Method for obtaining equivalent noise of multi-imaging mode SAR images

Abstract

The present invention discloses a method for obtaining the equivalent noise of a multi-imaging mode SAR image, which relates to the field of synthetic aperture radar radiation correction technology. The method includes: calculating the noise power at the imaging moment of noise calibration data; respectively calculating the noise gain of the SAR signal in the multi-mode imaging processing process, wherein the multi-mode includes a strip imaging mode, a beam imaging mode, and a sliding scanning (TOPSAR) imaging mode; respectively calculating the equivalent noise of each mode according to the noise gain corresponding to each imaging mode and the noise power at the imaging moment of the noise calibration data. The method directly obtains the equivalent noise coefficient in the SAR signal imaging processing and radiation correction process, avoids the dependence of the noise power estimation on the SAR image using the SAR image, greatly reduces the amount of calculation and shortens the time cost.

Description

Technical Field

[0001] The present disclosure relates to the technical field of synthetic aperture radar radiation correction, and in particular to a method for acquiring equivalent noise of a multi-imaging mode SAR image. Background Art

[0002] Synthetic aperture radar has the ability to work all day and all weather, and is an important microwave remote sensing method; with the increasing widespread quantitative application of synthetic aperture radar (SAR), the requirements for its radiation accuracy are getting higher and higher. In other words, whether SAR images can reflect the absolute normalized radar cross section (NRCS) of real objects plays a vital role in the quantitative application of SAR. For fields such as ocean remote sensing, due to weak scene echoes and low signal-to-noise ratio, noise becomes an important factor affecting quantitative applications, making the backscatter coefficient directly obtained from SAR images unable to accurately reflect the scattering characteristics of the sea surface. In SAR systems, the main source of noise is the thermal noise of the receiver.

[0003] The receiver thermal noise is modulated by the imaging processor and directly attached to the SAR image, resulting in inaccurate NRCS values ​​of the target directly obtained on the SAR image, especially when the backscattering of the ground target is weak. For example, the cross-polarization backscattering of the sea surface is weak, and the sea surface NRCS value shows the same variation characteristics as the system thermal noise power along the distance direction. However, the quantitative inversion of ocean parameters (sea surface wind field) requires accurate NRCS information, so the image must be denoised. The premise of image denoising is to obtain the intensity of the noise power in the SAR image.

[0004] At present, there are mainly three methods for estimating the equivalent noise coefficient (Noise Equivalent Sigma Zero, NESZ) of existing SAR images: First, it is obtained by measuring scenes with ideal zero backscattering (such as calm water or flat surface). It is also the main way of NESZ analysis for many SAR satellites. However, this method requires extremely high-quality illumination areas. Second, based on reciprocity, the minimum eigenvalue estimation (MEE) and maximum likelihood estimation (MLE) techniques can be used to derive NESZ from cross-polarization images. However, this method must ensure the use of reflection symmetric targets, that is, the HV and VH reflection characteristics of the target should be the same. And this method can only calculate the NESZ of cross-polarization images in full polarization mode. Third, based on the hardware measurement method, the current SAR payload has designed a noise calibration loop, which only receives system thermal noise as the echo signal, and then passes through the same ground imaging processing system as the SAR signal, and finally outputs the NESZ in the SAR image.

[0005] However, the first two methods extract NESZ through SAR images, and the results are limited by the quality of SAR images. Even in the same wave position, the NESZ of SAR images is different due to factors such as SAR payload imaging parameters, orbit, and elevation of the irradiated area. That is, the NESZ estimated from the SAR image is not applicable to all SAR data with the same wave position. The third method can obtain the NESZ of SAR images more accurately, but in the implementation process, the noise calibration signal needs to use the same imaging processing flow as the SAR signal, which is computationally intensive and time-consuming. Summary of the invention

[0006] In view of the above technical problems, the present disclosure provides a method for acquiring the equivalent noise of a multi-imaging mode SAR image, comprising: calculating the noise power of noise calibration data at the imaging moment; respectively calculating the noise gain of the SAR signal in the multi-mode imaging processing process, wherein the multi-mode includes a strip imaging mode, a beam imaging mode, and a sliding scanning imaging mode; respectively calculating the equivalent noise of each mode according to the noise gain corresponding to each imaging mode and the noise power of the noise calibration data at the imaging moment.

