Radar echo data processing method and system for improving signal-to-noise ratio

Abstract

The invention provides a radar echo data processing method and system for improving a signal-to-noise ratio, and the method comprises the steps: S10, obtaining original echo data for an imaging scene radar; s20, performing azimuth windowing processing on the original echo data to obtain echo data after azimuth windowing processing; s30, performing azimuth compression processing on the echo data after azimuth windowing processing to obtain echo data after azimuth compression processing; s40, azimuth accumulation processing is carried out on the echo data after azimuth compression processing according to rows, so that the final azimuth is a column of data, and the echo data after azimuth accumulation processing is obtained; and S50, performing range compression processing on the echo data after the azimuth accumulation processing to obtain the echo data after the range compression processing. According to the method for accumulating the N-dimensional azimuth data into the one-dimensional azimuth data, the signal-to-noise ratio can be increased by N times, and meanwhile the data size is reduced to be N times that of original echo data.

Description

Technical Field

[0001] The present invention relates to the field of radar echo data, and in particular to a radar echo data processing method and system for improving a signal-to-noise ratio. Background Art

[0002] As an advanced earth observation system, Synthetic Aperture Radar (SAR) is widely used in military reconnaissance, geological exploration, environmental monitoring and other fields. The SAR system forms a high-resolution two-dimensional image by emitting electromagnetic waves and receiving echo signals reflected by the target.

[0003] However, the processing of SAR echo signals faces some inherent challenges. According to the working principle of synthetic aperture radar, the SAR echo signal is a complex two-dimensional data set containing multi-directional and distance features. This data set is not only complex in structure, but also usually contains a large amount of noise signals, resulting in a generally low signal-to-noise ratio of the radar signal. Low signal-to-noise ratio will have a significant impact on the performance of the SAR system, especially in key applications such as target detection, tracking and imaging, which may lead to problems such as reduced image quality and reduced target recognition accuracy.

[0004] Existing SAR signal processing methods usually include a series of processing on the original echo data, such as azimuth processing and range processing, etc. However, these traditional methods still have limitations in improving the signal-to-noise ratio, especially in complex environments or weak target situations, and their effects are often unsatisfactory.

[0005] Therefore, it is of great practical significance to develop a data processing method that can effectively improve the signal-to-noise ratio of the SAR system. Summary of the invention

[0006] In view of this, an object of an embodiment of the present invention is to provide a radar echo data processing method and system for improving the signal-to-noise ratio, so as to solve the above technical problems.

[0007] In a first aspect, an embodiment of the present invention provides a radar echo data processing method for improving a signal-to-noise ratio, the method comprising:

[0008] Obtain the original echo data of the radar;

[0009] Performing azimuth windowing processing on the original echo data to obtain azimuth windowed echo data;

[0010] Performing azimuth compression processing on the echo data after the azimuth windowing processing to obtain azimuth compressed echo data;

[0011] Performing azimuth accumulation processing on the echo data after azimuth compression processing row by row, so that the final azimuth is a column of data, thereby obtaining echo data after azimuth accumulation processing;

[0012] The echo data after the azimuth accumulation processing is subjected to range compression processing to obtain echo data after the range compression processing.

[0013] In a second aspect, an embodiment of the present invention provides a radar echo data processing system for improving a signal-to-noise ratio, the system comprising:

[0014] The original echo data acquisition module is used to obtain the original echo data for the imaging scene radar;

[0015] An azimuth windowing processing module is used to perform azimuth windowing processing on the original echo data to obtain echo data after azimuth windowing processing;

[0016] An azimuth compression processing module, used for performing azimuth compression processing on the echo data after the azimuth windowing processing to obtain the echo data after the azimuth compression processing;

[0017] An azimuth accumulation processing module, used for performing azimuth accumulation processing on the echo data after azimuth compression processing row by row, so that the final azimuth is a column of data, thereby obtaining the echo data after azimuth accumulation processing;

[0018] The range compression processing module is used to perform range compression processing on the echo data after the azimuth accumulation processing to obtain the echo data after the range compression processing.

