High-dimensional clutter map radar signal processing method, system, device, medium and program

Abstract

The invention relates to a high-dimensional clutter map radar signal processing method, system and device, a medium and a program, and the method comprises the steps: carrying out the pulse compression of a real-time signal of a target radar, and obtaining a compressed signal; performing constant false alarm target detection on the compressed signal to obtain low-speed target information; constructing a signal clutter map according to the low-speed target information, and performing region division on the signal clutter map to obtain clutter regions; performing energy accumulation on trace points in the clutter region to obtain trace point energy; and identifying a signal detection target in the real-time signal according to the trace point energy. The detection accuracy of the signal detection target is improved, and the clutter suppression effect can be achieved, so that the target radar has better adaptability to the complex environment.

Description

Technical Field

[0001] The present disclosure relates to the technical field of radar signal processing, and in particular to a method, system, device, medium and program for processing high-dimensional clutter map radar signals. Background Art

[0002] The radar detection process of slow small targets will be interfered by the complex background around the target, such as roads, buildings, people, etc. The radar echo generated by them has a great influence on the detection of real targets, which is usually called clutter. In the radar system, the signal processor uses a correlation algorithm to suppress clutter to a certain extent and detect the target. At the same time, its spatial position, amplitude value, radial velocity and other information are transmitted to the data recorder. The data recorder reports the measurement point trace to the data processor, which obtains the target distance, azimuth, motion parameters and other data after processing by a certain method, and then takes correlation, filtering, tracking and other operations to form a stable target track and display it on the radar terminal. Because there are many clutters mixed in the radar echo, after conventional processing of signal processing and data processing, there are still a large number of false points on the radar terminal, especially in the environment of interference or fixed clutter. Generally, the CFAR (Constant False-Alarm Rate) detection threshold is reduced to ensure the stable detection of slow small targets, resulting in the low adaptability of radar to complex environments.

[0003] At the same time, for the fully coherent, fully solid-state, pulse Doppler three-coordinate radar system, it works in the mode of wide beam transmission and narrow beam reception, and achieves large area coverage through mechanical scanning in azimuth and simultaneous digital multi-beam in elevation. It can detect and track small and micro targets within the power range, form target tracks in automatic and semi-automatic ways, and output target distance, azimuth, speed, heading and other information. In radar signal processing, pulse compression is used to take into account the radar's effective range and resolution, and then coherent accumulation is used to improve the target's signal-to-noise ratio, and the target is detected and reported through the constant false alarm detection method. However, in this process, only the target's distance and Doppler information are used for mean-type constant false alarm detection. When detecting slow and micro targets, the detection probability of the target is often low or there are many false points due to inaccurate threshold setting.

[0004] In summary, how to improve the radar's adaptability to the environment and the accuracy of target detection has become an urgent problem to be solved.

[0005] Public Content

[0006] The present invention provides a high-dimensional clutter map radar signal processing method, system, device, medium and program, which construct a signal clutter map with multi-dimensional slow target information, and can identify the clutter area in the signal clutter map; then identify the signal detection target in the real-time signal according to the point trace energy in the clutter area, improve the detection accuracy of the signal detection target, solve the problem of poor target detection accuracy, and achieve the effect of clutter suppression, and solve the problem of poor radar adaptability to complex environments.

[0007] In a first aspect, the present disclosure provides a high-dimensional clutter map radar signal processing method, comprising: acquiring a real-time signal of a target radar, performing pulse compression on the real-time signal to obtain a compressed signal; performing constant false alarm target detection on the compressed signal to obtain slow target information in the real-time signal; constructing a signal clutter map according to the slow target information, dividing the signal clutter map into regions to obtain clutter regions; accumulating energy of points in the clutter region to obtain point trace energy; and identifying a signal detection target in the real-time signal according to the point trace energy.

[0008] In some embodiments, the pulse compressing the real-time signal to obtain a compressed signal includes: calculating an impulse response of the real-time signal using a pre-built pulse compression filter;

[0009] The impulse response of the real-time signal is calculated using the following formula:

[0010] h(t)=Ks i *(t d -t)

[0011] Among them, h(t) represents the real-time signal s i (t) is the impulse response at the tth sampling time, i represents the index of the real-time signal in the time series, K represents the better gain constant, * represents convolution, t d represents the delay of the pulse compression filter;

[0012] A compressed signal of the real-time signal is calculated according to the impulse response.

