A method for collecting electromagnetic characteristic data of a large scene target

Abstract

The application provides a large-scene target electromagnetic characteristic data acquisition implementation method, comprising the following steps: arranging a plurality of first calibration bodies in a test area, and measuring the electromagnetic characteristics of the test area by an airborne SAR; arranging a plurality of second calibration bodies in the test area, and measuring the electromagnetic characteristics of the test area by a spaceborne SAR; and recording and processing the test data. The application constructs a complete set of test methods for full-size ships and port targets, overcomes the defects of small size of the scale model and poor measurement accuracy, and the measurement wave band can cover X, Ku and Ka wave bands. The large-scene target electromagnetic characteristic data can be obtained by using the method, the satellite measurement data is compared with the airborne test data, the modeling accuracy of the scene electromagnetic data and the data production effectiveness are fully verified, and support is provided for accurately constructing large-scene electromagnetic target characteristic data.

Description

Technical Field

[0001] This invention belongs to the technical field of electromagnetic scattering test research on surface ship targets, specifically involving a method for acquiring electromagnetic characteristic data of large-scale targets. Background Technology

[0002] Current domestic research on electromagnetic scattering testing of surface ships mainly focuses on scaled-down measurements to verify theoretical models. Airborne methods are used to acquire the scattering characteristics of civilian ships and some military vessels. No research has been found that covers combined scenarios involving important port facilities and moored ships. The scaled-down tests involve relatively small-sized ships, limiting the estimation of radar scattering data for full-size targets in the P and L bands.

[0003] Currently, China has established a wave pool-based marine environment simulation test site. The initial wave pool size was 40m×30m×5m, capable of simulating a one-dimensional dynamic sea surface with regular waves and PM / JP spectra, with sea conditions ranging from 1 to 3 and a maximum wave height of 0.8m. At the end of 2015, a new wave pool with dimensions of 100m×60m×8m was constructed. This new wave pool can simulate a two-dimensional dynamic sea surface with regular waves and PM / JP spectra, with sea conditions ranging from 1 to 3 and a maximum wave height of 1.25m. It can be used for dynamic and static measurement studies of ultra-low-altitude targets and surface targets. The experimental system and methods are the first of their kind in China.

[0004] A scaled-down model of the sea surface was constructed using non-metallic composite materials to simulate high-sea-state marine environments. Scaled-down measurements of the composite electromagnetic scattering characteristics of ships at sea surface in microwave, 3mm, and submillimeter-wave bands were achieved. The coupling scattering mechanism between the sea surface and the target, and its impact on the target's RCS and scattering images, were analyzed. Simultaneously, composite downward-looking scattering imaging measurements of ships and targets were also conducted in a wave pool, reaching the submillimeter-wave band. However, the largest scaled-down model size for the submillimeter-wave band tests was 2.2m, and the largest ship size for the microwave band tests was 4m, primarily used for theoretical model verification.

[0005] Existing technologies lack methods for acquiring and verifying electromagnetic property data of large-scale targets. Current testing methods mainly suffer from three problems:

[0006] (1) The scaled-down test ship is small in size, and can only extrapolate the radar scattering data of full-size targets in the P and L bands;

[0007] (2) The research frequency band reaches the submillimeter wave band, but the maximum size of the ship scale model tested in the submillimeter wave band is 2.2m, and the maximum size of the ship tested in the microwave wave band is 4m. It is mainly used for theoretical model verification research.

[0008] (3) Electromagnetic property data of large scene targets are generally tested by satellite, but satellites cannot obtain electromagnetic data of scaled-down models, and there is a lack of verification between the two. Summary of the Invention

[0009] To address the problems existing in the prior art, this application proposes a method for acquiring electromagnetic property data of large-scale targets, comprising the following steps:

[0010] Several first calibration bodies were deployed in the test area, and the electromagnetic characteristics of the test area were measured by airborne SAR.

[0011] Several second calibration bodies were deployed in the test area, and the electromagnetic characteristics of the test area were measured by spaceborne SAR.

[0012] Data acquisition and processing of experimental data.

[0013] Furthermore, the first calibration body is a Luneburg sphere, and the second calibration body is a trihedral reflector.