[0019] The above technical solution has the following beneficial effects:

[0020] In order to increase the signal-to-noise ratio of the echo signal and improve the data processing rate, the embodiment of the present invention first multiplies the echo signal by the azimuth filter coefficient, and then performs the step of azimuth data accumulation, so that the amplitude of the processed data is close to the original data, but is compressed into only one column of data in the azimuth direction, and then the processed data is subjected to distance compression processing, thereby reducing the amount of data in the memory and improving the calculation efficiency and transmission efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0022] Figure 1is a flow chart of a radar echo data processing method for improving the signal-to-noise ratio according to an embodiment of the present invention;

[0023] Figure 2 is a diagram showing a data structure change process of the azimuth compression processing process in step S30 of an embodiment of the present invention;

[0024] Figure 3 FIG. 1 is a diagram showing a data structure change process of the azimuth accumulation process in step S40 of an embodiment of the present invention.

[0025] Figure 4 is a diagram showing a data structure change process in a distance compression process in step S50 of an embodiment of the present invention;

[0026] Figure 5 is a schematic diagram of a data arrangement method in an example of an embodiment of the present invention;

[0027] Figure 6 is a schematic diagram of signal-to-noise ratio comparison of an echo signal in an example of an embodiment of the present invention;

[0028] Figure 7 is a functional block diagram of a radar echo data processing system for improving a signal-to-noise ratio according to an embodiment of the present invention;

[0029] Figure 8 It is a functional block diagram of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] The embodiment of the present invention can improve the signal-to-noise ratio of radar echo data, and the method can be applied to any radar system that generates echo signals, including imaging scene radars and non-imaging scene radars. The embodiment of the present invention proposes a method based on accumulating N-dimensional azimuth data into one dimension, which can improve the signal-to-noise ratio by N times and reduce the data size to N times of the original echo data.

[0032] Although the embodiments of the present invention are mainly described in detail with respect to a SAR system, those skilled in the art should understand that the methods of the embodiments of the present invention can also be applied to other types of radar systems, such as pulse Doppler radar, continuous wave radar, phased array radar, meteorological radar, geological exploration radar, etc.

[0033] Embodiment 1

[0034] In order to increase the signal-to-noise ratio of the echo signal and improve the data processing rate, the embodiment of the present invention first multiplies the echo signal by the azimuth filter coefficient, and then performs the step of azimuth data accumulation, so that the amplitude of the processed data is close to the original data, but is compressed into only one column of data in the azimuth direction, and then the processed data is subjected to distance compression processing, thereby reducing the amount of data in the memory and improving the calculation efficiency and transmission efficiency.

[0035] like Figure 1 As shown in the figure, the echo processing flow includes the following steps:

[0036] Step S10: For a certain imaging scene radar, the original echo data Data(n) is obtained:

[0037] Data(n)=S(n)+w(n).

[0038] Where n is used to mark the sampling point position of the echo data, that is, a discrete time index. S(n) = Ae jφ represents the ideal component of the signal, which is the echo signal of the target, where j is an imaginary unit, φ is the phase angle of the echo signal, and A represents the amplitude of the echo signal, which reflects the strength of the echo signal and is related to factors such as the reflection characteristics and distance of the target. w(n) represents the noise component, which is random.

[0039] If the power of the original signal is A 2 , the size of the echo data is Na*Nr, Nr corresponds to the number of range directions, Na corresponds to the number of azimuth directions, and the power of the noise signal is Then the signal-to-noise ratio of the overall echo signal is:

[0040]

[0041] Step S20: To facilitate the subsequent FFT (Fast Fourier Transform) processing, the original echo data needs to be processed by adding a Hamming window in azimuth direction. The calculation method of adding a Hamming window in azimuth direction is as follows:

[0042]

[0043] Among them, Data H (n) represents the data processed by the window function, that is, the echo data after azimuth windowing. Ham(n) represents the time domain expression of the Hamming window. M represents the length of the window. If the entire data is completely windowed, M=n.

