Shipborne phased array radar RCS measurement accuracy evaluation method

Abstract

The application relates to a shipborne phased array radar RCS measurement precision evaluation method for a ship, characterized in that the method comprises the following steps: step 1, obtaining the RCS measurement result of a shipborne phased array radar for a moving ship; step 2, performing distance detection precision evaluation; step 3, performing angle detection precision evaluation; step 4, performing RCS actual measurement precision evaluation; step 5, giving an evaluation result, outputting the RCS actual measurement precision result, and determining whether the target RCS measurement precision meets the evaluation requirement according to the measurement environment and actual error requirement, so that the test site, test equipment and test method need to be corrected if the requirement is not met. The method fills the blank of the shipborne moving platform RCS measurement precision evaluation method for a moving ship, performs RCS measurement precision evaluation from the aspects of distance detection, angle detection and RCS actual measurement, and the evaluation method is more perfect.

Description

Technical Field

[0001] This invention relates to the field of marine radar accuracy assessment technology, and in particular to a method for assessing the accuracy of ship RCS measurement using a shipborne phased array radar. Background Technology

[0002] The radar cross section (RCS) is the radar cross section of an object measured by radar. It describes the target's ability to scatter incident electromagnetic waves and reflects the target's physical characteristics such as size, shape, and material. It is an important type of information for target identification.

[0003] A shipborne motion platform refers to a radar system installed on a surface platform to measure the radar cross-section (RCS) of vessels moving on the water. If the radar's operating status or surface measurement conditions are unstable, the accuracy of the vessel's RCS measurement will be affected; therefore, it is necessary to evaluate the accuracy of the RCS measurement. Summary of the Invention

[0004] The purpose of this invention is to provide a measurement accuracy evaluation method to assess the accuracy of measurement results from measuring equipment and determine whether they meet the required specifications.

[0005] The technical solution of this invention provides a method for evaluating the accuracy of ship RCS measurement using shipborne phased array radar, characterized in that the method includes the following steps:

[0006] Step 1: Obtain the RCS measurement results of the shipborne phased array radar for moving vessels;

[0007] Step 2: Evaluate the distance detection accuracy;

[0008] Range detection accuracy depends on noise and residual system delay. When evaluating range detection accuracy, the following factors are assessed: noise error, pulse compression delay error introduced by Doppler frequency drift on the linear frequency modulated signal, range quantization error, residual random delay error after receiver channel calibration, and other errors. The formula for calculating range detection accuracy is:

[0009]

[0010] Where, σ R For the total distance detection uncertainty, σ Ri These are the factors affecting various ranging errors;

[0011] Step 3: Evaluate the accuracy of the angle measurement;

[0012] Angle measurement accuracy depends on errors caused by signal-to-noise ratio (SNR), null depth error, amplitude imbalance, phase imbalance, and beam pointing error. When evaluating angle measurement accuracy, these errors should be assessed separately. The formula for calculating angle measurement accuracy is as follows:

[0013]

[0014] Where, σ θ The total uncertainty in angle measurement is σ. θi These are the factors affecting the angle measurement error;

[0015] Step 4: Evaluate the accuracy of the RCS measurement;

[0016] When evaluating the accuracy of RCS measurements, at least the following errors should be evaluated: antenna directivity error, error caused by background-target interaction, error caused by cross-polarization, error caused by drift, error caused by frequency, error caused by accumulation, error caused by IQ imbalance, error caused by near field, error caused by noise-background, error caused by nonlinearity, error caused by range, and error caused by target orientation.

[0017] Calculate the actual accuracy of RCS:

[0018]

[0019] Where, σ total Let σ be the measured uncertainty of the total RCS. totali These are the various error influencing factors;

[0020] Step 5: Provide the evaluation results and output the measured RCS accuracy results. Based on the measurement environment and actual error requirements, determine whether the target RCS measurement accuracy meets the evaluation requirements. If it does not meet the requirements, the test site, test equipment and test methods need to be modified.