[0014] Furthermore, the electromagnetic characteristic measurement of large-scale targets using airborne SAR includes:

[0015] Straight-line flight path test: Acquire SAR imaging data of the entire large scene target;

[0016] The circumferential flight path test acquires SAR imaging data of important targets within a large scene.

[0017] Furthermore, the acquisition and processing of experimental data specifically includes the following steps:

[0018] Data validity verification involves verifying the validity and completeness of various types of data collected during and after the experiment, and supplementing missing experimental data as necessary.

[0019] Data classification and backup: While verifying the validity of the data, the test data is classified and backed up. Various types of characteristic data are stored in folders and backups are set up.

[0020] Data processing involves using the measured calibration constants to perform amplitude calibration on the SAR image of the area under test, thereby obtaining the scattering intensity image of the area under test.

[0021] Test error analysis is performed to analyze the uncertainty of airborne SAR imaging test data.

[0022] Furthermore, the uncertainties in airborne SAR imaging test data include:

[0023] Average irradiance refers to the average irradiance between the target being measured and the calibration body;

[0024] Background-target interaction refers to the rescattering of the scattered field from the target by other structures in the background;

[0025] Cross-polarization refers to the error caused by the polarization purity of the antenna itself, the cross-polarization response of the target, etc.

[0026] Energy drift refers to the change in the amplitude or phase of a received signal over time.

[0027] Frequency drift is negligible because the stability of a normal frequency is above 10⁻⁶.

[0028] Signal accumulation is the error caused by the target motion during the test.

[0029] IQ imbalance refers to the imbalance in amplitude and phase of the receiving system's response to the input test signal;

[0030] Noise background refers to all measurement system noise, which is usually estimated by directly measuring the system noise without placing any target or support.

[0031] Nonlinearity is mainly related to the receiving system, such as the receiver and mixer in the measurement system, and reflects the nonlinearity index of the receiving system's response.

[0032] Distance accuracy refers to the error generated during the distance measurement process between the transmitting and receiving antennas and the target under test;

[0033] Target orientation refers to the error in the target's azimuth measurement;

[0034] Calibration error refers to the combined uncertainty related to the measurement of the calibration body.

[0035] Furthermore, airborne SAR imaging includes:

[0036] Imaging processing involves estimating and compensating the platform's motion parameters through inertial navigation system motion parameter recording and estimation methods, thereby achieving high-precision focused imaging of the target and acquiring a two-dimensional high-resolution scattering distribution image.

[0037] Amplitude calibration is performed on airborne SAR echo data using an integral calibration method that averages multiple targets.

[0038] The uncertainty of airborne SAR imaging test data is analyzed.

[0039] Furthermore, the specific processing steps for amplitude calibration are as follows:

[0040] SAR imaging processing is performed on the echo test data of multiple calibration bodies to obtain two-dimensional SAR images of each calibration body.

[0041] In the above SAR images, the maximum impulse response region of each calibration body is used as a reference to divide and obtain the corresponding scattering region of each calibration body;

[0042] The scattering region of each calibration body is integrated using the integral method to obtain the target energy of the corresponding calibration body. The calibration constant corresponding to the calibration body is obtained by comparing it with the theoretical value of the calibration body under the same condition.

[0043] The calibration constants of each calibration body are averaged according to the above method to obtain the final calibration constants.

[0044] By using the calibration constants obtained from the measurements to calibrate the amplitude of the SAR image of the area under test, the scattering image of the area under test can be obtained.

[0045] Furthermore, the electromagnetic property calibration of large-scale targets includes:

[0046] The calibration constants are obtained, and the relationship between the gray value of the SAR image and the absolute radar scattering is obtained by observing the calibration body with a known radar cross section.

[0047] Acquire a scattering image of the area to be measured, and use the measured calibration constant to perform amplitude calibration on the SAR image of the area to be measured.

[0048] To acquire RCS data for key areas or targets of interest, RCS reconstruction technology is employed.