[0044] It should be noted that there are many ways to add windows, not limited to the Hamming window. The main purpose of adding windows is to reduce spectrum leakage and improve the accuracy and effect of signal processing. Windowing controls edge effects by weighting the original signal. The expression corresponding to the Hamming window is fixed, and the parameters and constants cannot be modified. If other window function formulas are used, the corresponding parameters can be deformed or changed. Any window can be used for windowing. This embodiment is not limited to the use of the Hamming window. As long as the essence is to reduce leakage, any processing method can be used.

[0045] Step S30: Perform azimuth compression processing on the echo data after azimuth windowing processing, such as Figure 2 Azimuth compression refers to the compression of the azimuth signal in the echo data after azimuth windowing by using an azimuth filter. The received echo signal itself is a two-dimensional echo signal. One dimension represents the distance dimension, which is called the distance signal, and the other dimension represents the azimuth dimension, which is called the azimuth signal. Figure 2 The calculation method of azimuth compression processing is as follows:

[0046] Data a (n)=ifft(fft(Data H (n)*Ha(fa));

[0047]

[0048] Among them, Data a (n) is the data result after azimuth compression, Ha(fa) is the azimuth filter, fa is the Doppler frequency, Ka is the azimuth modulation frequency, the value of this parameter can be directly obtained according to the set value at the time of transmission, or it can be obtained by the formula Ka=2v 2 / (λR0) approximate estimation, V is the flight speed of the radar platform, λ is the wavelength of the radar signal, and R0 is the slant distance from the target to the radar platform. fft{} is the FFT transformation operation on the data, and ifft{} is the inverse FFT transformation operation on the data. H In the figure, the subscript H is added to distinguish and indicate that the data has changed. The subscript H is the abbreviation of the Hamming window.

[0049] Among them, the azimuth filter is a very important part of the synthetic aperture radar (SAR) imaging process, which is used to process the azimuth direction of the echo signal. The core principle of SAR imaging is to use the movement of the radar platform to synthesize a longer "synthetic aperture" to improve the resolution in the azimuth direction. And the azimuth filter is in this process, by matching the azimuth data to concentrate the energy of the target on a single pixel position in the image.

[0050] Among them, the azimuth FM rate is an important concept involved in synthetic aperture radar (SAR) signal processing, which reflects the rate of change of the phase of the received signal caused by the relative motion between the radar platform and the ground target during the synthetic aperture process. This FM rate directly affects the azimuth resolution and focusing accuracy of SAR imaging, and is a key parameter in SAR imaging.

[0051] Among them, the fast Fourier transform (FFT) and its inverse transform (IFFT) are efficient algorithms for implementing the discrete Fourier transform (DFT) and the inverse discrete Fourier transform (IDFT), but this does not mean that DFT and IDFT can only be implemented through FFT. In fact, there are many alternative implementations to implement the Fourier transform and its inverse transform, such as: (1) direct calculation of DFT / IDFT; (2) fast cosine transform (Fast Cosine Transform, FCT) and fast sine transform (Fast Sine Transform, FST); (3) short-time Fourier transform (STFT); (4) discrete wavelet transform; (5) Hilbert transform; (6) singular value decomposition (Singular Value Decomposition, SVD) and eigenvalue decomposition; (7) time domain convolution as an alternative to frequency domain multiplication, etc.

[0052] exist Figure 2 middle, Figure 2 The data structure of step S30 is shown as a whole. The left figure shows the matrix of two-dimensional echoes, the middle figure shows the multiplier, and the long bar in the right figure shows the azimuth filter. Figure 2 , Figure 3 , Figure 4 These are all graphs drawn to clearly understand the data structure changes during the processing process.

[0053] Step S40: The processed data is accumulated row by row, so that the final data is a column of data. Figure 3 , the cumulative calculation method is as follows:

[0054]

[0055] Among them, sumData is the data result after azimuth accumulation, It means that after accumulating the distance data, a distance data sumData is obtained.