[0021] Furthermore, in step 2:

[0022] Step 2.1, Evaluate noise error:

[0023]

[0024] Where c is the speed of light, B is the bandwidth, and SNR is the signal-to-noise ratio.

[0025] Step 2.2: Evaluate the pulse compression delay error introduced by Doppler frequency drift to the linear frequency modulated signal:

[0026]

[0027] Among them, Vm Let f0 be the target speed, f0 be the operating frequency, τ be the linear frequency modulation pulse width, and B be the bandwidth.

[0028] Step 2.3: Evaluate the distance quantization error:

[0029]

[0030] Where c is the speed of light, f s The sampling frequency.

[0031] Step 2.4: Evaluate the residual random delay error after receiving channel calibration:

[0032] σ R4 =2m

[0033] m is the unit of measurement, meters.

[0034] Step 2.5: Evaluate other errors, including those caused by propagation, flicker, frequency modulation waveforms, etc.

[0035] σ R5 =1m

[0036] m is the unit of measurement, meters.

[0037] Step 2.6: Calculate the distance detection accuracy:

[0038]

[0039] Where, σ R For the total distance detection uncertainty, σ Ri The factors affecting each ranging error are determined by steps 2.1-2.5 above.

[0040] Furthermore, step 3 is achieved in the following way:

[0041] Step 3.1: Evaluate the error caused by the signal-to-noise ratio:

[0042]

[0043] Where, θ 3dB denoted as beamwidth, and SNR as signal-to-noise ratio.

[0044] Step 3.2, Evaluate the zero-depth error:

[0045]

[0046] Among them, Z D The depth is zero, and k is the normalized slope of the angle.

[0047] Step 3.3: Evaluate the error caused by amplitude imbalance:

[0048]

[0049] Where, θ 3dB For beamwidth, A ub This is the amplitude imbalance factor.

[0050] Step 3.4: Evaluate the error caused by phase imbalance:

[0051]

[0052] Where, θ 3dB P is the beamwidth. ub Z is the phase imbalance factor. D The depth is zero, and k is the normalized slope of the angle.

[0053] Step 3.5: Evaluate beam pointing error:

[0054] σ θ5 =0.02θ 3dB

[0055] Where, θ 3dB This refers to the beamwidth.

[0056] Step 3.6: Calculate the angle measurement accuracy:

[0057]

[0058] Where, σ θ The total uncertainty in angle measurement is σ. θi The factors affecting each angle measurement error are determined by steps 3.1-3.5 above.

[0059] Furthermore, in step 4:

[0060] Step 4.1: Evaluate antenna directivity error:

[0061] Antenna directivity error refers to whether the target is illuminated by the antenna at its maximum gain, i.e., the difference between the antenna pattern gain corresponding to the angle between the vector pointing from the radar position to the target and the antenna beam pointing, and the antenna pattern gain at the position where the antenna beam points. It is assumed that the antenna pattern characteristics conform to the cosine function cos... 2 Its maximum gain is G0; the RCS measurement uncertainty caused by the pointing error due to antenna gain attenuation, the antenna gain attenuation factor G / G0, can be expressed as:

[0062]

[0063] Where θ0 is half of the 3dB beamwidth, and θ is the worst-case directivity error, according to the above formula, the uncertainty caused by the antenna directivity error is:

[0064]

[0065] Step 4.2: Assess the error caused by background-target interaction:

[0066] Background – Uncertainties arising from target interactions Estimation is made through measurement;

[0067] Step 4.3: Evaluate the error caused by cross-polarization:

[0068] If the polarization isolation of the radar system is insufficient, cross-polarization will produce a large measurement error:

[0069]

[0070] Where, ε p ε represents the antenna polarization isolation. p =20lg(R) v / R h ); R V Gain under dominant polarization, R H This refers to the gain under cross-polarization, where the subscripts v and h indicate different polarizations in the numerator and denominator.