[0007] According to an embodiment of the present disclosure, calculating the noise power of the noise-in-noise calibration signal specifically includes:

[0008] P N2 =P N1 ·MGC1 / MGC2

[0009] Calculate the noise power P at the imaging time of the noise calibration data N2 , where P N1 is the noise power of the noise calibration data, MGC1 is the manual control gain value used in noise calibration, and MGC2 is the manual control gain value used in noise imaging.

[0010] According to an embodiment of the present disclosure, calculating the noise gain of a SAR signal in a strip imaging mode imaging process includes:

[0011]

[0012] Calculate the noise gain G of SAR signal in the strip imaging mode imaging process noise_strip , where G crg is the range compression gain of the SAR signal, G caz is the SAR signal azimuth compression gain, G wrg is the range windowing gain of the SAR signal, G waz is the azimuth windowing gain of the SAR signal, G MGC is the radar control gain, G LGis the receiver link gain, G aa is the transmission attenuation compensation gain, G paz is the azimuth antenna pattern compensation gain, G prg is the distance antenna pattern compensation gain, GN wrg is the noise range window gain, GN waz The azimuth window gain of the noise signal.

[0013] According to the embodiments of the present disclosure, according to

[0014]

[0015] Calculate the range windowing gain G of the SAR signal wrg , among which, WIN rg (i) is the range window function, N wr The length of the windowed portion of the distance;

[0016] according to

[0017]

[0018] Calculate the noise range window gain GN wrg , where N r is the distance length.

[0019] According to the embodiments of the present disclosure, according to

[0020]

[0021] Calculate the azimuth windowing gain G of the SAR signal waz , among which, WIN az (i) is the azimuth window function, N wa The length of the azimuth windowing part;

[0022] according to

[0023]

[0024] Calculate the azimuth window gain GN of the noise signal waz , where G paz (i)) is the azimuth antenna pattern correction function, N a is the azimuth length.

[0025] According to an embodiment of the present disclosure, calculating the noise gain of a SAR signal in a spotlight imaging mode imaging process includes:

[0026] G noise_spot =G noise_strip ·G deramp

[0027] Calculate the noise gain G of SAR signal in the imaging process of spotlight imaging mode noise_spot , where G noise_strip is the noise gain of SAR signal in the strip imaging mode imaging process, G deramp is the noise gain generated by the SAR signal after Deramp processing.

[0028] According to the embodiments of the present disclosure, according to

[0029] G deramp =N /

[0030] Calculate G deramp , N is the number of azimuth points before zero padding of SAR signal in the Deramp process, and M is the number of azimuth points after zero padding of SAR signal in the Deramp process.

[0031] According to an embodiment of the present disclosure, calculating the noise gain of a SAR signal in an imaging process of a sliding scanning imaging mode includes:

[0032] G noise_top =G noise_strip ·G azpre ·G specan

[0033] Calculate the noise gain G of SAR signal in the imaging process of sliding scanning imaging mode noise_top , where G noise_strip is the noise gain of SAR signal in the strip imaging mode imaging process, G azpre is the azimuth pre-filter gain, G specan is the azimuth spectrum analysis gain.

[0034] According to an embodiment of the present disclosure, the multiple of energy reduction of the SAR signal and noise after azimuth pre-filtering is determined as G azpre ;according to

[0035] G specan =PRF / ((pulse_num / PRF)·K rot +PRF)

[0036] Calculate G specan , where PRF is the pulse repetition frequency of the radar, pulse_num is the number of azimuth pulses, and K rot It is the rate of change of the Doppler center of the target echo in the sliding scan imaging with the azimuth time.

[0037] According to an embodiment of the present disclosure, the equivalent noise of each mode is calculated according to the noise gain corresponding to each imaging mode and the noise power at the imaging moment of the noise calibration data, specifically including:

[0038] P N3 =P N2 ·G noise

[0039] Calculate the SAR image equivalent noise coefficient P corresponding to each mode N3 , G noise is the noise gain in the imaging process of each mode.