[0049] Furthermore, the logarithm of the mean of the calibration constants estimated from multiple point targets is used as the final calibration constant K, specifically calculated using the following formula:

[0050]

[0051] Where: K i The calibration constant is estimated from the i-th point target, where N is the number of point targets in the calibration field; θ is the incident angle; σ p ε is the theoretical value of the radar cross section of a point target; p The energy of the point target impulse response extracted from SAR data;

[0052]

[0053] Among them: I i Let N be the pixel value of the i-th pixel; the number of pixels in the energy integration region of the point target is N. A The background area corresponds to N pixels. B .

[0054] Compared with the prior art, the advantages of this invention are as follows:

[0055] The proposed method for acquiring electromagnetic characteristic data of large-scale targets establishes a complete testing approach for full-size ships and port targets. It overcomes the shortcomings of small-scale model size and poor measurement accuracy, and the measurement bands can cover X, Ku, and Ka bands. Using this method, electromagnetic characteristic data of large-scale targets can be obtained. By comparing satellite measurement data with airborne test data, the accuracy of scene electromagnetic data modeling and the effectiveness of data production can be fully verified, providing support for the accurate construction of electromagnetic target characteristic data in large-scale scenes. Attached Figure Description

[0056] Figure 1 This is a distribution map of important targets within the port according to an embodiment of the present invention;

[0057] Figure 2 This is a schematic diagram of the SAR imaging flight path for a port scene according to an embodiment of the present invention;

[0058] Figure 3 This is a division of important target regions in embodiments of the present invention;

[0059] Figure 4 This is a flowchart of the multi-point target average integral radiometric calibration method according to an embodiment of the present invention;

[0060] Figure 5 This is a schematic diagram of the point target integration region according to an embodiment of the present invention;

[0061] Figure 6 This is a schematic diagram of the structure of the corner reflector calibration body according to an embodiment of the present invention;

[0062] Figure 7 This is a schematic diagram of the RCS simulation results of the corner reflector in the pitch direction according to an embodiment of the present invention;

[0063] Figure 8 This is a schematic diagram of the RCS simulation results of the azimuth direction of the corner reflector in an embodiment of the present invention;

[0064] Figure 9 This is a schematic diagram showing the arrangement of multiple sets of corner reflectors according to an embodiment of the present invention;

[0065] Figure 10 This is a schematic diagram comparing the theory and test results of the Luneburg ball in an embodiment of the present invention;

[0066] Figure 11 This is a schematic diagram comparing the theoretical and test results of the corner reflector in an embodiment of the present invention;

[0067] Figure 12 This is a flowchart of an airborne SAR flight test according to an embodiment of the present invention;

[0068] Figure 13 This is a schematic diagram showing the placement of the corner reflector during spaceborne testing in an embodiment of the present invention;

[0069] Figure 14 This is a flowchart of SAR imaging according to an embodiment of the present invention. Detailed Implementation

[0070] To enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0071] The measurement equipment required for the implementation method of electromagnetic characteristic data acquisition of large-scale target (port) in this invention includes: a real-world reconnaissance satellite, a Ka-band SAR imaging radar, a Ka-band radar carrier aircraft, a Ku-band SAR imaging radar, a Ku-band radar carrier aircraft, an inertial navigation system, a power supply and conversion device, a GPS antenna, corner reflectors of different types and sizes, and a Luneburg sphere (as a calibration body).

[0072] The actual test area was a rectangular area 6.4 km long and 2.2 km wide, covering the east and west port areas of Longyan Port. The schematic diagram of the test area division is as follows, with the latitude and longitude coordinates as follows:

[0073] Top left: 37°25'39.4"N 122°37'44.9"E

[0074] Top right: 37°25'39.4"N 122°40'46.5"E

[0075] Bottom right: 37°24'26.7"N 122°40'46.5"E

[0076] Bottom left: 37°24'26.7"N 122°37'44.9"E

[0077] like Figure 1 The test subject is a port scene within the test area, including important targets within the port (including ship M4, wharf M5, dock M6, oil depot M1, warehouse M2, and office building M3).

[0078] The approximate distribution of the test targets within the port is shown in the above figure, and the list of names and codes of the tested targets is shown in Table 1.

