CN116990773A - Low-speed small target detection method and device based on self-adaptive threshold and storage medium - Google Patents
Low-speed small target detection method and device based on self-adaptive threshold and storage medium Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
- G01S7/414—Discriminating targets with respect to background clutter
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
- G01S7/415—Identification of targets based on measurements of movement associated with the target
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Abstract
The application discloses a low-speed small target detection method based on a self-adaptive threshold, which comprises the steps of removing direct current components of echo data in a distance dimension and a Doppler dimension; the pulse pressure result is subjected to coherent accumulation to obtain data to be detected, and a part of pulse compression results are selected in the Doppler dimension to perform coherent accumulation to extract a zero channel background; combining the Doppler window smoothing coefficient to obtain a Doppler threshold, and calculating the distance dimension threshold according to a distance unit where the target is and an STC attenuation curve; the constant false alarm detection is carried out on the sum channel by using two groups of self-adaptive thresholds, and the constant false alarm detection is compared with the position data corresponding to the difference channel, so that sidelobe interference is eliminated; and finally, carrying out fusion processing on the target, calculating track associated information, guiding the photoelectric equipment to carry out image detection and identification, and matching with a corresponding early warning processing mode. The method can remove the static target on the Doppler zero channel, effectively reserve the characteristic of the slow target and reduce the spurious false alarm.
Description
Technical Field
The application relates to a radar application technology, in particular to a low-speed small target detection method, a device and a storage medium based on a self-adaptive threshold.
Background
In recent years, the development of 'low-low' aircrafts is in blowout, and the low-low aircraft has the characteristics of low price and easy purchase, so that the low-low aircraft is easy to be used by illegal persons as a tool for invading high-grade security units. Thus, monitoring and intrusion prevention in the low-altitude area of high-level security units face serious challenges.
The target is usually a 'low, slow, small' consumer or professional unmanned aerial vehicle, and the radar is usually arranged in a city environment with a relatively complex environment, so that a large-scale radar (such as a low-altitude blind-complement radar) is not suitable for use, is generally based on a ground reconnaissance radar, and breaks through a weak target detection technology in the ground clutter background again to meet the requirement of 'low, slow and small' detection.
Disclosure of Invention
The present application aims to solve at least one of the technical problems existing in the prior art. Therefore, the application provides a low-speed small target detection method, a device and a storage medium based on a self-adaptive threshold so as to optimize ground-air detection effect.
In one aspect, an embodiment of the present application provides a method for detecting a slow small target based on an adaptive threshold, which is characterized by comprising the following steps:
and a data acquisition step: receiving signals from an antenna unit, and obtaining sum and difference channel echo data after preset processing;
and (3) pulse compression: pulse compression is carried out on return data collected by radar equipment;
and a phase-coherent accumulation step: performing coherent accumulation processing on the result output by the pulse compression step to obtain data to be detected, and performing coherent accumulation on the pulse compression result of the Doppler dimension selection part to extract zero channel background;
and a self-adaptive threshold calculating step: combining the Doppler window smoothing coefficient and the zero channel background to obtain a Doppler threshold, and calculating a distance threshold according to a distance unit where a target is and a short-range gain control attenuation curve;
and (3) constant false alarm detection: searching corresponding threshold values on a distance threshold curve and a Doppler threshold curve respectively according to a distance unit X and a Doppler channel Y where each detection point to be detected is located;
target fusion and early warning steps: and according to the target data information, matching the corresponding early warning grade and the early warning mode, guiding the photoelectric equipment to acquire the target image information, and sending an early warning notice to early warning personnel according to the early warning mode.
In some embodiments, the receiving the signal from the antenna unit and performing a preset process to obtain sum and difference channel echo data specifically includes:
the receiving channel receives signals from the antenna unit, outputs zero intermediate frequency IQ signals after amplification, filtering, attenuation control and twice down-conversion, wherein the sampling rate is 120MHz, the bandwidth is 25MHz or 50MHz, and finally FIR low-pass filtering is adopted to remove out-of-band spurious to obtain sum and difference channel echo data;
and selecting 1/16 pulse compression result in the phase-coherent accumulation step to perform phase-coherent accumulation.