[0071] Step 4.4: Evaluate the error caused by drift:

[0072] Uncertainty caused by drift in a measurement system can be determined by measuring a fixed target over a long period; the drift data acquisition time should be more than 3 hours; the period is based on the duration of a typical test; uncertainty caused by drift. Determined by measurement;

[0073] Step 4.5: Evaluate the error caused by frequency:

[0074] For the target being measured, the uncertainty analysis is the same as that for the calibration body, but the errors caused by different frequencies are different;

[0075] For C-band radar at f = 5.6 GHz,

[0076] For X-band radar at f = 9.6 GHz,

[0077] For Ku-band radar at f = 16.5 GHz,

[0078] For Ka-band radar, the error is small and can be ignored.

[0079] Step 4.6: Evaluate the error caused by accumulation:

[0080]

[0081] Step 4.7: Evaluate the error caused by IQ imbalance:

[0082]

[0083] Step 4.8: Evaluate the error caused by near-field:

[0084]

[0085] Step 4.9: Evaluate the error caused by noise and background:

[0086] System noise will affect measurement error; if the signal-to-noise ratio (or signal-to-noise ratio) expressed in dB is Where S is the signal power, N is the noise power, and SNR is the signal-to-noise ratio; then, for signal S, the uncertainty calculation formula is:

[0087]

[0088] Step 4.10: Evaluate the error caused by nonlinearity:

[0089] If the calibration signal is used as the power reference level, the uncertainty is taken as 0;

[0090]

[0091] Step 4.11, Evaluate the error caused by distance:

[0092] The RCS measurement uncertainty caused by distance is expressed as:

[0093]

[0094] Where: σ R R represents the total distance detection uncertainty, and R represents the target distance.

[0095] Step 4.12: Evaluate the error caused by the target direction:

[0096]

[0097] Step 4.13: Calculate the measured accuracy of RCS:

[0098]

[0099] Where, σ total Let σ be the measured uncertainty of the total RCS. totali These are the error factors affecting the measured accuracy.

[0100] The advantages of this invention compared to the prior art are:

[0101] This method fills the gap in the evaluation method of RCS measurement accuracy of moving vessels by shipborne motion platforms. It evaluates the RCS measurement accuracy from multiple angles, including distance detection, angle detection, and actual RCS measurement, and the evaluation method is more comprehensive. Attached Figure Description

[0102] The accompanying drawings illustrate, by way of example and not limitation, the embodiments discussed herein.

[0103] Figure 1 This is a schematic diagram of the method for evaluating the accuracy of ship RCS measurement using a shipborne phased array radar according to an embodiment of this application.

[0104] Figure 2 This is a schematic diagram of the process for evaluating distance detection accuracy in an embodiment of this application.

[0105] Figure 3 This is a schematic diagram of the process for evaluating the accuracy of angle measurement in an embodiment of this application.

[0106] Figure 4 This is a schematic diagram of the process for evaluating the measured accuracy of RCS in an embodiment of this application. Detailed Implementation

[0107] In order to gain a more detailed understanding of the features and technical content of the embodiments of this application, the implementation of the embodiments of this application will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for reference and illustration only and are not intended to limit the embodiments of this application.

[0108] like Figure 1 As shown, this embodiment provides a method for evaluating the accuracy of ship RCS measurements using a shipborne phased array radar. The method includes the following steps:

[0109] Step 1: Obtain the RCS measurement results of the shipborne phased array radar for moving vessels;

[0110] The radar range equation is:

[0111]

[0112] Among them, P r P represents the received power of the moving vessel under test. t λ is the transmit power, G is the antenna gain, λ is the signal wavelength, R is the target distance of the moving vessel under test, and σ is the RCS of the moving vessel under test.

[0113] Therefore, when other parameters are constant, the received power P of the moving vessel under test is... r It is proportional to the RCSσ of the moving vessel under test and can be determined based on the received power of the moving vessel under test.

[0114] Therefore, other parameters can be kept constant while calibrating the vessel under test.

[0115]

[0116] Where σ0 is the known target RCS, σ is the RCS of the moving vessel to be measured, P0 is the known target received power, and P r The received power of the moving vessel under test.

