of the low-altitude target monitoring device.

[0020] The above general description and the description below are exemplary and illustrative only and are not intended to limit this application. Attached Figure Description

[0021] One or more embodiments are illustrated by way of example with reference to the accompanying drawings. These illustrations and drawings do not constitute a limitation on the embodiments. Elements having the same reference numerals in the drawings are shown as similar elements. The drawings are not to be scaled. And wherein: Figure 1 This is a schematic flowchart of a test method for the performance of a low-altitude target monitoring device provided in an embodiment of this disclosure; Figure 2 This is a schematic flowchart of another test method for the performance of low-altitude target monitoring equipment provided in this disclosure embodiment; Figure 3 This is a schematic flowchart of another test method for the performance of low-altitude target monitoring equipment provided in this disclosure embodiment; Figure 4 This is a schematic flowchart of another test method for the performance of low-altitude target monitoring equipment provided in this disclosure embodiment; Figure 5 This is a schematic flowchart of another test method for the performance of low-altitude target monitoring equipment provided in this disclosure embodiment; Figure 6 This is a schematic flowchart of another test method for the performance of low-altitude target monitoring equipment provided in this disclosure embodiment; Figure 7 This is a schematic diagram of the structure of a test device for the performance of a low-altitude target monitoring device provided in an embodiment of this disclosure; Figure 8 This is a schematic diagram of the structure of a test system for the performance of a low-altitude target monitoring device provided in an embodiment of this disclosure. Detailed Implementation

[0022] To provide a more detailed understanding of the features and technical content of the embodiments of this disclosure, the implementation of the embodiments of this disclosure will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for illustrative purposes only and are not intended to limit the embodiments of this disclosure. In the following technical description, for ease of explanation, several details are used to provide a full understanding of the disclosed embodiments. However, one or more embodiments may still be implemented without these details. In other cases, well-known structures and devices may be simplified in their depiction to simplify the drawings.

[0023] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this disclosure described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0024] Unless otherwise stated, the term "multiple" means two or more. In embodiments of this disclosure, the character " / " indicates that the preceding and following objects are in an "OR" relationship. For example, A / B means: A or B. The term "and / or" describes an association relationship between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or, A and B. The term "correspondence" can refer to an association or binding relationship; A corresponding to B means that there is an association or binding relationship between A and B.

[0025] In this embodiment of the disclosure, combined with Figure 8As shown, the test system 800 for the performance of low-altitude target monitoring equipment includes a flight platform 801, a high-precision positioning device 802, a low-altitude target monitoring device 803 under test, and a test apparatus 700 for the performance of the low-altitude target monitoring equipment. The flight platform 801 is configured to fly along a preset route within the monitoring airspace of the low-altitude target monitoring device 803 under test. The high-precision positioning device 802 is integrated into the flight platform 801 and is configured to collect real-time trajectory data during the flight of the flight platform 801 along the preset route. The low-altitude target monitoring device 803 under test is configured to collect target detection trajectory data during the flight of the flight platform 801 along the preset route. Specifically: Flight platform 801 refers to an aerial mobile vehicle capable of carrying mission payloads and flying autonomously or under controlled flight along a preset route in low-altitude airspace. For example, flight platform 801 can be any of the following: multi-rotor UAV, fixed-wing UAV, vertical take-off and landing fixed-wing UAV, or unmanned helicopter, and its flight control system supports route planning import, autonomous navigation, and precise tracking flight along a preset route.

[0026] High-precision positioning equipment 802 refers to a combined navigation and measurement device capable of outputting its own three-dimensional position, three-dimensional velocity, and precise time information in real time or post-processing with an accuracy superior to that of the low-altitude target monitoring equipment being measured. For example, high-precision positioning equipment 802 includes: a high-precision Global Navigation Satellite System (GNSS) receiver supporting Real-Time Kinematic (RTK) or Post-Processed Kinematic (PPK) operating modes, and a high-precision Inertial Navigation System (INS) for providing continuous attitude estimation when satellite signals are disturbed or briefly lost. High-precision positioning equipment 802 must be calibrated by a qualified metrology institution to ensure that its output physical quantities such as position, velocity, and time can be traced back to national or international metrology standards through an uninterrupted calibration link.

[0027] The low-altitude target monitoring equipment 803 refers to an electronic information system deployed on the ground or an airborne platform for detecting, locating, tracking, and identifying flying targets in low-altitude airspace. For example, the low-altitude target monitoring equipment 803 includes, but is not limited to: low-altitude surveillance radar, radio spectrum detection equipment, integrated sensing base stations based on fifth-generation mobile communication enhancement technology, or other low-altitude target sensing equipment employing electromagnetic waves, acoustic waves, photoelectric detection, or other detection methods. The low-altitude target monitoring equipment 803 has the capability to output track data containing timestamps, spatial positions, and speed information for targets entering its monitored airspace.

[0028] In this embodiment, the high-precision positioning device 802 is fixedly integrated onto the flight platform 801, forming a rigid connection with the flight platform 801. The two work together as a single unit in the air to simulate the test target. The low-altitude target monitoring device 803 is independently deployed on the ground or at its launch point, and its monitoring airspace covers the preset flight path area of ​​the flight platform. During the test, the flight platform 801, carrying the high-precision positioning device 802, flies along a preset path within the monitoring airspace of the low-altitude target monitoring device 803. The high-precision positioning device 802 records its real position and time information in real time as a truth benchmark. Simultaneously, the low-altitude target monitoring device 803 detects and tracks the flight platform and outputs target trajectory data. The two data streams converge to the testing device for spatiotemporal alignment and error calculation, thereby achieving a quantitative evaluation of the detection performance of the low-altitude target monitoring device 803.

[0029] Combination Figure 1 As shown in the embodiments of this disclosure, a method for testing the performance of a low-altitude target monitoring device is provided, comprising the following steps: S101 controls the flight platform, which is the test target, to fly along a preset route within the monitoring airspace of the low-altitude target monitoring equipment.