[0056] The dimension of the data after azimuth accumulation is Nr×1. The azimuth data at this time is obtained after accumulation. The power of the signal component at this time is A 2 remains unchanged, but only one column of data is retained in the azimuth of the echo. The noise power at this time is It's the original power times, the signal-to-noise ratio of the echo signal will be improved by Na times, and the expression of the signal-to-noise ratio of the echo signal is:

[0057]

[0058] Step S50: Perform range compression on the processed signal to obtain processed echo data. The processing process is as follows: Figure 4 , Figure 4 The calculation method for mid-range compression processing is as follows:

[0059] S data =ifft(fft(sumData.*Hr(fr));

[0060]

[0061] Among them, S data It is the processing result after range compression, Hr(fr) is the range filter, fr is the frequency set in the range, Kr is the pulse frequency modulation slope, and the Kr value is equal to the k in the transmission wave formula. It is called Kr to distinguish it from KA, and r is the abbreviation of range.

[0062] Among them, the main function of the range filter is to perform range compression (RangeCompression) on the echo signal, thereby improving the resolution in the range direction. The SAR system illuminates by transmitting a linear frequency modulation signal, which causes the received echo signal to also contain this linear frequency modulation characteristic. Through matched filtering processing with the original transmitted signal, the energy of the target can be gathered in the range direction, preparing for high-resolution imaging. The function of the range filter is the same as that of the azimuth filter. The main purpose is to filter the signal in two different dimensions, the range direction and the azimuth direction.

[0063] The range frequency set is a set of frequency components used to describe the spectrum characteristics of the target in the range direction in synthetic aperture radar (SAR) processing. It reflects the frequency components and characteristics of the target echo signal in the range direction. In the range processing process of SAR imaging, the frequency set is used to analyze and process the range information of the echo signal.

[0064] Specifically, the frequency set in the range direction is not a fixed constant, but depends on multiple factors, including the frequency characteristics of the transmitted signal, the distance of the target, the motion state of the platform, etc. The frequency components in the frequency set in the range direction reflect the distribution characteristics of the target in the range direction. In actual calculations, it should be a set of matrix data, and the data is complex.

[0065] Specifically, the main source of the frequency set in the range direction is the result of the echo signal after Fourier transform. The following are the specific steps to obtain the frequency set in the range direction: the SAR system transmits a linear frequency modulation signal, the frequency of which increases or decreases linearly with time. After encountering the target, the transmitted signal is reflected and returned to the receiving antenna. Due to the different distances of the target, the time delay of the echo signal is also different. The echo signal is matched filtered (implemented in the range direction) to focus the target echo in the range direction. The matched filtered signal is Fourier transformed to convert the signal from the time domain to the frequency domain to obtain the spectrum. The frequency component set obtained at this time is the frequency set in the range direction. Each frequency component in the frequency set corresponds to the echo of a specific target in the range direction, which can be used for target detection, imaging and analysis.

[0066] The following are some application examples:

[0067] The original echo data is arranged in two dimensions, with the size of range × azimuth being Nr = 32768, Na = 32768, and each sampling point is a single-precision floating point complex type (size is 8 Byte), so the memory needs to store 8 GByte of data. After accumulating Na range data, a range data is obtained, and the memory only needs to store 0.25 MByte of data, which is 0.03051% of the original data. Compared with directly processing all the original echo data, the efficiency is increased by 32768 times, which greatly reduces the amount of data transmission. The data arrangement is as follows: Figure 5 shown.

[0068] like Figure 6 As shown, taking the rectangular signal adc_valid of N single pulses as an example, the amplitude of each single pulse signal is A, and the noise power contained is σ w 2 , the pulse signals of N cycles are accumulated together to obtain the signal sum_valid, maintaining the amplitude A unchanged, and the noise of each pulse at this time becomes 1 / N of the original. By calculating the signal-to-noise ratio of the echo signal at this time, it will be improved by N times. adc_valid is a signal used to indicate the validity of data during the analog-to-digital conversion process. After the signal is accumulated, it is named sum_valid.