[0079] Table 1. Names and codes of the targets being tested

[0080]

[0081] 1. Test Methods

[0082] (1) Airborne testing:

[0083] 1) Straight route test

[0084] Straight-line flight path tests were conducted on the entire port scenario to acquire its SAR imaging data, and the aircraft flight path was designed as follows: Figure 2As shown.

[0085] After takeoff, the helicopter reached the pre-designated starting shooting location A (the straight flight path AB is 1.26 km below the test area), maintained an altitude of 0.7 km, and flew at a speed of 120 km / h in a straight line to begin SAR data acquisition. The AB segment of the flight path corresponds to imaging area 1. After reaching point B (a flight distance of 6.4 km), the helicopter turned and flew 6.52 km along BC to point C. From point C, it continued flying in a straight line to point D (a flight distance of 6.4 km). The CD segment of the flight path corresponds to imaging area 2. Afterward, it flew 6.52 km along the DE direction to point E, and finally flew 6.4 km along the EF segment. The EF segment of the flight path corresponds to imaging area 3, completing the SAR measurement covering the entire port scene.

[0086] 2) Circumferential route test

[0087] Reference Figure 3 The circumferential route test, considering the distribution of important targets within the port area, proposes dividing the test area into three sub-regions: Sub-region 1 mainly includes important targets such as oil depots and office buildings; Sub-region 2 mainly includes important targets such as warehouses, wharves, and ships; and Sub-region 3 mainly includes important targets such as docks. SAR imaging data will be collected from various azimuths within each sub-region.

[0088] To verify the accuracy of the coupled modeling of ship targets and ports, SAR data with and without ships were collected for sub-region 2 containing the dock in the figure below, under the same conditions (frequency band, incident angle, azimuth angle).

[0089] 3) Calibration method

[0090] This scheme proposes to use the integral calibration method of multi-point target averaging to calibrate the amplitude of airborne SAR echo data. The specific calibration process is as follows: Figure 4 As shown, the relationship between the gray value of the SAR image and the absolute radar scattering is obtained by observing the calibration body with a known radar cross section, that is, the calibration constant is obtained; then, the amplitude of the SAR image of the area to be measured is calibrated using the measured calibration constant, and the scattering image of the area to be measured can be obtained; by using RCS reconstruction technology, the RCS data of the key area of ​​interest or target can be further obtained.

[0091] SAR absolute calibration mainly involves estimating the calibration constant k. In practice, the logarithm of the mean of the calibration constants estimated from multiple point targets is usually used as the final calibration constant.

[0092]

[0093] In the formula, K i The calibration constant is estimated from the i-th point target, where N is the number of point targets in the calibration field; θ is the incident angle; σp ε is the theoretical value of the radar cross section of a point target; p The energy of the point target impulse response is extracted from SAR data.

[0094] The integral method mainly obtains the energy of a point target by integrating the impulse response of the point target over a specific region. That is, the total echo power of the area where the point target is placed on the image minus the total power of the reference background area of ​​the same area.

[0095]

[0096] In the formula: I i Let be the pixel value of the i-th pixel; for example... Figure 5 As shown, the red area is the energy integration region for the point target, with N pixels. A The purple area represents the background area, corresponding to N pixels. B .

[0097] When performing SAR radiometric calibration on point targets, if the signal-to-clutter ratio (SCR) of the point target is greater than 20 dB, the impact of background noise on the calibration results is less than 0.5 dB. This invention employs a trihedral reflector as shown in the figure, where each face is an isosceles right triangle with a leg length of 0.8 m. Figure 6 As shown. Its RCS simulation results are as follows. Figure 7 and Figure 8 As shown, within the incident angle range of 60°–75° and the azimuth angle range of 20°–70°, the backscattering coefficient of concrete surfaces and grass is less than 0dB, and the RCS of a single pixel (calculated based on a pixel area of ​​3m*3m) is less than 10dB. The SCR of the trihedral calibration surface is greater than 20dB in both grass and concrete pavement environments, exceeding the 20dB background noise requirement and meeting the SCR visibility requirements.