In some embodiments, searching corresponding threshold values on a distance threshold curve and a doppler threshold curve according to a distance unit X and a doppler channel Y where each to-be-detected point is located, which specifically includes:
when constant false alarm detection is carried out, corresponding threshold values are respectively searched on a distance threshold curve and a Doppler threshold curve according to the distance unit X and the Doppler channel Y where each detection point to be detected is located, so that a decision threshold is adaptively adjusted, and compared with position data corresponding to a symmetrical position data and a difference channel of the channel, and sidelobe interference is eliminated.
In some embodiments, the pulse compression is performed on the return data collected by the radar device, specifically:
the return data acquired by the radar equipment is subjected to pulse compression after the direct current component is removed in the distance dimension, and the average value of all channels is subtracted in the Doppler dimension after the pulse compression;
in some embodiments, the target fusion and early warning step specifically includes:
calculating target measurement information, utilizing a sum-difference channel amplitude comparison angle measurement, carrying out centroid fusion on a detected target by taking a signal-to-noise ratio as a reference, carrying out track association in a plurality of scanning periods, matching corresponding early warning grades and early warning modes according to target data information, guiding the photoelectric equipment to acquire target image information, and sending early warning notification to early warning personnel according to the early warning modes.
In some embodiments, the slow small target comprises an unmanned aerial vehicle, a bird;
the radar equipment is an air-to-air low-speed small radar, adopts a pulse system, has three channels of sum, azimuth and pitch, and works in linkage with the photoelectric equipment;
the constant false alarm detection algorithm is a CA_CFAR algorithm, and the decision threshold value is self-adaptively adjusted according to a threshold curve in the distance dimension and the Doppler dimension.
In some embodiments, the pre-warning step specifically includes: and displaying the data information and the image information of the target to early warning personnel through a display.
In some embodiments, the target data information includes distance, speed, size, and echo energy values of the target, track correlation conditions among a plurality of scan periods; the distance and the speed of the target are the radial distance and the radial speed, and the size of the target comprises the radial size and the transverse size; the radial dimension refers to the dimension obtained after the target fusion in a single coherent processing interval period; the transverse dimension refers to the dimension obtained after the targets are fused in a plurality of coherent processing interval periods; the echo energy value refers to the reflected energy value of the target to the radar signal of the radar apparatus.
In some embodiments, the track association is a determination of target information during a plurality of scan cycles, and if there is no track association point, it may be an isolated stray point or a stationary target, and if there is a stable track, it may be a threatening moving target.
In another aspect, an embodiment of the present application provides a device for detecting a slow small target based on an adaptive threshold, which is characterized by including:
a memory for storing a program;
and the processor is used for loading the program to execute the low-speed small target detection method based on the self-adaptive threshold.
In another aspect, an embodiment of the present application provides a computer readable storage medium storing a program, where the program, when executed by a processor, implements the adaptive threshold-based low-speed small target detection method.
According to the embodiment of the application, the radar equipment and the photoelectric equipment are combined to realize the detection of low-speed and small targets, the self-adaptive threshold judgment is used during the detection of the constant false alarm, so that the ground clutter environment interference is eliminated, the characteristics of the weak targets are reserved, the photoelectric equipment is guided to acquire the target image information according to the corresponding early warning level and the early warning mode of the target data information obtained by detection, and then the corresponding early warning mode is provided for early warning personnel by combining the early warning level set in the system, thereby solving the problem of false alarm or missing alarm caused by the weak target detection under the ground clutter background in the prior art.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for detecting a low-speed small target based on an adaptive threshold;
FIG. 2 is a schematic diagram of echo data according to an embodiment of the present application;
FIG. 3 is a graph of a distance dimension threshold derived from an STC curve in accordance with an embodiment of the present application;
FIG. 4 is a graph of Doppler threshold derived from a window function in accordance with an embodiment of the present application;
FIG. 5 is a graph comparing the results of eliminating zero channels with conventional DC elimination techniques in accordance with an embodiment of the present application;
fig. 6 is a block diagram of a low-speed small target detection device based on an adaptive threshold according to the present application.