[0069] The advantages of the above technical solution are:

[0070] Since the processed data are accumulated in the azimuth direction according to the range direction, the amount of processed data is reduced from Nr×Na to Nr×1, which significantly reduces the amount of calculation, reduces the requirements for the SAR system processor, and saves system storage space.

[0071] By accumulating Na azimuth data, the signal-to-noise ratio is increased by Na times, which can improve the performance of target detection and parameter estimation in the SAR system.

[0072] Embodiment 2

[0073] like Figure 7 As shown, this embodiment provides a radar echo data processing system 200 for improving the signal-to-noise ratio, and the system 200 includes:

[0074] The original echo data acquisition module 210 is used to obtain the original echo data for the imaging scene radar;

[0075] An azimuth windowing processing module 220 is used to perform azimuth windowing processing on the original echo data to obtain echo data after azimuth windowing processing;

[0076] An azimuth compression processing module 230 is used to perform azimuth compression processing on the echo data after the azimuth windowing processing to obtain the echo data after the azimuth compression processing;

[0077] An azimuth accumulation processing module 240 is used to perform azimuth accumulation processing on the echo data after the azimuth compression processing by row, so that the final azimuth is a column of data, thereby obtaining the echo data after the azimuth accumulation processing;

[0078] The range compression processing module 250 is used to perform range compression processing on the echo data after the azimuth accumulation processing to obtain echo data after the range compression processing.

[0079] In some embodiments, the raw echo data acquisition module 210 is specifically used to:

[0080] For imaging scene radar, the radar transmits a linear frequency modulation (Chirp) signal, which is a signal whose frequency changes with time. The frequency increases or decreases according to a linear law over a period of time. The Chirp signal can be described by the following formula:

[0081]

[0082] Among them, A is the amplitude of the signal, f0 is the initial frequency (a constant selected and set according to the radar band). K is the pulse frequency modulation slope, which determines the speed of frequency change, expressed as: K = B / T, where B is the bandwidth of the signal, that is, the total range of frequency change from the initial frequency to the final frequency, in Hertz (Hz), and T is the pulse duration, that is, the total length of the Chirp signal in time, in seconds (s). The unit of the frequency modulation slope is Hz / s, and the frequency modulation slope controls the frequency change of the linear frequency modulation signal. The larger the frequency modulation slope, the faster the frequency change and the wider the bandwidth, which usually means a higher distance resolution. t is the time data set, in seconds (s).

[0083] The original echo signal can be obtained by the reflection of the transmitted signal through the object. The discrete echo data Data(n) of the continuous time signal (i.e. analog signal) converted into the discrete time signal (i.e. digital signal) is expressed as:

[0084] Data(n)=S(n)+w(n);

[0085] Where n is used to mark the sampling point position of the original echo data; S(n) = Ae jφ Represents the ideal component of the original echo data of the target, where j is the imaginary unit, φ is the phase angle of the original echo data, A represents the amplitude of the original echo data; w(n) represents the noise signal.

[0086] In some embodiments, in the processing of the azimuth windowing processing module 220, the calculation method of the azimuth windowing processing is as follows:

[0087]

[0088] Among them, Data H (n) represents the echo data after azimuth windowing, Ham(n) represents the time domain expression of the Hamming window, M represents the length of the windowing, and if all sampling points of the original echo data Data(n) are completely windowed, then M=n.

[0089] In some embodiments, in the processing of the azimuth compression processing module 230, the azimuth compression processing refers to using an azimuth filter to process the azimuth signal in the echo data after the azimuth windowing processing, so that the azimuth signal is compressed. The calculation method of the azimuth compression processing is as follows:

[0090] Data a (n)=ifft(fft(Data H (n)*Ha(fa));

[0091]

[0092] Among them, Data a (n) is the echo data after azimuth compression processing, Ha(fa) is the azimuth filter, fa is the Doppler frequency, Ka is the azimuth modulation frequency, fft{} is the FFT transformation operation, and ifft{} is the inverse FFT transformation operation.