[0030] Optionally, the flight platform used as the test target is controlled to fly along a preset route within the monitoring airspace of the low-altitude target monitoring equipment under test. This includes controlling the flight platform to fly in one or more of the following preset flight modes: uniform straight-line flight mode, used to test the speed measurement accuracy of the low-altitude target monitoring equipment under test on a stable flight path; uniform circular flight mode, used to test the tracking stability of the low-altitude target monitoring equipment under test under continuous large-angle maneuvers; layered flight mode at different altitudes, used to test the detection altitude accuracy of the low-altitude target monitoring equipment under test at different elevation angles and altitude levels; and variable acceleration maneuver flight mode, used to test the transient response capability of the low-altitude target monitoring equipment under sudden high-dynamic motion.

[0031] In some possible implementations, controlling the flight platform used as the test target to fly along a preset route within the monitoring airspace of the low-altitude target monitoring equipment includes: establishing a kinematic state-space model of the flight platform in an inertial coordinate system, where the kinematic state-space model uses the position vector, velocity vector, and acceleration vector of the flight platform as state variables; obtaining the performance indicators to be evaluated specified for this test task, and obtaining the corresponding performance evaluation functions for the performance indicators to be evaluated; wherein, the input of the performance evaluation function is the time series of state variables output by the kinematic state-space model, and the output is a representation of the performance indicators to be evaluated. The system quantifies the degree of incentive of performance indicators; based on the quantified score of the performance evaluation function, it determines the target flight mode from a preset flight mode set, which includes uniform linear flight mode, uniform circular flight mode, flight mode layered at different altitudes, and variable acceleration maneuver flight mode; it obtains the kinematic constraints corresponding to the target flight mode, and drives the kinematic state space model based on the kinematic constraints to generate a reference waypoint sequence corresponding to the target flight mode; it uploads the reference waypoint sequence to the flight control system of the flight platform to control the flight platform to fly according to the reference waypoint sequence.

[0032] Here, the performance evaluation function includes one or more of the following: velocity accuracy evaluation function, tracking stability evaluation function, altitude accuracy evaluation function, and transient response capability evaluation function. For the uniform linear flight mode, by constraining the acceleration vector to the zero norm, the kinematic state-space model outputs a steady velocity sequence to maximize the response value of the velocity accuracy evaluation function. For the uniform circular flight mode, by constraining the velocity magnitude and the rate of change of the velocity direction angle to a constant value, the kinematic state-space model outputs a continuous azimuth change sequence to maximize the response value of the tracking stability evaluation function. For the flight mode with different altitude layers, by setting the altitude state variable to multiple discrete preset values ​​and maintaining horizontal flight respectively, the kinematic state-space model outputs a multi-elevation angle coverage sequence to maximize the response value of the altitude accuracy evaluation function. For the variable acceleration maneuvering flight mode, by introducing a non-zero derivative term of acceleration with respect to time, the kinematic state-space model outputs a transient sequence containing jerk excitation to maximize the response value of the transient response capability evaluation function.

[0033] The following is a specific example illustrating the implementation scheme of a flight platform flying along a preset route. A special acceptance test on the tracking stability of a low-altitude surveillance radar is planned. The test system reads the test mission configuration file and identifies the performance indicator to be evaluated for this mission as tracking stability. The test system calls a predefined tracking stability evaluation function (e.g., tracking stability Jtrack = (azimuth angle sustained change rate × trajectory maintenance time) / (number of track interruptions + adjustment coefficient)). The output of the tracking stability evaluation function is a quantitative score of 0-100 points; a higher score indicates a better incentive effect of the route on tracking stability. The test system calculates the expected response values ​​of the tracking stability evaluation function for four preset flight modes. When the uniform circular flight mode has the highest expected response value, the test system automatically selects the uniform circular flight mode as the target flight mode. The test system retrieves the kinematic constraints corresponding to the uniform circular flight mode: velocity magnitude constraint: vec{v} = 15m / s; azimuth rate of change constraint: dot{theta} = 10 / circ / s (i.e., one circle is completed in 36 seconds). Combined with the pre-set center coordinates (0, 0, 100) and radius R = 200m, the system drives the kinematic state-space model to recursively generate a sequence of reference waypoints (including time, X-coordinate, Y-coordinate, Z-coordinate, velocity, heading angle, etc.). The test system packages this reference waypoint sequence into a waypoint file and uploads it to the UAV flight control system via a data transmission link. The flight control system compares the desired position of each waypoint with the real-time GPS position and drives the motors using a PID control law, enabling the UAV to fly precisely along the circular flight path.

[0034] By establishing a kinematic state-space model of the flight platform and constructing corresponding performance evaluation functions for the performance indicators to be evaluated, the optimal target flight mode is automatically determined from a preset set of flight modes based on the quantified score of the evaluation function. Then, based on the kinematic constraints corresponding to this mode, the state-space model is driven to generate a sequence of reference waypoints to control the flight platform's flight. This transforms the traditional route planning process, which relies on the experience of test personnel, into a quantifiable, reproducible, and optimizable automated decision-making and execution closed loop. This scheme enables the testing of key performance indicators such as speed measurement accuracy, tracking stability, altitude accuracy, and transient response capability to be performed under dynamic input conditions that maximize their information gain—that is, maximizing speed measurement accuracy through uniform straight-line flight, maximizing tracking stability through uniform circular flight, maximizing altitude accuracy through layered flight, and maximizing transient response through variable acceleration maneuvers. This significantly improves the validity of test data, the confidence of evaluation conclusions, and the comparability of test results between different devices, providing algorithmic support and engineering implementation paths for the standardized and refined testing of low-altitude target monitoring equipment performance.

[0035] S102, obtain the target detection trajectory data collected by the low-altitude target monitoring equipment during the flight of the flight platform along the preset route, and simultaneously obtain the real trajectory data output by the high-precision positioning equipment; wherein, the high-precision positioning equipment is integrated into the flight platform.

[0036] S103 performs spatiotemporal alignment between target detection track data and actual track data.

[0037] Optionally, spatiotemporal alignment of the target detection track data and the real track data is performed, including: temporal alignment of the target detection track data and the real track data; and / or spatial alignment of the target detection track data and the real track data.

[0038] In some possible implementations, spatiotemporal alignment of target detection track data and real track data is performed, including: time alignment of target detection track data and real track data.

[0039] In some possible implementations, spatiotemporal alignment of target detection track data and real track data is performed, including spatial alignment of target detection track data and real track data.

[0040] In some possible implementations, spatiotemporal alignment of target detection track data and real track data is performed, including: aligning the target detection track data and real track data temporally, and then aligning the target detection track data and real track data spatially.

