Resource-conserving commercial spaceborne broadband sar data compression method and apparatus

Abstract

The application provides a commercial spaceborne broadband SAR data compression method and device which can save resources, and relates to the field of broadband multi-channel radar technology in spaceborne application. The I / Q double circuit of echo signals is divided into data blocks composed of continuous samples, a block-by-block independent serial processing mode is adopted, corresponding quantization thresholds are calculated, and the quantization compression step is independently completed. Through the cooperative optimization of block processing and adaptive quantization mechanism, the utilization rate and processing delay of the calculation unit are improved, the storage resources and time resources are saved while the image reconstruction quality is ensured, and the application is easily expanded to large bandwidth multi-channel commercial spaceborne SAR application occasions. In particular, for scenes with sudden changes in the standard deviation of adjacent data blocks, serial calculation thresholds are forced to be used before quantization compression, which improves the quantization precision and maintains the compression consistency. In addition, right shift operation is preferentially used to quickly solve the mean value, and the standard deviation of the data block is determined based on the pre-stored mapping table of the mean value, which further optimizes the calculation process.

Description

Technical Field

[0001] This invention relates to the field of broadband multichannel radar technology in spaceborne applications, and specifically to a resource-saving commercial spaceborne broadband SAR data compression method and apparatus. Background Technology

[0002] Synthetic Aperture Radar (SAR) is an active microwave remote sensing sensor whose Earth observation is not limited by lighting or weather conditions, enabling all-day, all-weather Earth observation. It can even penetrate the Earth's surface and vegetation to obtain subsurface information. Therefore, it can be widely used in many disciplines and fields such as surveying, meteorology, land resource exploration, disaster monitoring and environmental protection, national defense, energy, transportation, and engineering. Wideband SAR radar, with its advantages of strong anti-jamming performance, ability to detect hidden targets, and extremely high range resolution, has become the mainstream trend in its development.

[0003] Wideband SAR radar has significant advantages due to its use of large time-bandwidth product signals as transmitted waveforms. However, in commercial spaceborne SAR systems, satellite storage capacity and downlink transmission bandwidth are limited, necessitating data compression of the raw SAR radar data. Block Adaptive Quantization (BAQ) algorithms are widely used in commercial spaceborne SAR due to their simplicity and ease of implementation. However, traditional BAQ algorithms, when dividing the raw echo data into blocks, simultaneously use r*d data points in both the azimuth and range directions as the calculation unit for the first step of the data compression averaging algorithm. This means that all waveform data for r cycles needs to be stored before calculation. This approach not only consumes substantial storage resources but also wastes data processing time.

[0004] Therefore, it is of great significance to study resource-saving commercial spaceborne broadband SAR data compression methods and devices. Summary of the Invention

[0005] (a) Technical problems to be solved To address the shortcomings of existing technologies, this invention provides a resource-saving commercial spaceborne broadband SAR data compression method and apparatus, resolving the contradiction between the high bandwidth and multi-channel application requirements of radar and the limited storage capacity of satellite logic processors.

[0006] (II) Technical Solution To achieve the above objectives, the present invention provides the following technical solution: In a first aspect, the present invention provides a resource-saving commercial spaceborne broadband SAR data compression method, comprising: The echo signal is received, and an n-bit baseband digital signal is generated through analog-to-digital conversion and preprocessing; wherein the baseband digital signal is composed of multiple discrete samples. The I and Q channels of the baseband digital signal are synchronously divided into multiple data blocks of size 1*d; where 1*d means that the azimuth direction of the data block is fixed as 1 pulse and the range direction contains d consecutive samples; Symmetrical processing of I-channel and Q-channel digital signals, performing the following operations on each data block on each channel: Calculate the mean of the d samples within the current data block; Determine the standard deviation of the current data block based on the mean; Based on the minimum mean square error criterion, the optimal quantization threshold of the block-optimal quantizer is calculated using the standard deviation of the current data block. This optimal quantization threshold is then used to compress the current data block, encoding each sample's n-bit signal into m bits; where m... <n; Each compressed data block is appended with a header information, packaged according to the protocol format, and transmitted back to the satellite platform; wherein the header information includes at least one of the following: compression encoding type, sample bit length, source from I or Q channel, block size, mean and standard deviation of each data block, and data packet length.