[0013] In some embodiments, performing constant false alarm target detection on the compressed signal to obtain slow target information in the real-time signal includes: performing sample division on the compressed signal to obtain multiple interval signal samples; performing minimum mean square deviation on the interval signal samples to obtain interval frequency components; performing coherent accumulation on the interval frequency components to obtain accumulation components; performing target detection on the compressed signal based on the accumulation components to obtain a detection interval signal; calculating the Doppler speed of the detection interval, and obtaining the slow target information in the real-time signal when the Doppler speed is less than a preset speed threshold.

[0014] In some embodiments, constructing a signal clutter map according to the slow target information includes: dividing a preset radar detection range into a plurality of slow units according to the slow target information; and constructing a signal clutter map according to the slow units.

[0015] In some embodiments, accumulating energy of the traces in the clutter region to obtain trace energy includes: calculating the signal energy corresponding to the trace of each Doppler unit in the clutter region; determining the target trace in each Doppler unit according to the signal energy; and calculating the trace energy of the Doppler unit according to the signal energy of the target trace.

[0016] In some embodiments, identifying the signal detection target in the real-time signal based on the point trace energy includes: determining whether the point trace energy is greater than a preset energy threshold; when the point trace energy is greater than the preset energy threshold, determining that the target point trace corresponding to the point trace energy is a signal detection target.

[0017] In a second aspect, the present disclosure provides a high-dimensional clutter map radar signal processing system, including: a pulse compression module, used to acquire a real-time signal of a target radar, and perform pulse compression on the real-time signal to obtain a compressed signal; a constant false alarm target detection module, used to perform constant false alarm target detection on the compressed signal to obtain slow target information in the real-time signal; a clutter region division module, used to construct a signal clutter map according to the slow target information, and perform region division on the signal clutter map to obtain a clutter region; an energy accumulation module, used to accumulate energy of point traces in the clutter region to obtain point trace energy; and a signal detection target identification module, used to identify a signal detection target in the real-time signal according to the point trace energy.

[0018] In a third aspect, the present disclosure provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of a high-dimensional clutter map radar signal processing method described in the above aspect.

[0019] In a fourth aspect, the present disclosure provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a high-dimensional clutter map radar signal processing method described in the above aspect.

[0020] In a fifth aspect, the present disclosure provides a computer program product, including a computer program / instructions, which, when executed by a processor, implements the steps of a high-dimensional clutter map radar signal processing method described in the above aspects.

[0021] The present invention discloses a high-dimensional clutter map radar signal processing method, system, device, medium and program. The method can increase the time width of the signal pulse and reduce the peak power of the pulse by performing pulse compression on the real-time signal; perform constant false alarm target detection on the compressed signal to obtain slow target information in the real-time signal; construct a signal clutter map according to the multi-dimensional slow target information, and identify the clutter area in the signal clutter map; identify the signal detection target in the real-time signal according to the point trace energy in the clutter area, improve the detection accuracy of the signal detection target, and achieve the effect of clutter suppression, so that the target radar has better adaptability to complex environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The present disclosure will be described in more detail below based on embodiments and with reference to the accompanying drawings:

[0023] Figure 1 A schematic diagram showing the flow of a high-dimensional clutter image radar signal processing method according to a first embodiment of the present disclosure;

[0024] Figure 2 A schematic diagram showing the structure of a Doppler unit in the first embodiment of the present disclosure is shown;

[0025] Figure 3 A schematic diagram showing the structure of a signal clutter diagram in Embodiment 1 of the present disclosure is shown;

[0026] Figure 4 It shows a schematic diagram of the structure of the slow unit in the signal clutter diagram in the first embodiment of the present disclosure;

[0027] Figure 5 A schematic diagram showing the effect of radar signal processing in the first embodiment of the present disclosure is shown;

[0028] Figure 6 A functional module diagram of a high-dimensional clutter map radar signal processing system according to a third embodiment of the present disclosure is shown.

[0029] In the drawings, the same reference numerals are used for the same components, and the drawings are not drawn to scale. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the technical solution of the present disclosure, and to fully understand and implement how the present disclosure applies technical means to solve technical problems and achieve the corresponding technical effects, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only embodiments of a part of the present disclosure, not all of the embodiments. The embodiments of the present disclosure and the various features in the embodiments can be combined with each other without conflict, and the technical solutions formed are all within the scope of protection of the present disclosure. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present disclosure.