[0117] The above formula can be used to obtain the RCS measurement results of a moving vessel by a shipborne phased array radar.

[0118] Step 2: Evaluate the distance detection accuracy;

[0119] Range detection accuracy primarily depends on factors such as noise and residual system delay. When evaluating range detection accuracy, the following should be assessed separately: noise error, pulse compression delay error introduced by Doppler frequency drift on the linear frequency modulated signal, range quantization error, residual random delay error after receiver channel calibration, and other errors, such as... Figure 2 As shown, evaluating distance detection accuracy includes the following steps:

[0120] Step 2.1, Evaluate noise error:

[0121]

[0122] Where c is the speed of light, B is the bandwidth, and SNR is the signal-to-noise ratio.

[0123] Step 2.2: Evaluate the pulse compression delay error introduced by Doppler frequency drift to the linear frequency modulated signal:

[0124]

[0125] Among them, V m Let f0 be the target speed, f0 be the operating frequency, τ be the linear frequency modulation pulse width, and B be the bandwidth.

[0126] Step 2.3: Evaluate the distance quantization error:

[0127]

[0128] Where c is the speed of light, f s The sampling frequency.

[0129] Step 2.4: Evaluate the residual random delay error after receiving channel calibration:

[0130] σ R4 =2m

[0131] m is the unit of measurement, meters.

[0132] Step 2.5: Evaluate other errors, including those caused by propagation, flicker, frequency modulation waveforms, etc.

[0133] σ R5 =1m

[0134] m is the unit of measurement, meters.

[0135] Step 2.6: Calculate the distance detection accuracy:

[0136]

[0137] Where, σ R For the total distance detection uncertainty, σ Ri The factors affecting each ranging error are determined by steps 2.1-2.5 above.

[0138] Step 3: Evaluate the angle measurement accuracy;

[0139] Angle measurement accuracy is mainly affected by several factors, including errors caused by signal-to-noise ratio (SNR), zero-depth error, amplitude imbalance, phase imbalance, and beam pointing error. When evaluating angle measurement accuracy, these errors should be assessed separately. Figure 3 As shown, evaluating angular measurement accuracy includes the following steps:

[0140] Step 3.1: Evaluate the error caused by the signal-to-noise ratio:

[0141]

[0142] Where, θ 3dB denoted as beamwidth, and SNR as signal-to-noise ratio.

[0143] Step 3.2, Evaluate the zero-depth error:

[0144]

[0145] Among them, Z D The depth is zero, and k is the normalized slope of the angle.

[0146] Step 3.3: Evaluate the error caused by amplitude imbalance:

[0147]

[0148] Where, θ 3dB For beamwidth, A ub This is the amplitude imbalance factor.

[0149] Step 3.4: Evaluate the error caused by phase imbalance:

[0150]

[0151] Where, θ3dB P is the beamwidth. ub Z is the phase imbalance factor. D The depth is zero, and k is the normalized slope of the angle.

[0152] Step 3.5: Evaluate beam pointing error:

[0153] σ θ5 =0.02θ 3dB

[0154] Where, θ 3dB This refers to the beamwidth.

[0155] Step 3.6: Calculate the angle measurement accuracy:

[0156]

[0157] Where, σ θ The total uncertainty in angle measurement is σ. θi The factors affecting each angle measurement error are determined by steps 3.1-3.5 above.

[0158] Step 4: Evaluate the accuracy of the measured RCS;

[0159] When evaluating the accuracy of RCS measurements, the following should be assessed separately: antenna directivity error, error caused by background-target interaction, error caused by cross-polarization, error caused by drift, frequency-induced error, accumulation-induced error, IQ imbalance-induced error, near-field error, noise-background error, nonlinearity-induced error, range-induced error, and target orientation error. Figure 4 As shown, evaluating the measured accuracy of RCS includes the following steps:

[0160] Step 4.1: Evaluate antenna directivity error:

[0161] Antenna directivity error mainly refers to whether the target is illuminated by the antenna at its maximum gain, that is, the difference between the antenna pattern gain corresponding to the angle between the vector pointing from the radar position to the target and the antenna beam pointing, and the antenna pattern gain at the antenna beam pointing position.