[0041] By performing temporal and spatial alignment processing on the target detection track data and the actual track data respectively, the systemic problem of dual systematic bias introduced by the asynchronous time of heterogeneous data and the inconsistent definition of spatial coordinate systems in the performance testing of low-altitude target monitoring equipment is systematically solved. In the temporal dimension, the target position error caused by the mismatch of sampling time is eliminated; in the spatial dimension, the geometric projection bias introduced by the offset of the coordinate system origin and axial deflection is eliminated. The temporal and spatial alignment processing ensures that each pair of data points used for error comparison is strictly aligned in both time and space dimensions. This allows the finally calculated detection position error and detection velocity error to be truly and accurately attributed to the detection capability of the tested low-altitude target monitoring equipment itself, rather than the systematic error of the data comparison method itself, thereby significantly improving the scientificity and confidence of the performance test results.

[0042] S104, under the spatiotemporal alignment reference, determine the detection error of the target detection trajectory data relative to the actual trajectory data.

[0043] Optionally, under the spatiotemporal alignment reference, the detection error of the target detection trajectory data relative to the real trajectory data is determined, including: calculating the instantaneous position error and instantaneous velocity error of each target detection point after spatiotemporal alignment; and determining the detection error of the target detection trajectory data relative to the real trajectory data based on the instantaneous position error and instantaneous velocity error.

[0044] Here, the target detection trajectory data includes the target detection three-dimensional coordinates and the target detection three-dimensional velocity vector of the flight platform at the detection point, and the real trajectory data includes the real three-dimensional coordinates and the real three-dimensional velocity vector of the flight platform at the detection point.

[0045] In some possible implementations, the instantaneous position error of each target detection point after spatiotemporal alignment is calculated, including: for each target detection point after spatiotemporal alignment, calculating the spatial Euclidean distance between the target detection three-dimensional coordinates corresponding to the target detection point and the real three-dimensional coordinates, and determining the calculated spatial Euclidean distance as the instantaneous position error of the target detection point.

[0046] In practical applications, for the k-th target detection point, the instantaneous position error is calculated according to the following formula:

[0047] in,( , , () represents the three-dimensional coordinates of the k-th target detection point in the target detection track data in the station-centered rectangular coordinate system. , , ) represents the true three-dimensional coordinates of the k-th target detection point in the station-centered rectangular coordinate system in the actual trajectory data.

[0048] In some possible implementations, the instantaneous position error and instantaneous velocity error of each target detection point after spatiotemporal alignment are calculated, including: calculating the magnitude of the difference between the target detection three-dimensional velocity vector corresponding to the target detection point and the real three-dimensional velocity vector, and determining the magnitude of the calculated difference as the instantaneous velocity error of the target detection point.

[0049] In practical applications, for the k-th target detection point, the instantaneous velocity error is calculated according to the following formula:

[0050] in,( , , ) represents the target detection three-dimensional velocity vector of the k-th target detection point in the target detection trajectory data. , , ) represents the true three-dimensional velocity vector of the k-th target detection point in the real trajectory data.

[0051] In some possible implementations, the detection error of the target detection track data relative to the real track data is determined based on the instantaneous position error and instantaneous velocity error. This includes: for multiple target detection points on the effective track, calculating the root mean square values ​​of the instantaneous position error and instantaneous velocity error respectively, and using the calculated root mean square values ​​as the root mean square error of the detection position and the root mean square error of the detection velocity of the low-altitude target monitoring equipment under test, so as to characterize the overall accuracy of the low-altitude target monitoring equipment under test.

[0052] By calculating the root mean square values ​​of instantaneous position error and instantaneous velocity error as the root mean square error of detection position and root mean square error of detection velocity of the tested low-altitude target monitoring equipment, the error information of all detection points on the entire test track can be comprehensively condensed and used as a single numerical index to fully reflect the overall detection accuracy level of the tested equipment. This provides a comprehensive evaluation scale that is both representative and robust for horizontal comparison and vertical tracking of performance between different equipment and between different batches of the same equipment.

[0053] In some other possible implementations, the detection error of the target detection track data relative to the real track data is determined based on the instantaneous position error and instantaneous velocity error. This includes: for multiple target detection points on the effective track, calculating the standard deviation of the instantaneous position error and instantaneous velocity error respectively, and using the calculated standard deviation as the standard error of the detection position and the standard error of the detection velocity of the low-altitude target monitoring equipment under test, so as to characterize the random error of the low-altitude target monitoring equipment under test.

[0054] By calculating the standard deviations of instantaneous position and velocity errors as the standard errors of the detection position and velocity of the tested low-altitude target monitoring equipment, the influence of system bias on the error sequence can be effectively isolated, and the random dispersion of the equipment's detection output can be specifically extracted and quantified. Testers can clearly distinguish between the two different types of error sources—"inherent bias" and "random fluctuations"—providing more targeted diagnostic information for equipment debugging and algorithm optimization.

[0055] In some other possible implementations, the detection error of the target detection track data relative to the real track data is determined based on the instantaneous position error and instantaneous velocity error. This includes: for multiple target detection points on the effective track, calculating the maximum error values ​​of the instantaneous position error and instantaneous velocity error respectively, and using the calculated maximum error values ​​as the maximum detection position error and maximum detection velocity error of the low-altitude target monitoring equipment under test, so as to characterize the extreme performance of the low-altitude target monitoring equipment under test.

[0056] By calculating the maximum error values ​​of instantaneous position error and instantaneous velocity error as the maximum detection position error and maximum detection velocity error of the tested low-altitude target monitoring equipment, it is possible to specifically evaluate the extreme operating condition performance boundaries exposed by the tested equipment during the test. It can effectively reveal the performance shortcomings and failure risks of the tested low-altitude target monitoring equipment under critical conditions such as high target maneuverability, strong interference, or low signal-to-noise ratio, and provide key data support for the evaluation of the equipment's practical applicability and redundancy design.

[0057] In some other possible implementations, the detection error of the target detection track data relative to the real track data is determined based on the instantaneous position error and instantaneous velocity error. This includes: for multiple target detection points on the effective track, calculating the arithmetic mean of the instantaneous position error and instantaneous velocity error respectively, and using the calculated arithmetic mean as the arithmetic mean error of the detection position and the arithmetic mean error of the detection velocity of the low-altitude target monitoring equipment under test, so as to characterize the system accuracy of the low-altitude target monitoring equipment under test.