[0040] The method for obtaining equivalent noise of a multi-imaging mode SAR image provided by the embodiment of the present disclosure can at least achieve the following technical effects:

[0041] By calculating the noise gain of the SAR signal in each mode of imaging processing, the NESZ can be directly obtained in the SAR signal imaging processing and radiation correction process, avoiding the dependence of SAR images on noise power estimation using SAR images, greatly reducing the amount of calculation and shortening the time cost.

[0042] Furthermore, since the calculation of noise gain is closely related to the SAR imaging mode, the difference in noise power caused by factors such as SAR payload imaging parameters, orbit, and elevation of the irradiated area under the same wave position, that is, the same viewing angle, is avoided.

[0043] Furthermore, the method can obtain in real time the variation of noise power along the range direction of SAR images in various imaging modes and various polarization modes. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The above and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0045] Figure 1 A diagram schematically shows a method for acquiring equivalent noise of a multi-imaging mode SAR image according to an embodiment of the present disclosure.

[0046] Figure 2 The diagram schematically shows a SAR signal propagation process according to an embodiment of the present disclosure.

[0047] Figure 3 The figure schematically shows a weighted window function curve diagram according to an embodiment of the present disclosure.

[0048] Figure 4 A comparison curve diagram of a white noise output power of 0 dB and a theoretical calculated value using a set of GF-3 standard stripe mode imaging parameters in the stripe imaging mode according to an embodiment of the present disclosure is schematically shown.

[0049] Figure 5A comparison curve diagram of a white noise output power of 0 dB and a theoretical calculated value using a set of GF-3 beamforming mode imaging parameters in the beamforming imaging mode according to an embodiment of the present disclosure is schematically shown.

[0050] Figure 6 A comparison curve of a set of imaging parameters of the GF-302 satellite sliding scanning imaging mode and a white noise output power of 0 dB with a theoretical calculated value in the sliding scanning imaging mode according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solutions and advantages of the present disclosure more clearly understood, the present disclosure is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present disclosure, rather than all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present disclosure.

[0052] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0053] In the present disclosure, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, an electrical connection, or can communicate with each other; it can be a direct connection, or it can be indirectly connected through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present disclosure can be understood according to specific circumstances.

[0054] In the description of the present disclosure, it is necessary to understand that the terms "longitudinal", "length", "circumferential", "front", "rear", "left", "right", "top", "bottom", "inside", "outside", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the present disclosure and simplifying the description, and do not indicate or imply that the subsystem or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present disclosure.

[0055] Throughout the drawings, the same elements are represented by the same or similar reference numerals. Conventional structures or configurations will be omitted when they may cause confusion in the understanding of the present disclosure. The shapes, sizes, and positional relationships of the components in the drawings do not reflect the actual size, proportion, and actual positional relationship. In addition, in the present disclosure, any reference symbol between brackets should not be constructed as a limitation to the present disclosure.

[0056] Similarly, in order to simplify the present disclosure and help understand one or more of the various disclosed aspects, in the above description of the exemplary embodiments of the present disclosure, the various features of the present disclosure are sometimes grouped together into a single embodiment, figure, or description thereof. The description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" and the like means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0057] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the feature. In the description of the present disclosure, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0058] In view of the shortcomings of the prior art, the embodiments of the present disclosure provide a method for obtaining the equivalent noise of a multi-imaging mode SAR image. For SAR imaging mode, strip imaging mode, beamforming mode, and sliding scanning imaging mode, the system NESZ is directly output during the imaging process, and there is no need to perform imaging processing on the noise calibration signal separately. As long as the noise gain of the entire SAR imaging process can be accurately characterized, combined with the noise power obtained by noise calibration, the NESZ superimposed on the SAR image can be obtained to meet the requirements of ocean parameter inversion and other needs. The following is a detailed introduction in conjunction with specific embodiments.

[0059] Figure 1 A diagram schematically shows a method for acquiring equivalent noise of a multi-imaging mode SAR image according to an embodiment of the present disclosure.

[0060] like Figure 1 As shown, the method for acquiring equivalent noise of a multi-imaging mode SAR image may include, for example, operations S101 to S103.

[0061] In operation S101 , the noise power of noise calibration data at an imaging time is calculated.