In the figure: 11. a memory; 12. a processor; 13. a communication bus; 14. a network interface.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be clearly and completely described by means of implementation examples with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In the description of the present application, the meaning of a number is one or more, the meaning of a number is two or more, and greater than, less than, exceeding, etc. are understood to exclude the present number, and the meaning of a number is understood to include the present number. The description of the first and second is for the purpose of distinguishing between technical features only and should not be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
In the description of the present application, unless explicitly defined otherwise, terms such as arrangement and the like should be construed broadly, and those skilled in the art can reasonably determine the specific meaning of the terms in the present application in combination with the specific contents of the technical scheme.
In the description of the present application, a description of the terms "one embodiment," "some embodiments," "an exemplary embodiment," "an example," "a particular example," or "some examples," etc., means that a particular feature or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
According to the embodiment of the application, the radar equipment and the photoelectric equipment are combined to realize the detection of low-speed and small targets, the self-adaptive threshold judgment is used during the detection of the constant false alarm, so that the ground clutter environment interference is eliminated, the characteristics of the weak targets are reserved, the photoelectric equipment is guided to acquire the target image information according to the corresponding early warning level and the early warning mode of the target data information obtained by detection, and then the corresponding early warning mode is provided for early warning personnel by combining the early warning level set in the system, thereby solving the problem of false alarm or missing alarm caused by the weak target detection under the ground clutter background in the prior art.
As shown in fig. 1, the present application provides a preferred embodiment of a low-speed small target detection method based on an adaptive threshold, which includes the following steps:
step S1, data acquisition: the receiving channel receives signals from the antenna unit, outputs zero intermediate frequency IQ signals (sampling rate 120MHz, bandwidth 25MHz/50 MHz) after amplification, filtering and attenuation control and twice down-conversion, and finally removes out-of-band spurious by adopting FIR low-pass filtering to obtain sum and difference channel echo data;
preferably, the present application is implemented based on existing low-slow small target detection devices. The slow small object detection device in this embodiment includes a radar device and an electro-optical device. The radar equipment is used for generating radar signals, radiating the radar signals into a monitoring area and receiving echo signals, adopts a pulse system, has three channels of sum, azimuth and pitching, and works in linkage with the photoelectric equipment. The optoelectronic device is used for photographing the detection target to generate an optical image.
Step S2, pulse compression: echo data collected by radar equipment is firstly subjected to pulse compression after direct current components are removed in a distance dimension, and the mean value of a channel where the echo data is located is subtracted in a Doppler dimension after pulse pressure. In the radon data, as shown in fig. 2, the echo data of each channel can be understood as a two-dimensional matrix, where each prt in the transverse direction corresponds to a distance dimension, and the doppler dimension in the longitudinal direction.
Preferably, the direct current component is removed in the distance dimension, and the mean value of the channel where the direct current component is located is subtracted in the Doppler dimension, so that the signal energy of the Doppler zero channel can be effectively restrained, and the ground clutter environment interference is avoided. FIG. 5 is a graph showing the comparison of the result of eliminating zero-channel with the conventional DC technique according to the embodiment of the present application.
Step S3, a coherent accumulation step: and performing coherent accumulation processing on the pulse compression result to obtain data to be detected, and performing coherent accumulation on the pulse compression result of 1/16 selected in the Doppler dimension to extract a zero channel background.
The coherent accumulation is to accumulate the data result of each pulse repetition period PRT of one coherence interval period (CPI) for improving the signal-to-noise ratio. For example, the target energy of one pulse repetition Period (PRT) is not significant, and the data accumulation for a plurality of consecutive pulse repetition periods does not vary significantly, but the target signal energy is greater.
Preferably, the pulse repetition period is 50 microseconds and the CPI time is 25.6 milliseconds.
Step S4, self-adaptive threshold calculation step: and combining the Doppler window smoothing coefficient and the zero channel background to obtain a Doppler threshold, and calculating the distance threshold according to a distance unit where the target is and an STC (short range gain control) attenuation curve. Referring to fig. 3 and 4, fig. 3 provides a distance-dimensional threshold graph derived from an STC curve. Figure 4 provides a graph of the doppler threshold derived from the window function.
Step S5, constant false alarm detection: when constant false alarm detection is carried out, corresponding threshold values are respectively searched on a distance threshold curve and a Doppler threshold curve according to the distance unit X and the Doppler channel Y where each detection point to be detected is located, so that a decision threshold is adaptively adjusted, and compared with position data corresponding to a symmetrical position data and a difference channel of the channel, and sidelobe interference is eliminated.