[0058] By calculating the arithmetic mean of instantaneous position error and instantaneous velocity error as the arithmetic mean error of detection position and detection velocity of the low-altitude target monitoring equipment under test, it is possible to specifically extract and quantify the persistent systematic deviation components in the detection output of the equipment under test. Based on the sign and magnitude of the arithmetic mean error, reverse compensation correction can be applied to the equipment output, thereby effectively improving the detection accuracy of the equipment in actual deployment.

[0059] The testing method for low-altitude target monitoring equipment performance provided in this disclosure utilizes a high-precision positioning device to output real track data with centimeter-level dynamic positioning accuracy that is traceable to national metrological standards. This effectively solves the inherent defects of low reference accuracy and lack of traceability caused by using ordinary UAV flight control positioning data as the reference truth in existing technologies. Simultaneously, by precisely aligning the target detection track data with the real track data under a unified time reference and spatial coordinate system, mismatch errors and geometric projection deviations caused by time asynchrony and coordinate definition differences are completely separated. This ensures that the final calculated detection error accurately reflects the detection performance of the tested low-altitude target monitoring equipment. Thus, by introducing a high-precision positioning device integrated into the flight platform as a traceable real track data source, and further performing spatiotemporal alignment processing after obtaining the target detection track data, the systematic bias introduced by insufficient reference accuracy and inconsistent spatiotemporal references of heterogeneous data in traditional testing methods is eliminated at its source. This significantly improves the accuracy and confidence of the low-altitude target monitoring equipment performance test results.

[0060] In some embodiments, combined with Figure 2 As shown, time alignment of target detection track data and real track data includes the following steps: S201 converts both real track data and target detection track data to the Coordinated Universal Time (UTC) time base.

[0061] Coordinated Universal Time (UTC) is a globally unified time scale maintained jointly by the International Bureau of Weights and Measures and the International Earth Rotation Service.

[0062] Optionally, the actual flight track data can be converted to a Coordinated Universal Time (UTC) time reference, including: obtaining high-precision GPS time from a high-precision global navigation satellite system receiver built into a high-precision positioning device; and converting GPS time or BeiDou time to UTC time using built-in time difference compensation parameters.

[0063] Optionally, the target detection track data is converted to Coordinated Universal Time (UTC) time reference, including: connecting the external time synchronization input port of the low-altitude target monitoring device to a standard time synchronization device, wherein the standard time synchronization device continuously outputs time synchronization data packets containing UTC absolute time information; after receiving the time synchronization data packets, the low-altitude target monitoring device forcibly calibrates the timing start point and counting frequency of its internal local clock to be synchronized with UTC.

[0064] S202 converts both the real track data and the target detection track data to the Coordinated Universal Time (UTC) time base, and then interpolates the high-sampling-rate real track data to calculate the precise time corresponding to each detection point in the target detection track data.

[0065] Optionally, the high-sampling-rate real track data is interpolated to the precise time corresponding to each detection point of the target detection track data, including: determining the high-sampling-rate real track data sequence of the high-precision positioning equipment and the low-sampling-rate detection point time sequence of the low-altitude target monitoring equipment; for the target detection point time in the low-sampling-rate detection point time sequence, selecting multiple real sampling points of the high-precision positioning equipment as interpolation nodes in the neighborhood before and after the target detection point time; based on the selected interpolation nodes and the position data corresponding to the interpolation nodes, calculating the target interpolated position data corresponding to the target detection point time, and using the target interpolated position data as the real track data after time alignment with the target detection track data.

[0066] In practical applications, firstly, the real track data output by the high-precision positioning equipment at a sampling rate of 100 Hz is analyzed, and the UTC timestamp and corresponding three-dimensional spatial coordinates of each record are extracted to construct a high-sampling-rate real track data sequence. Simultaneously, the target detection track data output by the low-altitude target monitoring equipment at a refresh rate of Hz or 10 Hz is analyzed, and the UTC timestamp corresponding to each detection point is extracted to construct a low-sampling-rate detection point time sequence. Then, for each target detection point time in the target detection track data, several neighboring sampling points are searched forward and backward along the time axis of the real track data sequence, selecting a total of three to five real sampling points that are closest in time as interpolation nodes. Next, based on the timestamps of the selected interpolation nodes and their corresponding three-dimensional coordinates, a Lagrange interpolation polynomial or cubic spline interpolation function is constructed. The current detection point time is substituted into this interpolation function to calculate the three-dimensional interpolated position coordinates (i.e., the target interpolated position data) corresponding to that target detection point time. Finally, the interpolated position coordinates are recorded as true track data with strict time alignment to the target detection point's time, and stored in pairs with the target detection point's own position data for subsequent instantaneous error calculation. This interpolation and alignment process is performed for each of all target detection point times.

[0067] Taking a real low-altitude surveillance radar test as an example: the high-precision positioning equipment has a sampling frequency of 100Hz, meaning it outputs a real position point every 0.01 seconds; the radar under test outputs data at a frequency of 10Hz, meaning it outputs a detection point every 0.1 seconds. On a certain test route, the high-precision positioning equipment recorded the following partial real track data: position at time 10.00 (150.00, 0.00, 100.00) meters, position at time 10.01 (150.15, 0.00, 100.00) meters, position at time 10.02 (150.30, 0.00, 100.00) meters, position at time 10.03 (150.45, 0.00, 100.00) meters, and position at time 10.04 (150.60, 0.00, 100.00) meters. The radar under test outputs a detection point at 10.025 seconds, and the target position recorded by this detection point is (152.10, -0.35, 101.20) meters. Since there is no directly corresponding sampling point for 10.025 seconds in the actual flight track data, the system uses 10.025 seconds as the baseline and selects four actual sampling points (10.01 seconds, 10.02 seconds, 10.03 seconds, and 10.04 seconds) in the preceding and following neighborhoods as interpolation nodes. Based on the time and position coordinates of these four nodes, a Lagrange interpolation function is constructed. Substituting 10.025 seconds into the calculation, the interpolated true position at that moment is obtained as (150.375, 0.00, 100.00) meters. Therefore, the comparison benchmark of the detection point was originally approximately selected as the nearest point (10.02 seconds or 10.03 seconds), and was precisely corrected to the actual position at 10.025 seconds (150.375, 0.00, 100.00 meters), forming a strictly time-aligned data pair with the detection position (152.10, -0.35, 101.20 meters).