[0062] In the disclosed embodiment, the noise power can be obtained by statistically analyzing the variance of the noise calibration data in the internal calibration data in the SAR raw data. It is necessary to pay attention to the inconsistency between the noise calibration and the MGC (manual gain control) used in the imaging process. The difference in MGC needs to be considered when calculating the noise power at the imaging moment. Suppose the noise power of the noise calibration data is P N1 , the manual control gain value used in noise calibration is MGC1, and the manual control gain value used in noise imaging calibration is MGC2, then according to

[0063] P N2 =P N1 ·MGC1 / MGC2

[0064] Calculate the noise power P at the imaging time of the noise calibration data N2 .

[0065] In operation S102, noise gains of SAR signals in a multi-mode imaging process are respectively calculated, wherein the multi-mode includes a strip imaging mode, a spotlight imaging mode, and a sliding scanning imaging mode.

[0066] In the SAR imaging and radiation correction process, not only the SAR echo signal is corrected, but also the thermal noise signal is processed in the same way. Therefore, the noise gain can be calculated according to the imaging and radiation correction process of the SAR data ground processing system. The disclosed embodiment combines the SAR imaging and radiation correction process to provide a theoretical calculation method for the noise gain in the SAR imaging process.

[0067] Figure 2 The diagram schematically shows a SAR signal propagation process according to an embodiment of the present disclosure.

[0068] like Figure 2 As shown in the figure, the radiation correction processing of the SAR ground processing system mainly considers the antenna and propagation process gain, receiver gain, imaging processor gain and other aspects. In addition, in the imaging processing process, range compression, range windowing, azimuth compression, azimuth windowing, azimuth antenna pattern correction and range antenna pattern correction will all produce additional gain for SAR signals and noise. It should be noted that in the SAR data radiation correction processing process, the gain of the noise signal in the windowing gain link is different from that of the SAR echo signal, that is, the window function has different effects on the signal and noise gain.

[0069] In one embodiment of the present disclosure, for the strip imaging mode, the

[0070]

[0071] Calculate the noise gain G of SAR signal in the strip imaging mode imaging process noise_strip , where G crg is the range compression gain of the SAR signal, G caz is the SAR signal azimuth compression gain, G wrg is the range windowing gain of the SAR signal, G waz is the azimuth windowing gain of the SAR signal, G MGC is the radar control gain, G LG is the receiver link gain, G aa is the transmission attenuation compensation gain, G paz is the azimuth antenna pattern compensation gain, G prg is the distance antenna pattern compensation gain, GN wrg is the noise range window gain, GN waz The azimuth window gain of the noise signal.

[0072] The following is a further description of each gain, as follows:

[0073] The range compression gain G of the SAR signal crg :

[0074] For SAR signals, it is mainly the matched filter gain. For noise signals, it has no actual physical meaning. In the radiation correction process, the imaging algorithm compensates for the range compression gain G crg Therefore, for noise gain calculation, G needs to be removed crg .

[0075] SAR signal azimuth compression gain G caz :

[0076] The range compression gain G of the SAR signal crg Similarly, for noise gain calculations, G needs to be removed. crg .

[0077] Range windowing gain G of SAR signal wrg :

[0078] The spectrum of the range echo signal is approximately rectangular, and the spectrum of the matched filter is also rectangular, so the gain of the range window function can be calculated directly.

[0079] Figure 3 The figure schematically shows a weighted window function curve diagram according to an embodiment of the present disclosure.

[0080] like Figure 3 As shown, for the signal, it can be based on

[0081]

[0082] Calculate the range windowing gain G of the SAR signal wrg , among which, WIN rg (i) is the range window function, N wr The length of the distance window.

[0083] Due to the truncation of the range window function, the signal and noise also lose the spectral energy outside the window function, but the signal loss has been considered in the range compression gain compensation process. Because the range compression gain is for the SAR echo signal, it does not generate gain for the noise power. For noise, it is necessary to consider the energy loss after windowing.

[0084] Therefore, according to

[0085]

[0086] Calculate the noise range window gain GN wrg , where N r is the distance length. That is, the theoretical calculation of noise gain needs to subtract the SAR signal range window gain and add the noise range window gain.

[0087] Azimuth windowing gain G of SAR signal waz :

[0088] For SAR signals, we can

[0089]

[0090] Calculate the azimuth windowing gain G of the SAR signal waz , among which, WIN az (i) is the azimuth window function, N wa The length of the azimuth windowing portion.