[0031] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0032] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0033] Embodiment 1

[0034] Figure 1 The following is a flow chart of a high-dimensional clutter radar signal processing method provided by an embodiment of the present disclosure. Figure 1 As shown, a high-dimensional clutter radar signal processing method includes:

[0035] S1. Acquire a real-time signal of a target radar, and perform pulse compression on the real-time signal to obtain a compressed signal.

[0036] In the disclosed embodiment, the target radar is a radar that needs to perform target detection, for example, slow small target radar detection. The real-time signal is a pulse signal reflected by the target and received by the target radar, which is an echo digital signal of the target with a large time-width bandwidth. The analog signal can be sampled, quantized and encoded by a preset A / D converter (Analog-to-Digital Converter, ADC for short) to convert the analog signal of the radar into a discrete digital signal, and further perform pulse compression on the real-time signal.

[0037] In the embodiment of the present disclosure, the pulse compression of the real-time signal to obtain the compressed signal includes:

[0038] Calculating an impulse response of the real-time signal using a pre-built pulse compression filter;

[0039] A compressed signal of the real-time signal is calculated according to the impulse response.

[0040] In the disclosed embodiment, the pulse compression filter is a widely used signal processing technology, which is mainly used to improve the distance resolution of the radar. The pulse signal emitted by the radar is compressed by means of a matching filter.

[0041] Specifically, the impulse response of the real-time signal is calculated using the following formula:

[0042] h(t)=Ks i *(t d -t)

[0043] Among them, h(t) represents the real-time signal s i (t) is the impulse response at the tth sampling time, i represents the index of the real-time signal in the time series, K represents the better gain constant, * represents convolution, t d Represents the delay of the pulse compression filter.

[0044] Specifically, the compressed signal is the output of the pulse compression filter, that is, the convolution of the real-time signal and the impulse response, as described in the following formula:

[0045] s0(t)=s i (t)*h(t)

[0046] Among them, s0(t) represents the compressed signal at the tth sampling time, s i (t) represents the real-time signal at the t-th sampling moment, * represents convolution, and h(t) represents the impulse response at the t-th sampling moment in real time.

[0047] In the embodiments of the present disclosure, by performing pulse compression on the real-time signal, the time width of the signal pulse can be increased and the peak power of the pulse can be reduced, while maintaining or increasing the total energy of the real-time signal.

[0048] S2. Performing constant false alarm target detection on the compressed signal to obtain slow target information in the real-time signal.

[0049] In the disclosed embodiments, constant false alarm target detection refers to maintaining a constant false alarm probability under different signal environments and noise levels, wherein a false alarm refers to a situation where a target is mistakenly detected when there is no target. The target constant false alarm detection can detect information such as the Doppler channel number, range gate, amplitude strength, beam number, azimuth information, etc. of the point trace.

[0050] In the embodiment of the present disclosure, the step of performing constant false alarm target detection on the compressed signal to obtain slow target information in the real-time signal includes:

[0051] Performing sample division on the compressed signal to obtain a plurality of interval signal samples;

[0052] Perform minimum mean square deviation on the interval signal samples to obtain interval frequency components;

[0053] Performing coherent accumulation on the interval frequency components to obtain accumulation components;

[0054] Performing target detection on the compressed signal according to the accumulated component to obtain a detection interval signal;

[0055] The Doppler speed of the detection interval is calculated, and when the Doppler speed is less than a preset speed threshold, the slow target information in the real-time signal is obtained.

[0056] In the embodiment of the present disclosure, sample division is to sample the compressed signal into N discrete points, each discrete point is an interval signal sample, and the N discrete points constitute a signal sequence of the compressed signal in the time domain.

[0057] Specifically, the minimum mean square error (MTD) uses a Doppler filter bank to suppress various clutters to improve the radar's ability to detect moving targets in a cluttered background. The N filters formed by the FFT of N points are evenly distributed in (0~f r ), the compressed signal may appear at different positions on the frequency axis due to its different Doppler frequencies, because it may be from 0 # ~(N-1) #As long as the target signal and the clutter signal are output from different Doppler filters, the new-to-clutter ratio of the filter output where the target signal is located will be significantly improved.

[0058] Furthermore, the following formula can be used to perform minimum mean square deviation on the interval signal samples to obtain the interval frequency component:

[0059]

[0060] Among them, X(n) represents the interval frequency component corresponding to the nth Doppler filter, x(k) represents the kth interval signal sample, e represents a natural constant, j represents an imaginary unit, and N represents the total number of interval signal samples.