[0007] Preferably, after receiving the echo signal, the echo signal is down-converted to an intermediate frequency by mixing, and then sampled at high speed by an analog-to-digital converter to generate a digital echo signal.

[0008] Preferably, the preprocessing includes: The digitized echo signal is sent into the FPGA to perform one or more of the following preprocessing steps: fractional delay, digital demodulation, decimation filtering, and predistortion compensation, to form a baseband digital signal.

[0009] Preferably, each data block contains at least 32 consecutive samples in the distance direction.

[0010] Preferably, the mean of d samples within the current data block is calculated using a right shift operation.

[0011] Preferably, the standard deviation of the current data block is determined using a mean pre-stored mapping table based on the mean.

[0012] Secondly, the present invention provides a resource-saving commercial spaceborne broadband SAR data compression device, comprising: The signal conversion and preprocessing module is used to receive the echo signal, and generate an n-bit baseband digital signal through analog-to-digital conversion and preprocessing; wherein the baseband digital signal is composed of multiple discrete samples. The data segmentation module is used to synchronously divide the I and Q channels of the baseband digital signal into multiple data blocks of size 1*d; where 1*d means that the azimuth direction of the data block is fixed as 1 pulse and the range direction contains d consecutive samples; The data processing module is used for symmetrical processing of I-channel and Q-channel digital signals. For each data block on each channel, the following sub-modules perform corresponding operations: The mean calculation submodule is used to calculate the mean of d samples within the current data block; The standard deviation calculation submodule is used to determine the standard deviation of the current data block based on the mean. The quantization calculation submodule is used to calculate the optimal quantization threshold of the block-optimal quantizer based on the minimum mean square error criterion and the standard deviation of the current data block, and to compress the current data block using the optimal quantization threshold to encode the n-bit signal of each sample into m bits; where m <n; The data packaging submodule is used to attach header information to each compressed data block, package it according to the protocol format, and transmit it back to the satellite platform; wherein the header information includes at least one of the following: compression encoding type, sample bit length, source from I or Q channel, block size, mean and standard deviation of each data block, and data packet length.

[0013] A storage medium storing a computer program, wherein the computer program causes a computer to perform the commercial spaceborne broadband SAR data compression method described above.

[0014] An electronic device, comprising: One or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the programs including methods for performing commercial spaceborne broadband SAR data compression as described above.

[0015] (III) Beneficial Effects This invention provides a resource-saving commercial spaceborne broadband SAR data compression method and apparatus. Compared with the prior art, it has the following advantages: In this invention, the I / Q dual-path of the echo signal is divided into data blocks consisting of continuous samples. After buffering the continuous samples contained in a single data block for each pulse cycle, subsequent threshold calculation and quantization compression processing can be performed with almost no waiting time. Furthermore, a block-by-block independent serial processing method is adopted, where statistical parameter solving, optimal quantization threshold calculation, and quantization compression operations are performed independently for each data block. Each data block generates its own exclusive quantization threshold based on its own signal characteristics, eliminating the need to reuse parameters from historical data blocks. This method, through the synergistic optimization of the block division method and adaptive quantization architecture, effectively optimizes processing latency and improves the utilization efficiency of computing units. While ensuring image reconstruction quality, it achieves dual savings in storage and time resources, and is easily scalable to high-bandwidth, multi-channel commercial spaceborne SAR applications. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of a 32*32 block data flow in the conventional BAQ algorithm; Figure 2 A block diagram illustrating a resource-saving commercial spaceborne broadband SAR data compression method provided in an embodiment of the present invention; Figure 3 A flowchart illustrating a resource-saving commercial spaceborne broadband SAR data compression method provided in this embodiment of the invention; Figure 4 A schematic diagram of the BAQ algorithm 1*32 block data stream provided in an embodiment of the present invention; Figure 5 A flowchart illustrating the workflow of the BAQ algorithm provided in this embodiment of the invention; Figure 6 Example images for commercial spaceborne SAR imaging using the resource-saving commercial spaceborne broadband SAR data compression method provided in this embodiment of the invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are described clearly and completely. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] This application provides a resource-saving commercial spaceborne broadband SAR data compression method and apparatus, resolving the contradiction between the high bandwidth and multi-channel application requirements of radar and the limited storage capacity of satellite logic processors, thereby achieving dual savings in satellite storage resources and time resources.