[0091] However, for noise, after the azimuth antenna pattern modulation compensation, the spectrum shape is no longer rectangular. Therefore, the azimuth window function gain calculation should consider the influence of the antenna pattern, and the antenna pattern correction coefficient is also regarded as a window function. The two are combined to calculate the distance window gain.

[0092] Therefore, according to

[0093]

[0094] Calculate the azimuth window gain GN of the noise signal waz , where G paz (i)) is the azimuth antenna pattern correction function, N ais the azimuth length. That is, the theoretical calculation of noise gain needs to subtract the SAR signal azimuth window gain and add the noise azimuth window gain.

[0095] Distance antenna pattern compensation gain G prg :

[0096] Antenna pattern gain refers to the absolute gain of the transmitting and receiving antennas to the signal and the change of the pattern with the azimuth. The range antenna pattern is equivalent to range windowing. Therefore, the echo energy distortion caused by this needs to be eliminated during the radiation correction process, but for noise, the range antenna pattern compensation gain is additionally increased. Therefore, the range antenna pattern compensation gain G prg It can be the inverse of the range antenna pattern.

[0097] Azimuth antenna pattern compensation gain G paz :

[0098] The azimuth antenna pattern is equivalent to azimuth windowing of the electromagnetic wave. The azimuth antenna pattern compensation gain G paz It can be the inverse of the antenna pattern in azimuth.

[0099] Multi-view processing:

[0100] Generally, multiple-look processing is used to reduce speckle noise. The processor bandwidth is reduced in azimuth and distance, and the spectrum is divided into several segments for separate imaging, and then incoherent superposition is performed. Therefore, for the system noise signal, due to multiple-look processing, the calculation of noise gain will also change, mainly in terms of window function gain.

[0101] Performing multi-look processing in the range direction does not cause additional gain to the window function gain.

[0102] Since the noise azimuth is modulated by the azimuth pattern, the spectrum of each azimuth segment is not consistent after azimuth multi-view processing. Therefore, it is necessary to perform post-superposition averaging processing, that is:

[0103]

[0104] Radar control gain G MGC :

[0105] Radar control gain is the main means to improve the dynamic range of radar receivers, which can effectively prevent reception or cutoff caused by excessive signal dynamic range. MGC gain compensation is required for SAR signal radiation correction and noise gain calculation.

[0106] Receiver link gain G LG :

[0107] The receiver link gain is the gain between the echo signal TR component and the analog-to-digital converter. For SAR signal radiation correction and noise gain calculation, the link gain G needs to be compensated. LG .

[0108] Transmission attenuation compensation gain G aa :

[0109] Transmission attenuation refers to the attenuation of the power of radar-transmitted electromagnetic waves and echoes after they propagate through the atmosphere. For SAR signal radiation correction, it is necessary to compensate for the signal energy transmission attenuation to generate additional gain for the noise signal.

[0110] In one embodiment of the present disclosure, for the spotlight imaging mode, the

[0111] G noise_spot =G noise_strip ·G deramp

[0112] Calculate the noise gain G of SAR signal in the imaging process of spotlight imaging mode noise_spot , where G noise_strip is the noise gain of SAR signal in the strip imaging mode imaging process, G deramp is the noise gain generated by the SAR signal after Deramp processing.

[0113] The following is a further description of each gain, as follows:

[0114] The noise gain G generated by the SAR signal after Deramp processing deramp :

[0115] Unlike the strip imaging algorithm, Deramp processing is required before linear frequency modulation scaling (CS) to eliminate spectrum aliasing. Therefore, it is necessary to increase the Deramp processing gain based on the strip mode. In the Deramp processing process, in order to meet the Nyquist sampling theorem, zero padding is required before FFT, which will cause the average signal power to attenuate by N / M times, where N is the number of azimuth points before zero padding and M is the number of azimuth points after zero padding.

[0116] Therefore, according to

[0117] G deramp =N / M

[0118] Calculate G deramp , N is the number of azimuth points before zero padding of SAR signal in the Deramp process, and M is the number of azimuth points after zero padding of SAR signal in the Deramp process.