The constant false alarm detection refers to a technology that a radar system judges a signal output by a receiver and noise under the condition of keeping the false alarm probability constant so as to determine whether a target signal exists. The constant virtual detection algorithm in the embodiment adopts a CA_CFAR algorithm, the lengths of a detection window and a protection window are changed along with the distance of a detection target, the specific length setting is determined through statistics of a test function, and meanwhile, the detection threshold can be adjusted through practical application.
Preferably, after the target coordinates are obtained through detection of the accumulated data related to the channel, the target coordinates are compared with the energy of the symmetrical position signals of the channel (comprising the symmetrical position of the distance dimension and the symmetrical position of the Doppler dimension), whether the target coordinates are stray or not is judged, and whether the target coordinates are side lobe interference or not is judged by comparing the target coordinates with the signals of the same position of the difference channel.
S6, target fusion and early warning steps: calculating target measurement information, utilizing a sum-difference channel amplitude comparison angle measurement, carrying out centroid fusion on a detected target by taking a signal-to-noise ratio as a reference, carrying out track association in a plurality of scanning periods, matching corresponding early warning grades and early warning modes according to target data information, guiding the photoelectric equipment to acquire target image information, and sending early warning notification to early warning personnel according to the early warning modes.
When detecting the target, fusing the calculation results in one pulse repetition period, fusing the targets with similar distance angles into one target, and fusing the calculation results in a plurality of pulse repetition periods. And during fusion, the signal-to-noise ratio is used as a reference value, and each target point calculates the data information of the fusion point according to the signal-to-noise ratio weight.
Preferably, the data information of the target comprises information such as distance, speed, angle, energy, size and the like of the target and track association condition. Wherein the dimensions of the target include a radial dimension and a lateral dimension of the target. The radial dimension is the dimension recorded by fusing the targets in each CPI, and the lateral dimension is the dimension recorded by fusing the targets in multiple CPIs.
Specifically, when calculating the size of the target, for example, by fusing the number of interval points of the target point, the distance resolution of the adjacent points is (c×kr)/(2×bw), where C is the speed of light in free space, kr is the bandwidth widening factor, and Bw is the frequency modulation bandwidth.
The radial size of the object is calculated from the resolution of the detected object points, e.g. one object is detected as 3 adjacent points, its size being 2 times the resolution. However, the lateral dimensions of the targets are calculated from a cycle of target fusion, e.g., the same target is detected over 4 consecutive angles, which is considered larger than the target lateral dimensions of 3 consecutive angles, but not the quantitative dimension. The size of the target in this embodiment is used only to distinguish the pairs and cannot be measured accurately.
Preferably, in multiple scanning periods, associated track information can be formed according to information such as target size, energy, distance, angle and speed, if no track associated point exists, the associated track information can be an isolated stray point or a static target, if a stable track exists, the associated track is a threatening moving target, and the corresponding early warning level and early warning mode are matched by combining the photoelectric image detection result, so that more false alarms can be avoided.
Preferably, step S6 further comprises: when the early warning notification is sent to the early warning personnel, the information of each target is also sent to the early warning personnel, so that the early warning personnel can carry out auxiliary confirmation on the target according to the echo energy value, the track information value and the optical image of the target, and judge whether the target is driven or counter-controlled.
According to the application, the ground clutter influence can be effectively filtered, the low-speed weak target is detected, the target information is timely reported to the early warning personnel, the early warning accuracy is improved, and the false alarm is avoided.
The application provides a low-speed small target detection device based on a self-adaptive threshold. As shown in fig. 6, an internal structure of the adaptive threshold-based low-speed small target detection device according to an embodiment of the present application is shown.
In this embodiment, the low-speed small target detection device based on the adaptive threshold may be a PC (Personal Computer ), or may be a terminal device such as a smart phone, a tablet computer, or a portable computer. The low-speed small target detection device based on the self-adaptive threshold at least comprises: a processor 12, a communication bus 13, a network interface 14 and a memory 11.