[0061] In the disclosed embodiment, coherent accumulation is to perform weighted accumulation of signals of multiple periods taking into account the phase information of the received data in each period. For example, the compressed signal is divided into 128 interval sample signals, that is, the frequency components of 128 points are coherently accumulated to obtain accumulated components.

[0062] Specifically, the coherent accumulation can be performed by pulse alignment of the frequency components through time delay estimation and correction, and then the sample phases are aligned and then accumulated to obtain the accumulated components. Among them, all frequency components can be multiplied by the same reference phase and then summed to obtain the accumulated components.

[0063] In the disclosed embodiment, target detection is to select some reference units that do not contain target echoes around the accumulated component signals to estimate the statistical characteristics of the background noise, and use the noise estimation value and the predetermined false alarm probability to calculate the CFAR detection threshold. If the signal value exceeds the threshold, it is considered that the unit detects the target and obtains the detection interval signal.

[0064] Furthermore, the Doppler velocity is the radial velocity of the target relative to the target radar system, which can be determined by analyzing the Doppler frequency shift of the target reflection or transmission signal. When the Doppler velocity is less than a preset velocity threshold, for example, 5 m / s, it is determined as slow target information.

[0065] Specifically, the slow target information includes the Doppler channel number, range gate, amplitude strength, beam number, azimuth and other information of the target detection point trace, and the slow target information is spatially stored.

[0066] S3. Construct a signal clutter map according to the slow target information, and divide the signal clutter map into regions to obtain clutter regions.

[0067] In the disclosed embodiment, the signal clutter map is a clutter intensity map that characterizes the distribution of distance-azimuth units within the radar power range. When the environmental noise is too strong, the slow target detection radar will detect a large amount of slow clutter on the low Doppler unit, and the low Doppler unit must be shielded to suppress the slow clutter, but the low-speed target is also shielded at the same time. Therefore, the signal clutter map can be constructed through the five dimensions of Doppler channel number, azimuth, distance, beam, and amplitude intensity in the slow target information to perform more refined target detection.

[0068] Among them, Figure 2 As shown, it represents the nth Doppler unit. The Doppler unit is a processing unit used to represent a specific frequency range in radar signal processing. The real-time signal is decomposed into multiple such units through the Doppler unit. Each unit corresponds to a Doppler frequency within a certain range, thereby allowing the target radar to measure the speed of the target. In some embodiments, the Doppler unit can be represented by a Doppler channel.

[0069] In the embodiment of the present disclosure, the step of constructing a signal clutter map according to the slow target information includes:

[0070] Dividing a preset radar detection range into a plurality of slow units according to the slow target information;

[0071] A signal clutter map is constructed based on the slow unit.

[0072] Specifically, the frequency range corresponding to the slow target information is smaller than the speed threshold frequency range, and the radar detection range is divided into a plurality of slow units, wherein the slow unit can be called a clutter unit, such as Figure 3 As shown, for each Doppler unit, the radar detection range is divided into several elevation beam units consisting of distance and azimuth according to the distance-azimuth. Each elevation beam unit is called a slow unit, such as Figure 4 As shown, where Δθ represents the azimuth width, represents the elevation angle beam width, and Δρ represents the radial distance, which can divide the space of the target radar into several space units. Specifically, the i-th distance unit, the j-th azimuth unit and the m-th elevation beam unit are represented by Δv(i, j, m).

[0073] In the embodiment of the present disclosure, the signal clutter map is divided into regions to obtain clutter regions, including:

[0074] Counting the number of points in each Doppler unit in the signal clutter map;

[0075] When the number of the point traces is greater than a preset number threshold, the pitch beam unit is used as a clutter area.

[0076] In the disclosed embodiment, a trace is a record of a target detected by a target radar at a specific time and position, for example, the record includes information such as the distance, azimuth, altitude, and Doppler velocity of the target, and then the target trace can be picked up through the slow target information in each elevation beam unit in the signal clutter map, and then the number of traces in each clutter unit on the same Doppler unit is counted. For example, if the signal in each elevation beam unit exceeds a threshold, it is considered that there is a target trace in the clutter unit, wherein the traces are associated to form a trajectory of the target. Wherein, the Doppler unit represents a specific frequency range, which is used to capture and represent the signal energy within a certain frequency range.