[0119] In one embodiment of the present disclosure, for the sliding scanning imaging mode,

[0120] G noise_top =G noise_strip ·G azpre ·G specan

[0121] Calculate the noise gain G of SAR signal in the imaging process of sliding scanning imaging mode noise_top , where G noise_strip is the noise gain of SAR signal in the strip imaging mode imaging process, G azpre is the azimuth pre-filter gain, G specan is the azimuth spectrum analysis gain.

[0122] The following is a further description of each gain, as follows:

[0123] Azimuth pre-filter gain G azpre :

[0124] Different from strip imaging, azimuth pre-filtering is required to eliminate spectrum aliasing. Azimuth pre-filtering upsamples the signal and noise. The energy of the signal and noise is also reduced by M times. The azimuth pre-filtering gain is G azpre =M.

[0125] Azimuth spectrum analysis gain G specan :

[0126] Unlike strip imaging, azimuth spectrum analysis (SPECAN) is introduced after CS imaging to adjust the azimuth pixel interval. The azimuth SPECAN operation itself does not introduce processing gain, but after azimuth SPECAN processing, unlike the strip mode, the sliding scan imaging mode image appears in the Doppler frequency domain. At this time, due to its physical characteristics, the image is distributed in the spectrum range determined by the antenna scanning angle, while the noise is distributed in the entire spectrum. Therefore, the azimuth SPECAN operation brings additional processing gain to the noise:

[0127] G specan =PRF / ((pulse_num / PRF)·K rot +PRF)

[0128] Among them, PRF is the pulse repetition frequency of the radar when it is working, pulse_num is the number of azimuth pulses, K rot It is the rate of change of the Doppler center of the target echo in the sliding scan imaging with the azimuth time.

[0129] In operation S103, the equivalent noise of each mode is calculated according to the noise gain corresponding to each imaging mode and the noise power at the imaging moment of the noise calibration data.

[0130] In one embodiment of the present disclosure, according to

[0131] P N3 =P N2 ·G noise

[0132] Calculate the SAR image equivalent noise coefficient P corresponding to each mode N3 , G noise is the noise gain in the imaging process of each mode, including the noise gain G of the SAR signal in the strip imaging mode. noise_strip , the noise gain G of SAR signal in the imaging process of spotlight imaging mode noise_spot And the noise gain G of the SAR signal in the imaging process of sliding scanning imaging mode noise_top .

[0133] In order to verify the correctness of the method of the embodiment of the present disclosure, the embodiment of the present disclosure also verifies the correctness of the method of the present invention through GF-3 SAR data. Gaussian white noise is used as input, and the noise variation curve along the distance is obtained through the GF-3 ground imaging algorithm, and compared with the theoretical calculation value. The results are as follows:

[0134] Strip imaging mode:

[0135] Figure 4 A comparison curve diagram of a white noise output power of 0 dB and a theoretical calculated value using a set of GF-3 standard stripe mode imaging parameters in the stripe imaging mode according to an embodiment of the present disclosure is schematically shown.

[0136] like Figure 4 As shown, the upper figure is a single-view situation, and the lower figure is the result of distance 3-view and azimuth 2-view processing. Figure 4 It can be clearly seen that the curves corresponding to the calculated value and the actual output value coincide with each other, indicating that the calculated value is consistent with the actual output value.

[0137] Spotlight imaging mode:

[0138] Figure 5 A comparison curve diagram of a white noise output power of 0 dB and a theoretical calculated value using a set of GF-3 beamforming mode imaging parameters in the beamforming imaging mode according to an embodiment of the present disclosure is schematically shown.

[0139] like Figure 5 As shown, it can be clearly seen that the curves corresponding to the calculated value and the actual output value coincide with each other, indicating that the calculated value is consistent with the actual output value.

[0140] Slide Scan Imaging Mode:

[0141] Figure 6A comparison curve diagram of a white noise output power of 0 dB and a theoretical calculated value using a set of GF-302 satellite sliding scanning imaging parameters in the sliding scanning imaging mode according to an embodiment of the present disclosure is schematically shown.

[0142] like Figure 6 As shown, it can be clearly seen that the curves corresponding to the calculated value and the actual output value coincide with each other, indicating that the calculated value is consistent with the actual output value.