[0020] The technical solution in this application is to solve the above-mentioned technical problems, and the general idea is as follows: In conventional methods, if the block size is 32 x 32, it means the BAQ algorithm module needs to wait for all 32 pulse cycles of echo data in the azimuth direction to be buffered before it can proceed. In the module implementation, ping-pong caching technology is used, employing two dual-port RAMs (Random Access Memory), each capable of storing a maximum of 32 pulse data cycles. Once one RAM is full with 32 cycles of data, the subsequent echo data is written to the other RAM, while simultaneously compressing the echo data in that RAM. If the data volume per cycle for a single channel is 25600, the required RAM storage depth (8 bits each for I and Q) is 32 * 2 * 25600 = 1638400, or 25 Mb. In multi-channel applications, resource consumption increases proportionally. For 8 channels, the required RAM resources are 200 Mb. Domestically produced programmable logic devices that meet these requirements lack spaceborne aerospace experience and radiation resistance, posing a significant challenge to project development and research design.

[0021] like Figure 1 As shown, Figure 1 A schematic diagram of the 32*32 block data flow for the conventional BAQ algorithm is disclosed. Here, PRF represents the number of pulses emitted per second by the radar system, dep represents the dimensionality of each data block, and 32*sample depth indicates that each data block contains 32 consecutive sample data points in the range direction. It is evident that this method not only requires enormous buffer resources but also wastes time because the FPGA (Field-Programmable Gate Array) cannot perform further processing during the waiting period. In other words, this method consumes significant storage resources and wastes data processing time, while the application requirements of commercial spaceborne SAR with its large bandwidth time-width product signals contradict the limited satellite storage capacity.

[0022] In response, this invention provides a resource-saving commercial spaceborne broadband SAR data compression method and apparatus, which is suitable for data compression processing of spaceborne broadband multi-channel radar signals. It can effectively reduce the time and storage resources required by the BAQ compression algorithm, and provide a technical foundation for the application and development of commercial spaceborne SAR large bandwidth signals.

[0023] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0024] Example 1: like Figure 2 As shown, this embodiment of the invention provides a resource-saving commercial spaceborne broadband SAR data compression method, including: S1. Receive the echo signal, and generate an n-bit baseband digital signal through analog-to-digital conversion and preprocessing; wherein the baseband digital signal is composed of multiple discrete samples; S2. The I and Q channels of the baseband digital signal are synchronously divided into multiple data blocks of size 1*d; where 1*d means that the azimuth direction of the data block is fixed as 1 pulse and the range direction contains d consecutive samples; S3. Symmetrically process the I and Q digital signals, and perform the following operations on each data block on each channel: S31. Calculate the mean of d samples within the current data block; S32. Determine the standard deviation of the current data block based on the mean; S33. Based on the minimum mean square error criterion, calculate the optimal quantization threshold of the block-optimal quantizer using the standard deviation of the current data block, and compress the current data block using the optimal quantization threshold to encode each sample's n-bit signal into m bits; where m <n; S4. Add header information to each compressed data block, package it according to the protocol format, and transmit it back to the satellite platform; wherein the header information includes at least one of the following: compression encoding type, sample bit length, source from I or Q channel, block size, mean and standard deviation of each data block, and data packet length.

[0025] The embodiments of the present invention optimize the block-based approach and parallel processing architecture in a coordinated manner, thereby improving the utilization rate of computing units and reducing processing latency. While ensuring reconstruction quality, it achieves dual savings in storage and time resources, and is easily scalable to commercial spaceborne SAR applications with high bandwidth and multiple channels.

[0026] like Figure 3 As shown, Figure 3 A flowchart of a resource-saving commercial spaceborne broadband SAR data compression method provided by an embodiment of the present invention is disclosed.

[0027] Next, we will combine Figure 3 The steps of the above scheme are described in detail: In step S1, the echo signal is received, and an n-bit baseband digital signal is generated through analog-to-digital conversion and preprocessing; wherein the baseband digital signal is composed of multiple discrete samples.