[0068] By performing time interpolation calculations based on neighborhood interpolation nodes for each low-sampling-rate target detection point, based on the high-sampling-rate output of the high-precision positioning equipment, the time mismatch problem caused by inconsistent sampling frequencies and non-overlapping sampling times of the two data sources is effectively solved. This scheme uses interpolation algorithms to accurately restore the true spatial position corresponding to the detection point time, improving the time alignment accuracy from the "sampling interval level" to the "interpolation function continuous approximation level," significantly reducing the target position estimation error introduced by time misalignment. This refined time alignment processing allows the instantaneous position error and instantaneous velocity error calculated subsequently to more purely reflect the detection deviation of the tested low-altitude target monitoring equipment itself, rather than the time synchronization residual in the data acquisition stage, thereby further improving the scientific validity and confidence of the performance test results.

[0069] In some embodiments, combined with Figure 3As shown, time alignment of target detection track data and real track data includes the following steps: The S301 carries a cooperative beacon on its flight platform that is synchronized with the clock of a high-precision positioning device.

[0070] S302 transmits the data packet containing timestamp information received by the cooperative beacon and generated by the high-precision positioning device to the external timing input terminal of the low-altitude target monitoring device under test, so as to force synchronization of the internal clock of the low-altitude target monitoring device under test.

[0071] In practical applications, the flight platform used as the test target, in addition to integrating high-precision positioning equipment, also carries a cooperative beacon. This cooperative beacon is connected to the high-precision positioning equipment via a hardwired connection or a high-precision clock synchronization bus, sharing the same clock source. This ensures that the time information acquired by the cooperative beacon is strictly synchronized with the timestamp of the high-precision positioning equipment. During the test flight, while outputting real flight track data, the high-precision positioning equipment continuously generates timing data packets containing Coordinated Universal Time (UTC) absolute time information (i.e., data packets containing timestamp information). These timing data packets include at least the integer second corresponding to the second pulse edge and the nanosecond offset within that second. After receiving this timing data packet, the cooperative beacon forwards it in real time to the external timing input port of the low-altitude target monitoring equipment under test via a physical cable (such as a serial communication line, Ethernet cable, or dedicated timing cable). Upon receiving the timing data packet, the low-altitude target monitoring equipment under test parses the UTC time information contained within it and uses this as a standard to forcibly update the count value of its internal clock register, ensuring that the timing start and frequency of the equipment's internal clock are strictly synchronized with the clock of the high-precision positioning equipment. Subsequently, the timestamp attached to each target detection track data output by the low-altitude target monitoring equipment is the absolute UTC time after hardware synchronization calibration, which is under the same time base framework as the timestamp of the real track data output by the high-precision positioning equipment.

[0072] By adding a cooperative beacon synchronized with the clock of the high-precision positioning equipment on the flight platform, and injecting the timing data packet containing absolute time information into the external timing input terminal of the low-altitude target monitoring equipment under test via a physical cable, hardware-level forced time synchronization between two independent data acquisition systems is achieved. This fundamentally eliminates the time asynchrony problem caused by different internal clock sources, timing start deviation, and timing frequency drift between the two devices, improving the time synchronization accuracy from the millisecond level or even the software interpolation approximation error level to the nanosecond level.

[0073] In some embodiments, combined with Figure 4 As shown, spatial alignment of target detection track data and actual track data includes the following steps: S401, acquire the first position data output by the high-precision positioning device, located in the first spatial coordinate system, and the second position data detected by the low-altitude target monitoring device, located in the second spatial coordinate system.

[0074] Here, the first spatial coordinate system refers to the coordinate reference frame used when the high-precision positioning equipment outputs position data, such as the geocentric coordinate system or the geodetic coordinate system; the second spatial coordinate system refers to the coordinate reference frame used when the low-altitude target monitoring equipment detects the target and outputs position data, such as the station-centered polar coordinate system with the rotation center of the equipment antenna as the origin, or the radar spherical coordinate system with the normal of the equipment antenna array as the reference.

[0075] In practical applications, first position data is extracted from the output data stream of the high-precision positioning device. This first position data is located in a first spatial coordinate system, such as three-dimensional rectangular coordinates in a geocentric coordinate system or latitude, longitude, and elevation values ​​in a geodetic coordinate system. Simultaneously, second position data is extracted from the output data stream of the low-altitude target monitoring device. This second position data is located in a second spatial coordinate system, such as slant range, azimuth, and elevation angle measurements with the device's antenna rotation center as the origin.

[0076] S402, with the antenna phase center of the low-altitude target monitoring equipment being measured as the origin, a station-centered rectangular coordinate system is constructed.

[0077] The station-centered rectangular coordinate system refers to a local spatial rectangular coordinate system constructed with the antenna phase center of the low-altitude target monitoring equipment as the origin. The three coordinate axes of the station-centered rectangular coordinate system are defined as follows: the X-axis points due east, the Y-axis points due north, and the Z-axis is perpendicular to the XY plane and points towards the zenith, forming an east-north-sky right-handed rectangular coordinate system.

[0078] S403, based on the predetermined coordinate transformation relationship between the first spatial coordinate system, the second spatial coordinate system and the station center rectangular coordinate system, the first position data and the second position data are uniformly transformed to the station center rectangular coordinate system.

[0079] In practical applications, a first set of transformation parameters from the first spatial coordinate system to the station-centered rectangular coordinate system, and a second set of transformation parameters from the second spatial coordinate system to the station-centered rectangular coordinate system, are invoked. The first set of transformation parameters includes the components of the baseline vector between the phase center of the high-precision positioning equipment antenna and the phase center of the low-altitude target monitoring equipment antenna in the geocentric coordinate system, as well as the rotation matrix from geodetic coordinates to station-centered rectangular coordinates. The second set of transformation parameters includes the translation vector and attitude rotation matrix from the internal measurement coordinate system of the low-altitude target monitoring equipment to the antenna phase center coordinate system. By applying these transformation parameters, the first and second position data are uniformly transformed to the same station-centered rectangular coordinate system, resulting in first and second position rectangular coordinates expressed in the same spatial reference, thus completing spatial alignment.