[0143] In summary, the method for obtaining the equivalent noise of a multi-imaging mode SAR image provided by the embodiment of the present disclosure can directly obtain NESZ in the SAR signal imaging processing and radiation correction process by calculating the noise gain of the SAR signal in each mode imaging processing process, thereby avoiding the reliance on the SAR image for estimating the noise power using the SAR image, greatly reducing the amount of calculation and shortening the time cost. Moreover, since the calculation of the noise gain is closely related to the SAR imaging mode, the difference in noise power caused by factors such as SAR payload imaging parameters, orbit, and elevation of the irradiated area under the same wave position, that is, the same viewing angle, is avoided. In addition, the method can obtain in real time the change in noise power along the distance direction of SAR images of various imaging modes and various polarization modes.

[0144] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present disclosure. It should be understood that the above description is only a specific embodiment of the present disclosure and is not intended to limit the present disclosure. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present disclosure should be included in the protection scope of the present disclosure.

Claims

1. A method for obtaining equivalent noise of multi-imaging mode SAR images, characterized in that: include: Calculate the noise power of the noise calibration data at the imaging moment; The noise gain of the SAR signal in the multi-mode imaging process is calculated respectively, wherein the multi-mode includes a strip imaging mode, a spotlight imaging mode, and a sliding scanning imaging mode; Calculating the equivalent noise of each mode according to the noise gain corresponding to each imaging mode and the noise power at the imaging moment of the noise calibration data; The calculating of the noise power of the noise calibration data at the imaging moment comprises: according to Calculate the noise power of the noise calibration data at the imaging moment ,in, is the noise power of the noise calibration data, Manually controlled gain value used when calibrating for noise, Manually controlled gain value used when imaging noise; Calculating the noise gain of SAR signals in the strip imaging mode imaging process includes: according to Calculation of noise gain of SAR signal in strip imaging mode imaging process ,in, is the range compression gain of the SAR signal, is the SAR signal azimuth compression gain, is the range windowing gain of the SAR signal, is the azimuth windowing gain of the SAR signal, is the radar control gain, is the receiver link gain, is the transmission attenuation compensation gain, is the azimuth antenna pattern compensation gain, is the distance antenna pattern compensation gain, is the distance window gain of the noise, is the azimuth window gain of the noise signal; Calculating the noise gain of the SAR signal in the spotlight imaging mode imaging process includes: according to Calculation of noise gain of SAR signal in the imaging process of spotlight imaging mode ,in, is the noise gain of SAR signal in the strip imaging mode imaging process, is the noise gain generated by the SAR signal after Deramp processing; Calculating the noise gain of the SAR signal in the imaging process of the sliding scanning imaging mode includes: according to Calculation of noise gain of SAR signal in the imaging process of sliding scanning imaging mode ,in, is the noise gain of SAR signal in the strip imaging mode imaging process, is the azimuth pre-filter gain, is the azimuth spectrum analysis gain.

2. The acquisition method according to claim 1, characterized in that: according to Calculate the range windowing gain of the SAR signal ,in, is the distance window function, The length of the windowed portion of the distance; according to Calculate the range window gain of the noise ,in, is the distance length.

3. The acquisition method according to claim 1, characterized in that: according to Calculate the azimuth windowed gain of the SAR signal ,in, is the azimuth window function, The length of the azimuth windowing part; according to Calculate the azimuth window gain of the noise signal ,in, is the azimuth antenna pattern correction function, is the azimuth length.

4. The acquisition method according to claim 1, characterized in that: according to Calculate the , N is the number of azimuth points before zero padding of SAR signal in the Deramp process, and M is the number of azimuth points after zero padding of SAR signal in the Deramp process.

5. The acquisition method according to claim 1, characterized in that: The multiple of energy reduction of SAR signal and noise after azimuth pre-filtering is determined as ; according to Calculate the ,in, is the pulse repetition frequency of the radar when it is working, is the number of azimuth pulses, It is the rate of change of the Doppler center of the target echo in the sliding scan imaging with the azimuth time.

6. The acquisition method according to claim 1, characterized in that: The calculating the equivalent noise of each mode according to the noise gain corresponding to each imaging mode and the noise power at the imaging moment of the noise calibration data specifically includes: according to Calculate the equivalent noise coefficient of the SAR image corresponding to each mode , is the noise gain in the imaging process of each mode.

Images