[0028] like Figure 3 As shown, this step utilizes the receiving channel to receive the (RF) echo signal and performs analog-to-digital conversion using the analog-to-digital converter (AD) within the high-speed acquisition module. Preprocessing is then performed using the programmable logic chip (FPGA) within the high-speed acquisition module (the FPGA is also used in subsequent processing steps). It is understood that both the receiving channel and the high-speed acquisition module are hardware modules.

[0029] Specifically, this step includes: After receiving the echo signal, the echo signal is down-converted to an intermediate frequency by mixing, and then sampled at high speed by an analog-to-digital converter to generate a digital echo signal.

[0030] The digitized echo signal is then fed into the FPGA to perform preprocessing such as fractional delay, digital demodulation, decimation filtering, and predistortion compensation to form a baseband digital signal. It should be noted that the baseband digital signal here is a complex signal, composed of multiple discrete samples, each sample including an n-bit real part (I-channel) digital signal and an n-bit imaginary part (Q-channel) digital signal.

[0031] In step S2, the I and Q channels of the baseband digital signal are synchronously divided into multiple data blocks of size 1*d; where 1*d means that the azimuth direction of the data block is fixed as 1 pulse and the range direction contains d consecutive samples.

[0032] It should be noted that the choice of block size in data partitioning should follow these principles: the block must be small enough to ensure that the mean squared error input level (standard deviation) of the SAR data in each block is constant; at the same time, the data block must be large enough to ensure the Gaussian distribution characteristics of the data within the block so as to effectively estimate the variance of each block.

[0033] Therefore, this step utilizes the FPGA's own BRAM resources to buffer and divide the baseband digital signal of the current cycle into blocks. The block size is set to 1*d, where 1*d represents that the azimuth direction of the data block is fixed at 1 pulse, the range direction contains d consecutive samples, and d is at least 32.

[0034] For example, when d is 32, such as Figure 4 As shown, Figure 4 A schematic diagram of a 1*32 block data stream using the BAQ algorithm provided in an embodiment of the present invention is disclosed. Thus, only 32 data samples need to be buffered per pulse cycle, allowing subsequent data compression calculations to be performed with almost no waiting time, greatly improving data processing efficiency.

[0035] In step S3, the I-channel and Q-channel digital signals are processed symmetrically, such as... Figure 5 As shown (both I-channel and Q-channel digital signals are n bits), perform the following operations on each data block on each channel: S31. Calculate the mean of d samples within the current data block.

[0036] Experiments with existing commercial spaceborne SAR raw data revealed that the mean of each data block is not equal to zero, exhibiting significant bias. Therefore, the BAQ algorithm was improved as follows through standardization: In the processing, the mean of the d samples in each data block is removed to ensure the final data follows a zero-mean distribution. It's important to note that a right shift operation is preferred over traditional division for faster mean calculation. Continuing with the example above, if the block size is 1*32=2... 5 Then, the mean can be quickly obtained by shifting it 5 bits to the right.

[0037] S32. Determine the standard deviation of the current data block based on the mean.

[0038] To simplify the calculation and avoid directly calculating the standard deviation of each block of the original input data. It can be derived from the mean of the absolute values ​​of the input data amplitudes. It can be estimated directly.

[0039] For example, a mean pre-stored mapping table is constructed in advance. After obtaining the mean, the standard deviation of the current data block is determined by using the mean pre-stored mapping table.

[0040] Therefore, the standardized blocks strictly satisfy the zero mean and Gaussian distribution of standard deviation, which meets the input requirements of the BAQ algorithm.

[0041] S33. Based on the minimum mean square error (MMSE) criterion, calculate the optimal quantization threshold of the block-optimal quantizer using the standard deviation of the current data block, and compress the current data block using the optimal quantization threshold to encode each sample's n-bit signal into m bits; where m <n。

[0042] The block-optimal quantizer is a block-by-block adaptive scalar quantizer that strictly follows the minimum mean square error criterion. It calculates the optimal quantization threshold based on the signal statistical characteristics of the current independent data block and uses this optimal quantization threshold as the quantization decision threshold. It compares each input sample data with the optimal quantization threshold one by one to complete the sample quantization mapping and output the corresponding quantization result. Each data block independently generates its own quantization threshold, realizing adaptive quantization compression that adapts to the dynamic characteristics of a single block signal.