[0093] In some embodiments, in the processing of the azimuth accumulation processing module 240, the azimuth accumulation processing is calculated as follows:

[0094]

[0095] Among them, sumData is the data result after azimuth accumulation processing, It means that after accumulating the distance data, a distance data sumData is obtained.

[0096] In some embodiments, in the processing of the distance compression processing module 250, the distance compression processing is calculated as follows:

[0097] S data =ifft(fft(sumData*Hr(fr));

[0098]

[0099] Among them, S data is the echo data after range compression processing, Hr(fr) is the range filter, fr is the frequency set in the range, and Kr is the pulse frequency modulation slope.

[0100] In some embodiments, if the power of the original echo data is A 2 , the size of the original echo data is Na*Nr, Nr is the number of corresponding range directions, Na is the number of corresponding azimuth directions, and the power of the noise signal is Then the signal-to-noise ratio of the original echo data is:

[0101]

[0102] The data dimension after azimuth accumulation processing is Nr×1. The azimuth data at this time is obtained after accumulation. The power of the signal component at this time is A 2 remains unchanged, but only one column of data is retained in the azimuth direction of the echo data after azimuth accumulation processing. The power of the noise signal at this time is The signal-to-noise ratio of the echo data after the azimuth accumulation processing is:

[0103]

[0104] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0105] Embodiment 3

[0106] An embodiment of the present invention further provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, each step of the above-mentioned radar echo data processing method for improving the signal-to-noise ratio is implemented.

[0107] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. Of course, there are other ways of readable storage media, such as quantum memory, graphene memory, etc. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media does not include electrical carrier signals and telecommunication signals.

[0108] Embodiment 4

[0109] The embodiment of the present invention also provides a computer device, such as Figure 8 As shown, it includes one or more processors 301 , a communication interface 302 , a memory 303 and a communication bus 304 , wherein the processor 301 , the communication interface 302 , and the memory 303 communicate with each other via the communication bus 304 .

[0110] Memory 303, used for storing computer programs;

[0111] The processor 301 is used to implement the steps of the radar echo data processing method for improving the signal-to-noise ratio when executing the program stored in the memory 303.

[0112] The processor 301 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0113] The memory 303 may include a large capacity memory for data or instructions. For example, but not limitation, the memory 303 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape or a universal serial bus (USB) drive or a combination of two or more of these. In appropriate cases, the memory 303 may include a removable or non-removable (or fixed) medium. In a specific embodiment, the memory 303 is a non-volatile solid-state memory. In a specific embodiment, the memory 303 includes a read-only memory (ROM). In appropriate cases, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM) or a flash memory or a combination of two or more of these.

[0114] Communication bus 304 includes hardware, software or both, for coupling the above-mentioned components to each other.For example, bus may include accelerated graphics port (AGP) or other graphics bus, enhanced industrial standard architecture (EISA) bus, front side bus (FSB), hypertransport (HT) interconnection, industrial standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations.In suitable cases, bus may include one or more buses.Although the embodiment of the present invention describes and shows a specific bus, the present invention considers any suitable bus or interconnection.

[0115] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0116] Although the present application provides method operation steps such as embodiments or flow charts, more or fewer operation steps may be included based on conventional or non-creative labor. The order of steps listed in the embodiments is only one way of executing the order of many steps and does not represent the only execution order. When the actual device or client product is executed, it can be executed in the order of the method shown in the embodiments or the drawings or in parallel (for example, in a parallel processor or multi-threaded processing environment).

[0117] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0118] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0119] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0120] The present invention uses specific embodiments to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A radar echo data processing method for improving signal-to-noise ratio, characterized in that: The method comprises: Step S10: obtaining original echo data of the radar; Step S20: performing azimuth windowing processing on the original echo data to obtain azimuth windowed echo data; Step S30: performing azimuth compression processing on the echo data after the azimuth windowing processing to obtain azimuth compressed echo data; Step S40: performing azimuth accumulation processing on the echo data after azimuth compression processing row by row, so that the final azimuth is a column of data, thereby obtaining echo data after azimuth accumulation processing; Step S50: performing range compression processing on the echo data after the azimuth accumulation processing to obtain echo data after the range compression processing.