[0077] Further, the quantity threshold may be half of the total number of Doppler units in the signal clutter map, the number of traces M, when M>P / 2, the elevation beam unit is a clutter area, where P is the number of Doppler units in the signal clutter map.

[0078] In the disclosed embodiment, a more refined signal-clutter map is established through multi-dimensional slow target information, the clutter area can be identified and the clutter area can be processed intensively, and the problem of slow target detection difficulty can be addressed, while clutter suppression can be achieved and the detection accuracy of signal detection targets can be further improved.

[0079] S4. Accumulate the energy of the points in the clutter area to obtain the energy of the points.

[0080] In the embodiment of the present disclosure, energy accumulation is to select the point trace with the largest or second largest amplitude intensity in the clutter area of ​​the same Doppler unit (same frequency range) for energy accumulation to obtain the point trace energy.

[0081] In the embodiment of the present disclosure, the step of accumulating energy of the points in the clutter area to obtain the energy of the points includes:

[0082] Calculating the signal energy corresponding to the point trace of each Doppler unit in the clutter area;

[0083] Determine the target point trace in each of the Doppler units according to the signal energy;

[0084] The point energy of the Doppler unit is calculated according to the signal energy of the target point.

[0085] In the disclosed embodiment, signal energy is the power or intensity of each point trace, that is, the power or intensity corresponding to the point trace in the clutter area within the same frequency range. The signal energy can be measured by the hardware and software of the radar receiver of the target radar, for example, signal amplification, filtering, and analog-to-digital conversion steps.

[0086] Furthermore, the target point trace is the point trace with the largest or second largest signal energy in the clutter area, and the point trace energy of each Doppler unit is obtained by recursively estimating the target point trace.

[0087] Preferably, the energy of the point track is usually estimated by a recursive estimation method, that is, the signal energy of the newly received target point track is multiplied by 1-k, and then added to the original signal energy of the target point track multiplied by k to obtain the current average estimated value of the clutter. The value of k should make the estimated value relatively stable, for example, k = 7 / 8. Among them, the clutter modulus value should be equal to the average value accumulated after different radar scanning cycles.

[0088] In the disclosed embodiment, the signal-to-noise ratio (SNR) of the signal can be improved through energy accumulation, thereby enhancing the reliability of target detection.

[0089] S5. Identify a signal detection target in the real-time signal according to the point trace energy.

[0090] In the disclosed embodiment, the signal detection target is a slow target located by the target radar, and clutter suppression is performed on the target in the real-time signal according to the point trace energy to obtain a more accurate signal detection target.

[0091] In the embodiment of the present disclosure, the step of identifying a signal detection target in the real-time signal according to the point trace energy includes:

[0092] Determine whether the energy of the point trace is greater than a preset energy threshold;

[0093] When the point trace energy is greater than a preset energy threshold, it is determined that the target point trace corresponding to the point trace energy is a signal detection target.

[0094] Furthermore, when the point trace energy is less than or equal to a preset energy threshold, it is determined that the target point trace corresponding to the point trace energy is not a signal detection target, and clutter suppression is performed, which can further improve the accuracy of signal detection targets.

[0095] Among them, by associating the signal detection targets, the trajectory corresponding to the slow target located by the target radar can be obtained, and the description information of the signal detection target can be obtained. For example, through the echo signal corresponding to each signal detection target, the Doppler channel number, range gate, amplitude strength, beam number, azimuth information and other information of the signal detection target can be obtained.

[0096] For example, since the Doppler channel number of a slow target basically changes little, the distance change is also small within a certain period. Assuming a target with a radial motion of 2m / s and a stable flight altitude, based on the radar detection result of 20rad / min, the motion distance of 5 circles is 30 meters. When the distance unit Δρ=30m is set, the energy of the target can be estimated by the average value of 5 times. If the target is clutter, there are multiple non-accumulative situations. Therefore, setting a reasonable threshold Q further improves the detection probability of the target and reduces the false alarm rate. Specifically, the effect of real-time signal processing is as follows: Figure 5 shown.

[0097] Furthermore, the signal energy is non-coherently accumulated through the detection positions with the largest amplitude and the second largest amplitude in the clutter area, and the clutter suppression effect is achieved through the design of energy thresholds, so that the target radar has better adaptability to complex environments.