[0098] To achieve accurate calibration within the dynamic range of scattering in the port scene, seven sets of RCS calibration bodies of different sizes were used (specific calibration equipment parameters are shown in Table 2). Considering the control errors of the flight test angle and angular reversal placement, each set of angular reversals included 3-4 bodies (with an azimuth deviation of 7 degrees, such as...). Figure 9 (As shown).

[0099] Table 2 Calibration Equipment Parameters

[0100] name Dimensions Theoretical RCS (15.2GHz) Remark Corner Reversal No. 1 100cm (length of the right-angled side) 40.3 dBsm (maximum value) A group of 4 Corner Reversal No. 2 30cm (length of the right-angled side) 19.4 dBsm (maximum value) Group of 3 Corner Reversal No. 3 25cm (length of the right-angled side) 16.2 dBsm (maximum value) Group of 3 Corner Reversal No. 4 15cm (length of the right-angled side) 12.4 dBsm (maximum value) Group of 3 Longbo Ball No. 1 25cm (diameter) 5.9dBsm Longbo Ball No. 2 15cm (diameter) -2.9dBsm Longbo Ball No. 3 10cm (diameter) -9.9dBsm

[0101] The relationship between the RCS and different sizes of Luneburg spheres and corner reflectors after calibration is as follows: Figure 10 and Figure 11As shown in the figure, the blue theoretical curve is a line graph showing the relationship between the RCS and size of the calibration body, while the red curve is a line graph showing the measured curve. It can be seen that the two trends are consistent; except for the smallest Luneburg sphere, the theoretical and measured errors for other calibration bodies are within 2 dB.

[0102] The entire experimental process is as follows Figure 12 As shown: After the test equipment arrives at the site, the first step is to unload and inspect the exterior of each piece of equipment; conduct ground-based debugging of the SAR radar to ensure that the system is working properly; if the system is working properly, harden the SAR radar onto the aircraft and perform simple functional verification by powering it on; if the status is confirmed to be correct, conduct an in-flight test.

[0103] (2) Onboard testing:

[0104] For port targets, the method in this invention employs a data purchase method to coordinate the acquisition of SAR data of the port scene from TerraSAR-X satellites through live-fire programming. During spaceborne SAR testing, corner reflector calibration bodies are deployed in an open area of ​​the test site, such as... Figure 13 As shown.

[0105] 1) Calibration method

[0106] TerraSAR-X has its own calibration capability, with a radiation stability of ±0.2dB, relative calibration accuracy of <0.3dB, and absolute calibration accuracy of 0.6dB. The RCS of the corner reflector calibration body can be obtained based on the test conditions and TerraSAR-X calibration coefficients, and compared with the theoretical value to confirm the calibration accuracy.

[0107] (3) Data Acquisition and Processing:

[0108] 1) Data validity verification

[0109] Data validity verification mainly refers to verifying the validity and completeness of various types of data collected during and after the test. Port target electromagnetic characteristic data acquisition involves long test durations, numerous operating conditions, and large data volumes. Therefore, after each test, it is necessary to promptly check whether each test item in the test implementation plan is complete, verify the validity of the measurement data, and supplement any missing test data if necessary.

[0110] The test data verification record table is as follows:

[0111] Table 3 Test Data Verification Record Form (Airborne Platform Test)

[0112]

[0113] 2) Data classification and backup

[0114] While verifying the validity of the data, we also categorized and backed up the test data. Various types of characteristic data were stored in folders and backups were configured. The folder naming and file storage rules are as follows:

[0115] Create a new folder (first-level directory) with the test project code as the folder name, and name the subfolders (second-level directories) with the code of the target being tested to store the raw data of electromagnetic characteristics;

[0116] To facilitate data traceability, the original data files or folders are stored using the original filenames recorded by each data acquisition device.

[0117] 3) Data processing

[0118] The method of the present invention obtains the relationship between the gray value of the SAR image and the absolute radar scattering by observing a calibration body with a known radar cross section, that is, obtains the calibration constant; then, the amplitude calibration of the SAR image of the area to be measured is performed using the measured calibration constant to obtain the scattering intensity image of the area to be measured.

[0119] Airborne SAR imaging mainly consists of two parts: SAR imaging and amplitude calibration.