[0080] By acquiring first and second position data in different spatial coordinate systems, and constructing a unified station-centered rectangular coordinate system with the antenna phase center of the low-altitude target monitoring equipment as the origin, and then transforming the two heterogeneous position data to the same spatial reference based on a pre-calibrated coordinate transformation relationship, the problem of geometric projection deviation and inconsistency with the spatial reference caused by the use of different coordinate system origins, different coordinate axis directions, and different coordinate expression forms by the high-precision positioning equipment and the low-altitude target monitoring equipment is systematically eliminated. Spatial alignment processing ensures that each pair of data points used for comparison is expressed with the same reference point and the same axis definition as the reference in the spatial dimension. This allows the instantaneous position error calculated subsequently to truly reflect the inherent detection deviation of the monitoring equipment in target spatial positioning, thereby significantly improving the accuracy and spatial comparability of the performance evaluation results of the low-altitude target monitoring equipment.

[0081] In some embodiments, the testing method for the performance of low-altitude target monitoring equipment further includes: generating a traceable test report to establish a correlation link between the detection error and a traceable metrological benchmark; wherein the traceable test report includes one or more of the following: an error statistics item, used to record the detection error of the target detection trajectory data calculated based on the spatiotemporal alignment benchmark relative to the real trajectory data; a traceability correlation item, used to store the metrological calibration certificate number of the high-precision positioning equipment; and a reproduction support item, used to save environmental parameter recording files during the test process and an electronic flight path diagram that overlays and displays the target detection trajectory data and the real trajectory data.

[0082] In practical applications, error statistics are generated as follows: After completing spatiotemporal alignment and detection error calculation, the test device acquires the statistical result dataset for this test. The statistical result dataset includes one or more of the following: root mean square error of detection position, root mean square error of detection velocity, arithmetic mean error of detection position, arithmetic mean error of detection velocity, standard deviation of detection position, standard deviation of detection velocity, maximum error of detection position, and maximum error of detection velocity. The statistical result dataset is written into the error statistics field of a traceable test report file in a structured data format (such as JSON, XML, or key-value text). Each error data is accompanied by a corresponding unit of measurement and error type identifier.

[0083] In practical applications, traceability association items are generated as follows: The testing device reads the metrology calibration certificate number of the high-precision positioning device, which is pre-stored in the system configuration file or entered by the user through the interactive interface. The metrology calibration certificate number is a unique identification code issued by a legally qualified metrology technical institution (e.g., "National Measurement and Control Certificate No. XXXX-YYYY" or "JL2024-XXXX"). The metrology calibration certificate number is written as string data into the traceability association field of the traceable test report file.

[0084] In practical applications, the reproduction support items are generated as follows: The testing device acquires the environmental parameter recording file for this test, which includes one or more of the following environmental parameters during the test period: average wind speed, maximum instantaneous wind speed, temperature, air pressure, and electromagnetic background noise level, and records and stores them in time series form; The testing device overlays and renders the spatiotemporally aligned target detection track data and the real track data on the same three-dimensional or two-dimensional electronic map to generate a spatial comparison visualization track layer and an electronic flight path map file, in which the target detection track and the real track are distinguished by different colors or line types in the layer, and significant deviation points are marked; The environmental parameter recording file and the electronic flight path map file are embedded as attachments in the traceable test report, or stored as independent files and their storage path and file hash value are recorded in the report.

[0085] The testing device assembles the aforementioned error statistics, traceability items, and reproduction support items according to a preset report template, generating a single electronic test report file in both machine-readable and human-readable formats (e.g., a PDF-formatted visual report and a JSON-formatted structured data report coexist). The electronic test report file also includes a report generation timestamp, a unique test task identifier, and the testing device software version number to ensure the report's integrity and traceability.

[0086] Combination Figure 5 As shown, the test method for the performance of low-altitude target monitoring equipment includes the following steps: S501 controls the flight platform, which is the test target, to fly along a preset route within the monitored airspace of the low-altitude target monitoring equipment.

[0087] S502 acquires target detection trajectory data collected by the low-altitude target monitoring equipment during flight on the flight platform along a preset route, and simultaneously acquires the real trajectory data output by the high-precision positioning equipment; wherein, the high-precision positioning equipment is integrated into the flight platform.

[0088] S503 performs spatiotemporal alignment between target detection track data and actual track data.

[0089] S504, under the spatiotemporal alignment reference, determines the detection error of the target detection track data relative to the actual track data.

[0090] S505 generates a traceable test report to establish a link between the detection error and the traceable metrological benchmark.

[0091] In this embodiment, a flight platform integrated with a high-precision positioning device is controlled to fly along a preset route within the airspace monitored by the device under test. Simultaneously, it collects target detection trajectory data output by the device under test and real trajectory data output by the high-precision positioning device, traceable to national metrological standards. This fundamentally solves the inherent defects of insufficient accuracy and lack of traceability caused by using ordinary flight control positioning data as a reference in existing technologies. Furthermore, by performing precise time alignment and spatial coordinate system transformation on the two heterogeneous trajectory data sources, systematic comparison biases introduced by time asynchrony and coordinate system differences are eliminated. This ensures that the finally calculated detection position error and detection velocity error can truly and accurately reflect the inherent detection performance of the low-altitude target monitoring device under test. Furthermore, by generating a traceable test report that includes statistical values ​​of detection errors, the metrological calibration certificate number of the high-precision positioning equipment, and test environment parameters, a traceable and verifiable link is established between the test results and the national standard metrological system. This gives the test report legal validity and industry credibility, providing a scientific and reliable technical basis for the performance evaluation, factory acceptance, and on-site access of low-altitude target monitoring equipment.

[0092] Combination Figure 6 As shown, the test method for the performance of low-altitude target monitoring equipment includes the following steps: S601 controls the flight platform, which is the test target, to fly along a preset route within the monitored airspace of the low-altitude target monitoring equipment.

[0093] S602, obtains target detection trajectory data collected by the low-altitude target monitoring equipment during the flight of the flight platform along the preset route, and simultaneously obtains the real trajectory data output by the high-precision positioning equipment; wherein, the high-precision positioning equipment is integrated into the flight platform.

[0094] S603 aligns the target detection track data with the actual track data in time.