[0162] Assume the antenna pattern characteristics conform to the cosine function cos 2 Its maximum gain is G0. The RCS measurement uncertainty caused by the pointing error due to antenna gain attenuation, the antenna gain attenuation factor G / G0, can be expressed as:

[0163]

[0164] Where θ0 is half of the 3dB beamwidth, and θ is the worst-case directivity error, according to the above formula, the uncertainty caused by the antenna directivity error is:

[0165]

[0166] Step 4.2: Evaluate the error caused by background-target interaction:

[0167] Background – The effects of target coupling are difficult to analyze and resolve entirely analytically. Generally, experimental measurements are used to study the coupling scattering of different targets and sea clutter. Currently, most RCS test sites consider this uncertainty to be non-negligible when analyzing the effects of sea clutter coupling scattering. Background – Uncertainties caused by target interaction. Estimation is made through measurement.

[0168] Step 4.3: Evaluate the error caused by cross-polarization:

[0169] If the polarization isolation of the radar system is insufficient, cross-polarization will produce a large measurement error:

[0170]

[0171] Where, ε p ε represents the antenna polarization isolation. p =20lg(R) v / R h R V Gain under dominant polarization, R H For the gain under cross-polarization, the subscripts v and h do not specifically refer to horizontal and vertical polarization, but to the different polarizations of the numerator and denominator.

[0172] Step 4.4: Evaluate the error caused by drift:

[0173] Uncertainty caused by drift in a measurement system can be determined through long-term measurements on a fixed target. The drift data acquisition time should be at least 3 hours. This period is based on the duration of a typical test. Uncertainty caused by drift. Determined by measurement.

[0174] Step 4.5: Evaluate the error caused by frequency:

[0175] For the target being measured, the uncertainty analysis is the same as that for the calibration body, but the error caused by different frequencies is different.

[0176] For C-band radar at f = 5.6 GHz,

[0177] For X-band radar at f = 9.6 GHz,

[0178] For Ku-band radar at f = 16.5 GHz,

[0179] For Ka-band radar, the error is small and can be ignored.

[0180] Step 4.6: Evaluate the error caused by accumulation:

[0181] Integral uncertainty arises from the target motion within the duration of a single pulse. In RCS measurements, the signal-to-noise ratio can be improved by coherently accumulating the target echo, thereby reducing the impact of noise on measurement uncertainty. For quasi-static tests (where the target moves slowly and the pulse repetition period is short), integral error is generally not a key factor affecting RCS uncertainty.

[0182]

[0183] Step 4.7: Evaluate the error caused by IQ imbalance:

[0184] Since modern advanced RCS measurement radars mostly use digital IQ receivers, their channel imbalance can be calibrated to a relatively ideal level. Therefore, this factor is generally not a key factor affecting the uncertainty of RCS measurement.

[0185]

[0186] Step 4.8: Evaluate the error caused by near-field:

[0187] A complete analysis of the effects of illumination is very difficult and may not be practically meaningful. Therefore, a simpler, coarse estimation method is often used to assess the impact of illumination, typically by estimating the peak-to-peak amplitude variation of the scattering source in the target image domain (the radial and lateral distance space of the target). Thus, a 0.5 dB taper will produce a 0.5 dB RCS uncertainty component. If it can be ensured that a major scattering center on the target is illuminated relatively uniformly, the RCS uncertainty can be reduced accordingly.

[0188]

[0189] Step 4.9: Evaluate the error caused by noise and background:

[0190] System noise will affect measurement error. If the signal-to-noise ratio (or signal-to-noise ratio) is expressed in dB... Where S is the signal power, N is the noise power, and SNR is the signal-to-noise ratio; then, for signal S, the uncertainty calculation formula is:

[0191]

[0192] Step 4.10: Evaluate the error caused by nonlinearity:

[0193] If the calibration signal is used as the power reference level, the uncertainty can be taken as 0.