2. The radar echo data processing method for improving the signal-to-noise ratio according to claim 1, characterized in that: Step S10 specifically includes: For imaging scene radar, the original echo data Data(n) is obtained: Data(n)=S(n)+w(n); Where n is used to mark the sampling point position of the original echo data; S(n) = Ae jφ Represents the ideal component of the original echo data of the target, where j is the imaginary unit, φ is the phase angle of the original echo data, A represents the amplitude of the original echo data; w(n) represents the noise signal.

3. The radar echo data processing method for improving the signal-to-noise ratio according to claim 2, characterized in that: In step S20, the azimuth windowing process is calculated as follows: Among them, Data H (n) represents the echo data after azimuth windowing, Ham(n) represents the time domain expression of the Hamming window, M represents the length of the windowing, and if all sampling points of the original echo data Data(n) are completely windowed, then M=n.

4. The radar echo data processing method for improving the signal-to-noise ratio according to claim 3, characterized in that: In step S30, the azimuth compression processing refers to processing the azimuth signal in the echo data after the azimuth windowing processing by using an azimuth filter so that the azimuth signal is compressed. The calculation method of the azimuth compression processing is as follows: Data a (n)=ifft(fft(Data H (n)*Ha(fa)); Among them, Data a (n) is the echo data after azimuth compression processing, Ha(fa) is the azimuth filter, fa is the Doppler frequency, Ka is the azimuth modulation frequency, fft{} is the FFT transformation operation, and ifft{} is the inverse FFT transformation operation.

5. The radar echo data processing method for improving the signal-to-noise ratio according to claim 4, characterized in that: In step S40, the calculation method of the azimuth accumulation process is as follows: Among them, sumData is the data result after azimuth accumulation processing, It means that after accumulating the distance data, a distance data sumData is obtained.

6. The radar echo data processing method for improving the signal-to-noise ratio according to claim 5, characterized in that: In step S50, the distance compression process is calculated as follows: S data =ifft(fft(sumData*Hr(fr)); Among them, S data is the echo data after range compression processing, Hr(fr) is the range filter, fr is the frequency set in the range, and Kr is the pulse frequency modulation slope.

7. The radar echo data processing method for improving the signal-to-noise ratio according to claim 1, characterized in that: If the power of the original echo data is A 2 , the size of the original echo data is Na*Nr, Nr is the number of corresponding range directions, Na is the number of corresponding azimuth directions, and the power of the noise signal is Then the signal-to-noise ratio of the original echo data is: The data dimension after azimuth accumulation processing is Nr×1. The azimuth signal data at this time is obtained after accumulation. The power of the signal component at this time is A 2 remains unchanged, but only one column of data is retained in the azimuth direction of the echo data after azimuth accumulation processing. The power of the noise signal at this time is The signal-to-noise ratio of the echo data after the azimuth accumulation processing is:

8. A radar echo data processing system for improving signal-to-noise ratio, characterized in that: The system comprises: The original echo data acquisition module is used to obtain the original echo data for the imaging scene radar; An azimuth windowing processing module is used to perform azimuth windowing processing on the original echo data to obtain echo data after azimuth windowing processing; An azimuth compression processing module, used for performing azimuth compression processing on the echo data after the azimuth windowing processing to obtain the echo data after the azimuth compression processing; An azimuth accumulation processing module, used for performing azimuth accumulation processing on the echo data after azimuth compression processing row by row, so that the final azimuth is a column of data, thereby obtaining the echo data after azimuth accumulation processing; The range compression processing module is used to perform range compression processing on the echo data after the azimuth accumulation processing to obtain the echo data after the range compression processing.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the radar echo data processing method for improving the signal-to-noise ratio as described in any one of claims 1 to 7 is implemented.

10. A computer device, characterized in that: It includes: one or more processors; A storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the radar echo data processing method for improving the signal-to-noise ratio as described in any one of claims 1 to 7.

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