[0095] S604 spatially aligns target detection track data with actual track data.

[0096] S605 calculates the instantaneous position error and instantaneous velocity error of each target detection point after spatiotemporal alignment.

[0097] S606 determines the detection error of the target detection trajectory data relative to the actual trajectory data based on the instantaneous position error and instantaneous velocity error.

[0098] S607 generates a traceable test report to establish a link between the detection error and the traceable metrological benchmark.

[0099] In this embodiment, a flight platform integrated with a high-precision positioning device is controlled to fly along a preset route within the airspace monitored by the device under test, simultaneously collecting target detection trajectory data and real trajectory data traceable to national metrological standards. This fundamentally eliminates the inherent defects of insufficient accuracy and lack of traceability caused by using ordinary flight control positioning data as a reference benchmark in existing technologies. Furthermore, by performing time and spatial alignment processing on the two trajectory data separately, the mismatch error and geometric projection deviation problems introduced by the asynchronous time of heterogeneous data and differences in coordinate system definitions are systematically solved, ensuring that subsequent error calculations are based on a unified spatiotemporal benchmark. Then, by calculating the instantaneous position error and instantaneous velocity error of each detection point point by point, and determining the overall detection error based on instantaneous error statistics, a refined quantitative evaluation of the detection performance of the device under test is achieved. Finally, by generating a traceable test report containing the detection error statistics and the metrological calibration certificate number of the high-precision positioning device, a traceable and verifiable link is established between the test results and the national standard metrological system, significantly improving the accuracy, confidence, and legal validity of the performance test results of the low-altitude target monitoring equipment.

[0100] Combination Figure 7 As shown in the figure, this disclosure provides a testing device (e.g., a computer, controller, etc.) 700 for testing the performance of low-altitude target monitoring equipment, including a memory 701, a processor 702, a communication interface 703, and a bus 704. The memory 701, processor 702, and communication interface 703 are interconnected via the bus 704.

[0101] The memory 701 can be a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM).

[0102] The memory 701 can store a program. When the program stored in the memory 701 is executed by the processor 702, the processor 702 and the communication interface 703 are used to execute the various steps of the test method for the performance of the low-altitude target monitoring device according to the embodiments of this application.

[0103] Processor 702 is a circuit with signal processing capabilities. In one implementation, processor 702 can be a circuit with instruction read and execute capabilities, such as a central processing unit (CPU), microprocessor, graphics processing unit (GPU) (which can be understood as a type of microprocessor), or digital signal processor (DSP). In another implementation, processor 702 can implement certain functions through the logical relationships of hardware circuits. These logical relationships of hardware circuits are fixed or reconfigurable. For example, processor 702 can be a hardware circuit implemented as an ASIC or a programmable logic device (PLD), such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration document and configuring the hardware circuit can be understood as the process of the processor loading instructions to implement the functions of some or all of the above modules. Furthermore, it can also be a hardware circuit designed for artificial intelligence, which can be understood as a type of ASIC, such as a neural network processing unit (NPU), tensor processing unit (TPU), or deep learning processing unit (DPU). The processor 702 is used to execute related programs to implement the functions required by the units in the test apparatus for the performance of low-altitude target monitoring equipment according to the embodiments of this application, or to execute the test method for the performance of low-altitude target monitoring equipment according to the method embodiments of this application.

[0104] As can be seen, each module in the above device can be one or more processors (or processing circuits) configured to implement the above methods, such as: CPU, GPU, NPU, TPU, DPU, microprocessor, DSP, ASIC, FPGA, or a combination of at least two of these processor types.

[0105] Furthermore, the modules in the above devices can be integrated in whole or in part, or they can be implemented independently. In one implementation, these modules are integrated together as a system-on-a-chip (SOC). The SOC may include at least one processor for implementing any of the above methods or for implementing the functions of the modules of the device. The at least one processor may be of different types, such as CPU and FPGA, CPU and artificial intelligence processor, CPU and GPU, etc.

[0106] The communication interface 703 uses a transceiver device, such as, but not limited to, a transceiver, to enable communication between the test device 700 for low-altitude target monitoring equipment performance and other devices or communication networks. For example, data can be acquired through the communication interface 703.

[0107] Bus 704 may include a pathway for transmitting information between various components (e.g., memory 701, processor 702, communication interface 703) of a test apparatus 700 for monitoring the performance of low-altitude target equipment.

[0108] It should be noted that, although Figure 7 The illustrated test apparatus 700 for low-altitude target monitoring equipment performance only shows the memory, processor, and communication interface. However, those skilled in the art should understand that in specific implementations, the test apparatus 700 may also include other components necessary for normal operation. Furthermore, depending on specific needs, those skilled in the art should understand that the test apparatus 700 may also include hardware components for implementing other additional functions. Moreover, those skilled in the art should understand that the test apparatus 700 may only include the components necessary for implementing the embodiments of this application, and may not necessarily include... Figure 7 All the devices shown.

[0109] This application also provides a computer-readable storage medium storing instructions that, when executed on a computer or processor, cause the computer or processor to perform one or more steps of any of the above methods.

[0110] This application also provides a computer program product containing instructions. When the computer program product is run on a computer or processor, it causes the computer or processor to perform one or more steps of any of the methods described above.

[0111] The aforementioned computer-readable storage medium may be a transient computer-readable storage medium or a non-transitory computer-readable storage medium.

[0112] The technical solutions of this disclosure can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes one or more instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in this disclosure. The aforementioned storage medium can be a non-transitory storage medium, including: a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and other media capable of storing program code; it can also be a transient storage medium.