[0120] Image processing

[0121] The method of this invention estimates and compensates the platform's motion parameters by recording and estimating motion parameters using an inertial navigation system, thereby achieving high-precision focused imaging of the target and acquiring a two-dimensional high-resolution scattering distribution image.

[0122] Amplitude calibration

[0123] The method of this invention proposes to use an integral calibration method based on multi-point target averaging to calibrate the amplitude of airborne SAR echo data. The specific processing steps are as follows:

[0124] SAR imaging processing is performed on the echo test data of multiple calibration bodies to obtain two-dimensional SAR images of each calibration body.

[0125] In the above SAR images, the maximum impulse response region of each calibration body is used as a reference to divide and obtain the corresponding scattering region of each calibration body;

[0126] The scattering region of each calibration body is integrated using the integral method to obtain the target energy of the corresponding calibration body. The calibration constant corresponding to the calibration body is obtained by comparing it with the theoretical value of the calibration body under the same condition.

[0127] The calibration constants of each calibration body are averaged according to the above method to obtain the final calibration constants.

[0128] By using the calibration constants obtained from the measurements to calibrate the amplitude of the SAR image of the area under test, the scattering image of the area under test can be obtained.

[0129] 4) Test error analysis

[0130] Based on the relevant standards IEEE 1502-2007 and GJB-3756, the uncertainty of airborne SAR imaging test data is analyzed. When the measurement equipment and test field conditions are fixed, the main factors contributing to measurement uncertainty include average irradiance, background-target interaction, cross-polarization, energy drift, frequency drift, accumulation, IQ imbalance, noise-background, nonlinearity, range accuracy, target pointing, and calibration error.

[0131] Uncertainty is usually expressed as a logarithm, and the formula is:

[0132]

[0133] In the formula: Δσ′ ± σ is the logarithmic representation of the uncertainty; Δσ is the uncertainty; σ0 is the true value.

[0134] After analyzing the main uncertainty components in the flight measurement, it can be assumed that each uncertainty component is independent or approximately independent. The combined uncertainty of the measurement can be obtained using the root sum of squares (RSS) method, and the calculation formula is as follows:

[0135]

[0136] In the formula: Δσ i This represents the uncertainty component.

[0137] Average irradiance

[0138] Average irradiance refers to the uncertainty arising from the difference in average irradiance between the target and the calibration object. Common causes include gain attenuation due to antenna pointing error and gain fluctuations within the antenna beamwidth caused by a significant difference in size between the target and the calibration object. Assume the antenna pattern is cos... 2 If the antenna has a specific shape and an ideal line of sight, then the average irradiance uncertainty caused by the antenna positioning error can be expressed as:

[0139]

[0140] In the formula, θ0 is half of the antenna's 3dB beamwidth, and θ is the maximum positioning error. G / G0 is the gain attenuation factor. The uncertainty of the combined amplitude illumination non-uniformity of the radar transceiver antenna is within 1dB.

[0141] Background - Target Interaction

[0142] Background-target interaction refers to the rescattering of the scattered field from the target by other structures in the background. In the method of this invention, the interaction between the target and the background is mainly scattering from the sea surface background. However, the actual target itself is a composite scattering from the ship and the sea surface, so this effect is not considered.

[0143] Cross-polarization

[0144] Cross-polarization refers to errors arising from the polarization purity of the antenna itself, the cross-polarization response of the target, etc. Theoretically, this error can be corrected using full polarization measurement. When the target under test is a highly depolarized target, the cross-polarization uncertainty component can be expressed as:

[0145]

[0146] In the formula: Δσ′ is the cross-polarization uncertainty component; ε p This refers to the antenna polarization isolation. In practice, the cross-polarization of the antenna used is above 25dB, and compared to other factors, this effect is negligible.

[0147] Energy drift

[0148] Energy drift generally refers to the change in the amplitude or phase of a received signal over time. It is usually defined as a percentage error over a specified time period. During measurement, the drift uncertainty can be obtained by measuring a fixed target over a long period of time. This error needs to be obtained through actual measurement.