[0043] It should be noted that the data compression process in this embodiment of the invention adopts a serial, block-by-block independent processing method, and there is no cross-block parameter association or threshold reuse mechanism.

[0044] Specifically, the mean, standard deviation, and optimal quantization threshold of each data block are calculated independently based on the data within their own block. There is no correlation between different data blocks in terms of parameter inheritance, parameter comparison, or threshold reuse. The quantization compression process of each data block is independent of each other and is completed entirely based on the signal characteristics of the current data block to achieve adaptive quantization. This effectively avoids the problems of poor quantization adaptability and error accumulation caused by the reuse of historical block parameters in traditional block adaptive quantization algorithms, and significantly improves the quantization accuracy and signal adaptability of each data block.

[0045] In step S4, each compressed data block is appended with packet header information, packaged according to the protocol format, and transmitted back to the satellite platform; wherein the packet header information includes at least one of the following: compression encoding type, sample bit length, source from I or Q channel, block size, mean and standard deviation of each data block, and data packet length.

[0046] To facilitate decompression of compressed data at the ground station, the preferred header information includes: sample bit depth, source from I or Q channel, block size, mean and standard deviation of each data block, and data packet length.

[0047] This concludes the detailed description of the complete process of a commercial spaceborne broadband SAR data compression method in this invention. This method is easily extended to high-bandwidth, multi-channel commercial spaceborne SAR applications, such as… Figure 6 As shown, Figure 6 An image of commercial spaceborne SAR imaging using the BAQ algorithm according to an embodiment of the present invention is disclosed, showing that the image quality is good.

[0048] Example 2: This invention provides a resource-saving commercial spaceborne broadband SAR data compression device, comprising: The signal conversion and preprocessing module is used to receive the echo signal, and generate an n-bit baseband digital signal through analog-to-digital conversion and preprocessing; wherein the baseband digital signal is composed of multiple discrete samples. The data segmentation module is used to synchronously divide the I and Q channels of the baseband digital signal into multiple data blocks of size 1*d; where 1*d means that the azimuth direction of the data block is fixed as 1 pulse and the range direction contains d consecutive samples; The data processing module is used for symmetrical processing of I-channel and Q-channel digital signals. For each data block on each channel, the following sub-modules perform corresponding operations: The mean calculation submodule is used to calculate the mean of d samples within the current data block; The standard deviation calculation submodule is used to determine the standard deviation of the current data block based on the mean. The quantization calculation submodule is used to calculate the optimal quantization threshold of the block-optimal quantizer based on the minimum mean square error criterion and the standard deviation of the current data block, and to compress the current data block using the optimal quantization threshold to encode the n-bit signal of each sample into m bits; where m <n; The data packaging module is used to attach header information to each compressed data block, package it according to the protocol format, and transmit it back to the satellite platform; wherein the header information includes at least one of the following: compression encoding type, sample bit length, source from I-channel or Q-channel, block size, mean and standard deviation of each data block, and data packet length.

[0049] Example 3: This invention provides a storage medium storing a computer program that causes a computer to execute the commercial spaceborne broadband SAR data compression method as described in Embodiment 1.

[0050] Example 4: This invention provides an electronic device, comprising: One or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the programs including methods for performing a commercial spaceborne broadband SAR data compression method as described in Example 1.

[0051] It is understood that the resource-saving commercial spaceborne broadband SAR data compression device, storage medium and electronic device provided in the embodiments of the present invention correspond to the resource-saving commercial spaceborne broadband SAR data compression method provided in the embodiments of the present invention. The explanation, examples and beneficial effects of the relevant contents can be referred to the corresponding parts of the method, and will not be repeated here.

[0052] In summary, compared with existing technologies, it has the following beneficial effects: 1. The embodiments of the present invention optimize the block-based approach and parallel processing architecture in a coordinated manner, thereby improving the utilization rate of computing units and reducing processing latency. While ensuring the quality of image reconstruction, it achieves dual savings in storage and time resources, and is easy to extend to commercial spaceborne SAR applications with high bandwidth and multiple channels.

[0053] 2. The embodiments of the present invention further optimize the calculation process: We prioritize right shift operations to replace traditional division for faster calculation of the mean.