[0194]

[0195] Step 4.11, Evaluate the error caused by distance:

[0196] Based on the results of "Evaluating the accuracy of distance detection", the RCS measurement uncertainty caused by distance can be calculated and expressed as follows:

[0197]

[0198] In the formula: σ R R represents the total distance detection uncertainty, and R represents the target distance.

[0199] Step 4.12: Evaluate the error caused by the target direction:

[0200] Since RCS measurements are only concerned with the envelope levels of the peak and side lobes (as is the case for most RCS measurements), the uncertainty caused by target pointing is largely negligible.

[0201]

[0202] Step 4.13: Calculate the measured accuracy of RCS:

[0203]

[0204] Where, σ total Let σ be the measured uncertainty of the total RCS. totali Each error influencing factor is determined by steps 4.1-4.12 above.

[0205] Step 5: Provide the evaluation results.

[0206] Output the measured RCS accuracy result. Based on the measurement environment and actual error requirements, determine whether the target RCS measurement accuracy meets the evaluation requirements. If it does not meet the requirements, the test site, test equipment and test methods need to be modified to reduce the uncertainty components and improve the measurement accuracy.

[0207] This embodiment uses specific examples to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this embodiment should not be construed as a limitation of the present invention.

Claims

1. A method for evaluating the accuracy of ship RCS measurement using a shipborne phased array radar, characterized in that: The method includes the following steps: Step 1: Obtain the RCS measurement results of the shipborne phased array radar for moving vessels; Step 2: Conduct distance detection accuracy assessment; Range detection accuracy depends on noise and residual system delay. When evaluating range detection accuracy, the following factors are assessed: noise error, pulse compression delay error introduced by Doppler frequency drift on the linear frequency modulated signal, range quantization error, residual random delay error after receiver channel calibration, and other errors. The formula for calculating range detection accuracy is: ； Where, σ R For the total distance detection uncertainty, σ Ri These are the factors affecting various ranging errors; Step 3: Evaluate the accuracy of the angle measurement; Angle measurement accuracy depends on errors caused by signal-to-noise ratio (SNR), null depth error, amplitude imbalance, phase imbalance, and beam pointing error. When evaluating angle measurement accuracy, these errors should be assessed separately. The formula for calculating angle measurement accuracy is as follows: ； Where, σ θ The total uncertainty in angle measurement is σ. θi These are the factors affecting the angle measurement error; Step 4: Evaluate the accuracy of the RCS measurement; When evaluating the accuracy of RCS measurements, at least the following errors should be evaluated: antenna directivity error, error caused by background-target interaction, error caused by cross-polarization, error caused by drift, error caused by frequency, error caused by accumulation, error caused by IQ imbalance, error caused by near field, error caused by noise-background, error caused by nonlinearity, error caused by range, and error caused by target orientation. Calculate the actual accuracy of RCS: ； Where, σ total Let σ be the measured uncertainty of the total RCS. totali These are the various error influencing factors; Step 5: Provide the evaluation results and output the measured RCS accuracy results. Based on the measurement environment and actual error requirements, determine whether the target RCS measurement accuracy meets the evaluation requirements. If it does not meet the requirements, the test site, test equipment and test methods need to be modified.

2. The method for evaluating the accuracy of ship RCS measurement by shipborne phased array radar according to claim 1, characterized in that: In step 2: Step 2.1, Evaluate noise error: ； Where c is the speed of light, B is the bandwidth, and SNR is the signal-to-noise ratio. Step 2.2: Evaluate the pulse compression delay error introduced by Doppler frequency drift to the linear frequency modulated signal: ； in, For the target speed, For operating frequency, B is the linear frequency modulated pulse width, and B is the bandwidth. Step 2.3: Evaluate the distance quantization error: ； Where c is the speed of light. The sampling frequency; Step 2.4: Evaluate the residual random delay error after receiving channel calibration: ； m is the unit meter; Step 2.5: Evaluate other errors, including those caused by propagation, flicker, and frequency modulation waveforms. ； m is the unit meter; Step 2.6: Calculate the distance detection accuracy: ； Where, σ R For the total distance detection uncertainty, σ Ri The factors affecting each ranging error are determined by steps 2.1-2.5 above.