[0149] Frequency drift

[0150] The RCS measurement uncertainty caused by frequency drift can be estimated by the following formula:

[0151]

[0152] In the formula, Δf is the effective system bandwidth, and f is the center frequency. Since the stability of a conventional frequency reaches over 10⁻⁶, this effect can be ignored.

[0153] Signal accumulation

[0154] Signal accumulation is due to the error caused by the target's motion during the test. For the measurement of targets such as slow-moving ships or stationary docks, this error can be ignored.

[0155] IQ Imbalance

[0156] IQ imbalance refers to the amplitude and phase imbalance in the receiving system's response to the input test signal. Measurement radars have excellent IQ quadrature characteristics, making this error negligible.

[0157] Noise-background

[0158] Noise-background generally refers to all measurement system noise, and is typically estimated by directly measuring system noise without placing any targets or supports. This error needs to be analyzed based on the actual measurement results.

[0159] Nonlinear

[0160] Nonlinearity is mainly related to the receiving system, such as the receiver and mixer in the measurement system, and reflects the nonlinearity index of the receiving system's response.

[0161] Distance accuracy

[0162] Distance refers to the error generated during the distance measurement process between the transmitting and receiving antennas and the target being measured, and can be estimated using the following formula:

[0163]

[0164] In the formula, ΔR represents the distance error, and R represents the test distance. The radar ranging error is 1m, and the maximum flight altitude is 1km. The resulting RCS measurement error can be expressed as:

[0165] Δσ′=-40log((R±ΔR) / R)

[0166] In the formula, R is the test distance (1400m), ΔR is the distance measurement error (1m), and its magnitude is 0.012dB.

[0167] Target pointing

[0168] Target pointing usually refers to the error in the target's azimuth measurement. This error can generally be reduced by using auxiliary aiming devices such as lasers or by using a certain azimuth angle smoothing method.

[0169] Calibration error

[0170] Calibration error refers to the combined uncertainty related to the measurement of the calibration body. For calibration bodies with theoretical solutions, the error mainly stems from incorrect RCS values ​​or discrepancies between the actual target and the theoretical target. This error can be reduced by improving the machining accuracy of the calibration body, using the multi-point target average integration method, and cross-calibrating calibration bodies with two sets of dimensions. The error can be controlled to approximately 0.7 dB.

[0171] Taking all uncertainties into account, the uncertainty of airborne SAR imaging tests can be controlled within 3dB.

[0172] The final electromagnetic characteristics analysis results for the large-scale port scene are as follows:

[0173] Table 4. Scattering characteristics of main facilities in port scenarios

[0174]

[0175]

[0176] This invention establishes a testing method for measuring the electromagnetic characteristics of large-scale (port) targets using airborne and spaceborne SAR, supporting similar large-scale electromagnetic characteristic testing experiments. It also establishes a calibration method for the electromagnetic characteristics of large-scale (port) targets, primarily by observing a calibration body with a known radar cross-section to obtain the relationship between the grayscale value of the SAR image and the absolute radar scattering, thus obtaining the calibration constant. Then, using the measured calibration constant, the amplitude of the SAR image of the area under test is calibrated to obtain the scattering image of the area under test. Furthermore, RCS reconstruction technology is employed to obtain RCS data for key areas of interest or targets. The uncertainty of airborne SAR imaging test data is analyzed. When the measurement equipment and test site conditions are fixed, the main factors of measurement uncertainty include average amplitude illuminance, background-target interaction, cross-polarization, energy drift, frequency drift, accumulation, IQ imbalance, noise-background, nonlinearity, range accuracy, target pointing, and calibration error. These errors are summarized and analyzed.

[0177] In summary, these are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. All equivalent changes and modifications made in accordance with the scope of the present invention and the contents of the specification are within the scope of the present invention.