[0054] The standard deviation of data blocks is determined by pre-stored mean mapping tables, avoiding complex real-time calculations.

[0055] 3. In the case of a sudden change in the standard deviation of adjacent data blocks, the embodiments of the present invention force the use of serial calculation of thresholds before quantization and compression, thereby improving quantization accuracy and maintaining compression consistency.

[0056] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0057] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A resource-saving commercial spaceborne broadband SAR data compression method, characterized in that, include: The echo signal is received, and an n-bit baseband digital signal is generated through analog-to-digital conversion and preprocessing. The baseband digital signal is composed of multiple discrete samples; The I and Q channels of the baseband digital signal are synchronously divided into multiple data blocks of size 1*d; wherein 1*d indicates that the azimuth direction of the data block is fixed at 1 pulse, and the range direction contains d consecutive samples; Symmetrical processing of I-channel and Q-channel digital signals, performing the following operations on each data block on each channel: Calculate the mean of the d samples within the current data block; Determine the standard deviation of the current data block based on the mean; Based on the minimum mean square error criterion, the optimal quantization threshold of the block-optimal quantizer is calculated using the standard deviation of the current data block. This optimal quantization threshold is then used to compress the current data block, encoding each sample's n-bit signal into m bits; where m... <n; Each compressed data block is appended with a header information, packaged according to the protocol format, and transmitted back to the satellite platform; wherein the header information includes at least one of the following: compression encoding type, sample bit length, source from I or Q channel, block size, mean and standard deviation of each data block, and data packet length.

2. The commercial spaceborne broadband SAR data compression method as described in claim 1, characterized in that, After receiving the echo signal, the echo signal is down-converted to an intermediate frequency by mixing, and then sampled at high speed by an analog-to-digital converter to generate a digital echo signal.

3. The commercial spaceborne broadband SAR data compression method as described in claim 1, characterized in that, The preprocessing includes: The digitized echo signal is sent into the FPGA to perform one or more of the following preprocessing steps: fractional delay, digital demodulation, decimation filtering, and predistortion compensation, to form a baseband digital signal.

4. The commercial spaceborne broadband SAR data compression method as described in claim 1, characterized in that, Each data block contains at least 32 consecutive samples in the distance direction.

5. The commercial spaceborne broadband SAR data compression method as described in claim 1, characterized in that, The mean of d samples within the current data block is calculated using a right shift operation.

6. The commercial spaceborne broadband SAR data compression method as described in claim 1, characterized in that, Based on the mean, the standard deviation of the current data block is determined using a mean pre-stored mapping table.

7. A resource-saving commercial spaceborne broadband SAR data compression device, characterized in that, include: The signal conversion and preprocessing module is used to receive the echo signal and generate an n-bit baseband digital signal through analog-to-digital conversion and preprocessing. The baseband digital signal is composed of multiple discrete samples; The data block module is used to synchronously divide the I and Q channels of the baseband digital signal into multiple data blocks of size 1*d. Where 1*d represents that the azimuth direction of the data block is fixed at 1 pulse, and the range direction contains d consecutive samples; The data processing module is used for symmetrical processing of I-channel and Q-channel digital signals. For each data block on each channel, the following sub-modules perform corresponding operations: The mean calculation submodule is used to calculate the mean of d samples within the current data block; The standard deviation calculation submodule is used to determine the standard deviation of the current data block based on the mean. The quantization calculation submodule is used to calculate the optimal quantization threshold of the block-optimal quantizer based on the minimum mean square error criterion and the standard deviation of the current data block, and to compress the current data block using the optimal quantization threshold to encode the n-bit signal of each sample into m bits; where m <n; The data packaging module is used to attach header information to each compressed data block, package it according to the protocol format, and transmit it back to the satellite platform; wherein the header information includes at least one of the following: compression encoding type, sample bit length, source from I-channel or Q-channel, block size, mean and standard deviation of each data block, and data packet length.

8. A storage medium, characterized in that, It stores a computer program, wherein the computer program causes a computer to perform the commercial spaceborne broadband SAR data compression method as described in any one of claims 1 to 6.

9. An electronic device, characterized in that, include: One or more processors; Memory; And one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the programs including methods for performing the commercial spaceborne broadband SAR data compression method as described in any one of claims 1 to 6.

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