[0098] Embodiment 2

[0099] On the basis of the above embodiments, in order to more clearly understand the present disclosure, a second embodiment is used below to further explain the situation in which the energy of the point traces in the clutter area needs to be more accurately accumulated to obtain the point trace energy in the first embodiment of the present disclosure.

[0100] In the embodiment of the present disclosure, accumulating the energy of the point traces in the clutter area to obtain the point trace energy includes:

[0101] Determining a reference cell within the clutter region in the signal clutter map;

[0102] Calculating the signal energy corresponding to the point trace in each Doppler unit in the reference unit;

[0103] The average value of the signal energy is calculated to obtain the point energy of the Doppler unit.

[0104] In the embodiment of the present disclosure, N reference units are taken on both sides of the clutter area in the signal-clutter diagram, and the point trace signal energy of 2N reference units in the Doppler unit is calculated. The average value of the signal energy is used as the estimated value of the clutter area, and then the point trace energy in each Doppler unit is calculated.

[0105] In the disclosed embodiment, the reference unit can provide stable detection performance under different noise levels, thereby improving the accuracy of subsequent signal detection target detection.

[0106] Embodiment 3

[0107] Based on the above embodiments, Figure 6 This is a functional module diagram of a high-dimensional clutter radar signal processing system provided by an embodiment of the present disclosure. Figure 6As shown, a high-dimensional clutter image radar signal processing system includes:

[0108] The high-dimensional clutter image radar signal processing system 600 described in this embodiment can be installed in an electronic device. According to the functions implemented, the high-dimensional clutter image radar signal processing system 600 may include a pulse compression module 601, a constant false alarm target detection module 602, a clutter area division module 603, an energy accumulation module 604 and a signal detection target identification module 605. The module described in the present disclosure may also be referred to as a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0109] In this embodiment, the functions of each module / unit are as follows:

[0110] The pulse compression module 601 is used to obtain the real-time signal of the target radar, and perform pulse compression on the real-time signal to obtain a compressed signal;

[0111] The constant false alarm target detection module 602 is used to perform constant false alarm target detection on the compressed signal to obtain slow target information in the real-time signal;

[0112] The clutter region division module 603 is used to construct a signal clutter map according to the slow target information, and divide the signal clutter map into regions to obtain clutter regions;

[0113] The energy accumulation module 604 is used to accumulate the energy of the points in the clutter area to obtain the energy of the points;

[0114] The signal detection target identification module 605 is used to identify the signal detection target in the real-time signal according to the point trace energy.

[0115] In detail, each module described in the high-dimensional clutter map radar signal processing system 600 described in the embodiment of the present disclosure adopts the same technical means as the high-dimensional clutter map radar signal processing method described in Example 1 when used, and can produce the same technical effects, which will not be repeated here.

[0116] Embodiment 4

[0117] On the basis of the above embodiments, this embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the above embodiments.

[0118] In some implementations of this embodiment, a computer-readable storage medium is provided, on which a computer program is stored, characterized in that when the computer program is executed by a processor, the steps of the method described in the above embodiment are implemented.

[0119] In some implementations of this embodiment, a computer program product is provided, including a computer program / instructions, characterized in that when the computer program is executed by a processor, the steps of the method described in the above embodiment are implemented.

[0120] The processor may include, but is not limited to, one or more processors or microprocessors. Each processor may be an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a controller, a microcontroller, a microprocessor or other electronic components to execute the method in the above embodiments.

[0121] The computer-readable storage medium may be implemented by any type of volatile or non-volatile storage device or a combination thereof, and the computer-readable storage medium may include but is not limited to, for example, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, computer storage media (e.g., hard disk, floppy disk, solid-state drive, removable disk, CD-ROM, DVD-ROM, Blu-ray disc, etc.).

[0122] The computer-readable storage medium may also store at least one computer executable program / instruction, which may be, for example, a computer-readable instruction. The computer-readable storage medium includes, but is not limited to, for example, a volatile memory and / or a non-volatile memory. The volatile memory may include, for example, a random access memory (RAM) and / or a cache memory (cache), etc. The computer-readable storage medium may include, for example, a read-only memory (ROM), a hard disk, a flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device runs the computer-readable instructions stored on the computer-readable storage medium, the various methods described above may be performed.

[0123] In addition, the computer device may also include (but not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (eg, keyboard, mouse, speaker, etc.), etc.

[0124] The processor may communicate with external devices via an I / O bus via a wired or wireless network.