Claims

1. A method for acquiring electromagnetic characteristic data of targets in a large scene, characterized in that, Includes the following steps: Several first calibration bodies were deployed in the test area, and the electromagnetic characteristics of the test area were measured by airborne SAR. Several second calibration bodies were deployed in the test area, and the electromagnetic characteristics of the test area were measured by spaceborne SAR. Data acquisition and processing; Electromagnetic property measurement of large-scale targets using airborne SAR includes: Straight-line flight path test: Acquire SAR imaging data of the entire large scene target; The circumferential flight path test acquires SAR imaging data of important targets within a large scene. Airborne SAR imaging includes: Imaging processing involves estimating and compensating the platform's motion parameters through inertial navigation system motion parameter recording and estimation methods, thereby achieving high-precision focused imaging of the target and acquiring a two-dimensional high-resolution scattering distribution image. Amplitude calibration is performed on airborne SAR echo data using an integral calibration method that averages multiple targets. Analysis of uncertainty in airborne SAR imaging test data; The specific steps for amplitude calibration are as follows: SAR imaging processing is performed on the echo test data of multiple calibration bodies to obtain two-dimensional SAR images of each calibration body. In the above SAR images, the maximum impulse response region of each calibration body is used as a reference to divide and obtain the corresponding scattering region of each calibration body; The scattering region of each calibration body is integrated using the integral method to obtain the target energy of the corresponding calibration body. The calibration constant corresponding to the calibration body is obtained by comparing it with the theoretical value of the calibration body under the same condition. The calibration constants of each calibration body are averaged according to the above method to obtain the final calibration constants; By using the calibration constants obtained from the measurements to calibrate the amplitude of the SAR image of the area under test, the scattering image of the area under test can be obtained. Electromagnetic property calibration for large-scale targets includes: The calibration constants are obtained, and the relationship between the gray value of the SAR image and the absolute radar scattering is obtained by observing the calibration body with a known radar cross section. Acquire a scattering image of the area to be measured, and use the measured calibration constant to perform amplitude calibration on the SAR image of the area to be measured. Obtain RCS data for key areas or targets using RCS reconstruction technology; The logarithm of the mean of the calibration constants estimated from multiple point targets is used as the final calibration constant. Please refer to the following formula for calculation: in: For the first The calibration constant is obtained from the target point estimation. The number of point targets in the calibration field; Angle of incidence; This represents the theoretical value of the radar cross section for a point target. The energy of the point target impulse response extracted from SAR data; in: For the first The pixel value of each pixel; the number of pixels in the energy integration region of the point target is... The number of pixels corresponding to the background area is .

2. The method for acquiring electromagnetic characteristic data of large-scale targets according to claim 1, characterized in that: The first calibration body is a Luneburg sphere, and the second calibration body is a trihedral reflector.

3. The method for acquiring electromagnetic characteristic data of large-scale targets according to claim 1, characterized in that, The acquisition and processing of experimental data specifically includes the following steps: Data validity verification involves verifying the validity and completeness of various types of data collected during and after the experiment, and supplementing missing experimental data as necessary. Data classification and backup: While verifying the validity of the data, the test data is classified and backed up. Various types of characteristic data are stored in folders and backups are set up. Data processing involves using the measured calibration constants to perform amplitude calibration on the SAR image of the area under test, thereby obtaining the scattering intensity image of the area under test. Test error analysis is performed to analyze the uncertainty of airborne SAR imaging test data.

4. The method for acquiring electromagnetic characteristic data of large-scale targets according to claim 3, characterized in that, Uncertainties in airborne SAR imaging test data include: Average irradiance refers to the average irradiance between the target being measured and the calibration body; Background-target interaction refers to the rescattering of the scattered field from the target by other structures in the background; Cross-polarization refers to the error caused by the polarization purity of the antenna itself, the cross-polarization response of the target, etc. Energy drift refers to the change in the amplitude or phase of a received signal over time. Frequency drift is negligible. Signal accumulation is the error caused by the target motion during the test. IQ imbalance refers to the imbalance in amplitude and phase of the receiving system's response to the input test signal; Noise background refers to all measurement system noise, which is usually estimated by directly measuring the system noise without placing any target or support. Nonlinearity is mainly related to the receiving system, such as the receiver and mixer in the measurement system, and reflects the nonlinearity index of the receiving system's response. Distance accuracy refers to the error generated during the distance measurement process between the transmitting and receiving antennas and the target under test; Target orientation refers to the error in the target's azimuth measurement; Calibration error refers to the combined uncertainty related to the measurement of the calibration body.

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