3. The method for evaluating the accuracy of ship RCS measurement by shipborne phased array radar according to claim 1, characterized in that: Step 3 is achieved in the following way: Step 3.1: Evaluate the error caused by the signal-to-noise ratio: ； in, Where S is the beamwidth and SNR is the signal-to-noise ratio; Step 3.2, Evaluate the zero-depth error: ； in, The depth is zero, and k is the normalized slope of the angle. Step 3.3: Evaluate the error caused by amplitude imbalance: ； in, For beamwidth, This is the amplitude imbalance factor; Step 3.4: Evaluate the error caused by phase imbalance: ； in, For beamwidth, For phase imbalance factor, The depth is zero, and k is the normalized slope of the angle. Step 3.5: Evaluate beam pointing error: ； in, Beamwidth; Step 3.6: Calculate the angle measurement accuracy: ； Where, σ θ The total uncertainty in angle measurement is σ. θi The factors affecting each angle measurement error are determined by steps 3.1-3.5 above.

4. The method for evaluating the accuracy of ship RCS measurement by shipborne phased array radar according to claim 1, characterized in that: In step 4: Step 4.1: Evaluate antenna directivity error: Antenna directivity error refers to whether the target is illuminated by the antenna at its maximum gain, i.e., the difference between the antenna pattern gain corresponding to the angle between the vector pointing from the radar position to the target and the antenna beam pointing, and the antenna pattern gain at the antenna beam pointing position; assuming the antenna pattern characteristics conform to a cosine function. Its maximum gain is The RCS measurement uncertainty caused by pointing error due to antenna gain attenuation, and the antenna gain attenuation factor. It can be represented as: ； in It is half the 3dB beamwidth. For the worst-case directivity error, according to the above formula, the uncertainty caused by the antenna directivity error is: ； Step 4.2: Assess the background – error caused by target interaction: Background – Uncertainties arising from target interactions Estimation is performed through measurement; Step 4.3: Evaluate the error caused by cross-polarization: If the polarization isolation of the radar system is insufficient, cross-polarization will produce a large measurement error: ； in, Antenna polarization isolation, ;R V Gain under dominant polarization, R H This refers to the gain under cross-polarization, where the subscripts v and h indicate different polarizations in the numerator and denominator. Step 4.4: Evaluate the error caused by drift: Uncertainty caused by drift in a measurement system can be determined by measuring a fixed target over a long period; the drift data acquisition time should be more than 3 hours; the period is based on the duration of a typical test; uncertainty caused by drift. Determined by measurement; Step 4.5: Evaluate the error caused by frequency: For the target being measured, the uncertainty analysis is the same as that for the calibration body, but the errors caused by different frequencies are different; For C-band radar hour, ; For X-band radar hour, ; For Ku-band radar hour, ; For Ka-band radar, the error is small and can be ignored. ; Step 4.6: Evaluate the error caused by accumulation: ； Step 4.7: Evaluate the error caused by IQ imbalance: ； Step 4.8: Evaluate the error caused by near-field: ； Step 4.9: Evaluate the error caused by noise and background: System noise will affect measurement error; if the signal-to-noise ratio is expressed in dB... Where S is the signal power, N is the noise power, and SNR is the signal-to-noise ratio; then, for signal S, the uncertainty calculation formula is: ； Step 4.10: Evaluate the error caused by nonlinearity: If the calibration signal is used as the power reference level, the uncertainty is taken as 0; ； Step 4.11, Evaluate the error caused by distance: The measurement uncertainty of RCS caused by distance is expressed as ； In the formula: R represents the total distance detection uncertainty, and R represents the target distance. Step 4.12: Evaluate the error caused by the target direction: ； Step 4.13: Calculate the measured accuracy of RCS: ； in, The measured uncertainty of the total RCS is... These are the error factors affecting the measured accuracy.

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