[0113] The foregoing description and accompanying drawings fully illustrate embodiments of the present disclosure to enable those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, procedural, and other changes. The embodiments represent only possible variations. Individual components and functions are optional unless explicitly required, and the order of operation may vary. Parts and features of some embodiments may be included or substituted for parts and features of other embodiments. The scope of the embodiments of this disclosure includes the entire scope of the claims and all available equivalents of the claims. While the terms “first,” “second,” etc., may be used in this application to describe elements, these elements should not be limited by these terms. These terms are used only to distinguish one element from another. For example, a first element may be called a second element without changing the meaning of the description, and similarly, a second element may be called a first element, provided that all occurrences of “first element” are consistently renamed and all occurrences of “second element” are consistently renamed. First and second elements are both elements, but may not be the same element. Moreover, the terminology used in this application is only for describing embodiments and is not intended to limit the claims. As used in the description of the embodiments and claims, unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “the” are intended to also include the plural forms. Similarly, the term “and / or” as used herein means including one or more of the associated listed any and all possible combinations. Additionally, when used herein, the terms “comprise” and its variations “comprises” and / or “comprising” refer to the presence of stated features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof. Without further limitations, an element defined by the phrase “comprising an…” does not exclude the presence of additional identical elements in the process, method, or apparatus that includes said element. In this document, each embodiment may focus on the differences from other embodiments, and similar or identical parts between embodiments can be referred to mutually. For methods, products, etc., disclosed in the embodiments, if they correspond to the method section disclosed in the embodiments, the relevant parts can be referred to the description of the method section.

[0114] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the embodiments of this disclosure. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0115] The methods and products disclosed in the embodiments herein (including but not limited to devices and equipment) can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units may be merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to implement this embodiment according to actual needs. In addition, the functional units in the embodiments of this disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0116] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

Claims

1. A test method for the performance of low-altitude target monitoring equipment, characterized in that, include: Control the flight platform, which is the test target, to fly along a preset route within the airspace monitored by the low-altitude target monitoring equipment under test; The system acquires target detection trajectory data collected by the low-altitude target monitoring equipment during flight on the flight platform along a preset route, and simultaneously acquires the real trajectory data output by the high-precision positioning equipment; the high-precision positioning equipment is integrated into the flight platform. Spatiotemporal alignment of target detection trajectory data and real trajectory data; Under the spatiotemporal alignment reference, determine the detection error of the target detection trajectory data relative to the actual trajectory data.

2. The test method according to claim 1, characterized in that, Spatiotemporal alignment of target detection track data and real track data, including: Time-align the target detection track data and the actual track data; and / or, Spatial alignment is performed between target detection track data and actual track data.

3. The test method according to claim 2, characterized in that, Time alignment of target detection track data and actual track data includes: After converting both the actual trajectory data and the target detection trajectory data to Coordinated Universal Time (UTC), the high-sampling-rate actual trajectory data is interpolated to the precise time corresponding to each detection point in the target detection trajectory data; or, The flight platform carries a cooperative beacon synchronized with the clock of a high-precision positioning device; The data packets containing timestamp information received by the cooperative beacon and generated by the high-precision positioning device are transmitted to the external timing input terminal of the low-altitude target monitoring device under test, so as to force synchronization of the internal clock of the low-altitude target monitoring device under test.

4. The test method according to claim 3, characterized in that, The high-sampling-rate real track data is interpolated to calculate the precise time corresponding to each detection point in the target detection track data, including: Determine the high-sampling-rate real trajectory data sequence of the high-precision positioning equipment and the low-sampling-rate detection point time sequence of the low-altitude target monitoring equipment under test; For the target detection point time in the low sampling rate detection point time sequence, multiple real sampling points of high-precision positioning devices are selected as interpolation nodes in the neighborhood before and after the target detection point time. Based on the selected interpolation nodes and their corresponding position data, the target interpolation position data corresponding to the target detection point time is calculated, and the target interpolation position data is used as the real track data after being time-aligned with the target detection track data.

5. The test method according to claim 2, characterized in that, Spatial alignment of target detection track data and actual track data includes: Acquire the first position data output by the high-precision positioning device, located in the first spatial coordinate system, and the second position data detected by the low-altitude target monitoring device, located in the second spatial coordinate system; A station-centered rectangular coordinate system is constructed with the antenna phase center of the low-altitude target monitoring equipment as the origin. Based on the predetermined coordinate transformation relationship between the first spatial coordinate system, the second spatial coordinate system and the station center rectangular coordinate system, the first position data and the second position data are uniformly transformed to the station center rectangular coordinate system.

6. The test method according to claim 1, characterized in that, Controlling the flight platform, which is the test target, to fly along a preset route within the monitored airspace of the low-altitude target monitoring equipment, including controlling the flight platform to fly in one or more preset flight modes: Uniform linear flight mode is used to test the speed measurement accuracy of the low-altitude target monitoring equipment under test on a stable flight path; Uniform circular flight mode is used to test the tracking stability of the low-altitude target monitoring equipment under test during continuous large-angle maneuvers. Different altitude-layered flight modes are used to test the detection altitude accuracy of the low-altitude target monitoring equipment under test at different elevation angles and altitude layers; The variable acceleration maneuver flight mode is used to test the transient response capability of the low-altitude target monitoring equipment under sudden high dynamic motion.

7. The test method according to claim 1, characterized in that, Under the spatiotemporal alignment reference, determine the detection error of the target detection trajectory data relative to the true trajectory data, including: Calculate the instantaneous position error and instantaneous velocity error of each target detection point after spatiotemporal alignment; The detection error of the target detection trajectory data relative to the actual trajectory data is determined based on the instantaneous position error and instantaneous velocity error.

8. The test method according to any one of claims 1 to 7, characterized in that, Also includes: Generate a traceable test report to establish a link between the detection error and the traceable metrological benchmark; wherein the traceable test report includes one or more of the following: Error statistics are used to record the detection error of the target detection trajectory data calculated based on the spatiotemporal alignment reference relative to the actual trajectory data. The traceability entry is used to store the metrology and calibration certificate number of the high-precision positioning equipment. The reproduction support item is used to save environmental parameter records during the test process and to overlay electronic flight path charts that display target detection trajectory data and real trajectory data.

9. A testing device for the performance of low-altitude target monitoring equipment, characterized in that, include: A processor, a memory, and a computer program stored in the memory, wherein the processor, when executing the computer program, implements the test method for the performance of a low-altitude target monitoring device as described in any one of claims 1 to 8.

10. A testing system for the performance of low-altitude target monitoring equipment, characterized in that, include: The flight platform is configured to fly along a preset route within the monitored airspace of the low-altitude target monitoring equipment. High-precision positioning equipment is integrated into the flight platform and is configured to collect real flight track data during flight of the flight platform along a preset route. The low-altitude target monitoring equipment is configured to collect target detection trajectory data during flight of the flight platform along a preset route; The testing apparatus for the performance of low-altitude target monitoring equipment as described in claim 9.

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