[0125] In one embodiment, the at least one computer executable instruction may also be compiled into or constitute a software product / computer program product, wherein one or more computer executable instructions are executed by a processor to perform the various functions and / or method steps in the embodiments described in the present technology.

[0126] In the embodiments provided in the present disclosure, it should be understood that the disclosed systems and methods can also be implemented in other ways. The system embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the systems, methods and computer program products according to the multiple embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the above-mentioned module, program segment or a part of the code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0127] It should be noted that in the present disclosure, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element limited by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0128] Although the embodiments disclosed in the present disclosure are as above, the above contents are only embodiments adopted for facilitating the understanding of the present disclosure and are not intended to limit the present disclosure. Any technician in the technical field to which the present disclosure belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present disclosure, but the scope of patent protection of the present disclosure shall still be subject to the scope defined in the attached claims.

Claims

1. A high-dimensional clutter radar signal processing method, characterized in that: include: Acquire a real-time signal of a target radar, and perform pulse compression on the real-time signal to obtain a compressed signal; Performing constant false alarm target detection on the compressed signal to obtain slow target information in the real-time signal; Constructing a signal clutter map according to the slow target information, and dividing the signal clutter map into regions to obtain clutter regions; Accumulating energy of the points in the clutter area to obtain point energy; A signal detection target in the real-time signal is identified according to the point trace energy.

2. The high-dimensional clutter radar signal processing method according to claim 1, characterized in that: The pulse compressing the real-time signal to obtain a compressed signal comprises: Calculating an impulse response of the real-time signal using a pre-built pulse compression filter; The impulse response of the real-time signal is calculated using the following formula: h(t)=Ks i *(t d -t) Among them, h(t) represents the real-time signal s i (t) is the impulse response at the tth sampling time, i represents the index of the real-time signal in the time series, K represents the better gain constant, * represents convolution, t d represents the delay of the pulse compression filter; A compressed signal of the real-time signal is calculated according to the impulse response.

3. The high-dimensional clutter radar signal processing method according to claim 1, characterized in that: The performing constant false alarm target detection on the compressed signal to obtain slow target information in the real-time signal includes: Performing sample division on the compressed signal to obtain a plurality of interval signal samples; Perform minimum mean square deviation on the interval signal samples to obtain interval frequency components; Performing coherent accumulation on the interval frequency components to obtain accumulation components; Performing target detection on the compressed signal according to the accumulated component to obtain a detection interval signal; The Doppler speed of the detection interval is calculated, and when the Doppler speed is less than a preset speed threshold, the slow target information in the real-time signal is obtained.

4. The high-dimensional clutter radar signal processing method according to claim 1, characterized in that: The constructing a signal clutter map according to the slow target information includes: Dividing a preset radar detection range into a plurality of slow units according to the slow target information; A signal clutter map is constructed based on the slow unit.

5. The high-dimensional clutter radar signal processing method according to claim 1, characterized in that: The step of accumulating energy of the points in the clutter region to obtain the energy of the points includes: Calculating the signal energy corresponding to the point trace of each Doppler unit in the clutter area; Determine the target point trace in each of the Doppler units according to the signal energy; The point energy of the Doppler unit is calculated according to the signal energy of the target point.

6. The high-dimensional clutter radar signal processing method according to claim 1, characterized in that: The step of identifying a signal detection target in the real-time signal according to the point trace energy includes: Determine whether the energy of the point trace is greater than a preset energy threshold; When the point trace energy is greater than a preset energy threshold, the target point trace corresponding to the point trace energy is determined as a signal detection target.

7. A high-dimensional clutter radar signal processing system, characterized in that: include: A pulse compression module is used to obtain a real-time signal of a target radar, and to perform pulse compression on the real-time signal to obtain a compressed signal; A constant false alarm target detection module, used for performing constant false alarm target detection on the compressed signal to obtain slow target information in the real-time signal; A clutter region division module is used to construct a signal clutter map according to the slow target information, and divide the signal clutter map into regions to obtain clutter regions; An energy accumulation module, used for accumulating energy of point traces in the clutter area to obtain point trace energy; A signal detection target identification module is used to identify the signal detection target in the real-time signal according to the point trace energy.

8. A computer device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the high-dimensional clutter map radar signal processing method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the high-dimensional clutter map radar signal processing method described in any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program is executed by a processor, the steps of the high-dimensional clutter map radar signal processing method described in any one of claims 1 to 6 are implemented.

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