The memory 11 includes at least one type of readable storage medium including flash memory, a hard disk, a multimedia card, a card memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 may in some embodiments be an internal memory unit of the adaptive threshold based low slow small object detection device, e.g. a hard disk of the adaptive threshold based low slow small object detection device. The memory 11 may also be an external storage device of the adaptive threshold-based slow and small object detection device in other embodiments, for example, a plug-in hard disk, smart Media Card (SMC), secure Digital (SD) Card, flash Card (Flash Card) or the like provided on the adaptive threshold-based slow and small object detection device. Further, the memory 11 may also comprise both an internal memory unit and an external memory device of the low-speed small-object detection device based on the adaptive threshold. The memory 11 may be used not only for storing application software installed in the adaptive threshold-based slow and small object detection device and various types of data, such as codes of the adaptive threshold-based slow and small object detection program, but also for temporarily storing data that has been output or is to be output.
The processor 12 may in some embodiments be a central processing unit (Central Processing Unit, CPU), controller, microcontroller, microprocessor or other data processing chip for running program code or processing data stored in the memory 11, e.g. executing an adaptive threshold based low-speed small object detection program or the like.
The communication bus 13 is used to enable connection communication between these components.
The network interface 14 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), and is typically used to establish a communication connection between the adaptive threshold-based low speed small object detection device and other electronic devices.
Optionally, the adaptive threshold-based slow small object detection device may further comprise a user interface, which may comprise a Display (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface may further comprise a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the adaptive threshold-based low-speed small-object detection device and for displaying a visual user interface.
Fig. 6 shows only an adaptive threshold based slow small object detection device having components 11-14 and an adaptive threshold based slow small object detection procedure, it will be appreciated by those skilled in the art that the configuration shown in fig. 6 does not constitute a limitation of an adaptive threshold based slow small object detection device and may include fewer or more components than shown, or some components in combination, or a different arrangement of components.
In the embodiment of the adaptive threshold-based slow and small target detection device shown in fig. 6, the memory 11 stores an adaptive threshold-based slow and small target detection program; the processor 12 performs the following steps when executing the adaptive threshold based low-slow small object detection program stored in the memory 11:
and a data acquisition step: the receiving channel receives signals from the antenna unit, outputs zero intermediate frequency IQ signals (sampling rate 120MHz, bandwidth 25MHz/50 MHz) after amplification, filtering and attenuation control and twice down-conversion, and finally removes out-of-band spurious by adopting FIR low-pass filtering to obtain sum and difference channel echo data;
and (3) pulse compression: echo data collected by radar equipment is subjected to pulse compression after direct current components are removed in a distance dimension, and the mean value of a channel where the echo data is located is subtracted in a Doppler dimension after pulse pressure;
and a phase-coherent accumulation step: performing coherent accumulation processing on the pulse compression result to obtain data to be detected, and selecting 1/16 pulse compression result in Doppler dimension to perform coherent accumulation for extracting zero channel background;
and a self-adaptive threshold calculating step: combining the Doppler window smoothing coefficient and the zero channel background to obtain a Doppler threshold, and calculating the distance threshold according to a distance unit where a target is and an STC (short range gain control) attenuation curve;
and (3) constant false alarm detection: when constant false alarm detection is carried out, corresponding threshold values are respectively searched on a distance threshold curve and a Doppler threshold curve according to a distance unit X and a Doppler channel Y where each detection point to be detected is positioned, so that a decision threshold is adaptively adjusted, and compared with position data corresponding to a channel symmetrical position data and a channel difference position data, and sidelobe interference is eliminated;
target fusion and early warning steps: calculating target measurement information, utilizing a sum-difference channel amplitude comparison angle measurement, carrying out centroid fusion on a detected target by taking a signal-to-noise ratio as a reference, carrying out track association in a plurality of scanning periods, matching corresponding early warning grades and early warning modes according to target data information, guiding the photoelectric equipment to acquire target image information, and sending early warning notification to early warning personnel according to the early warning modes.
The integrated units in the present application may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as stand alone products. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in whole or in part in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Note that the above is only a preferred embodiment of the present application and the technical principle applied. It will be understood by those skilled in the art that the present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the application. Therefore, while the application has been described in connection with the above embodiments, the application is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the application, which is set forth in the following claims.
The application discloses a low-speed small target detection method based on a self-adaptive threshold, which comprises the steps of removing direct current components of echo data in a distance dimension and a Doppler dimension; the pulse pressure result is subjected to coherent accumulation to obtain data to be detected, and a part of pulse compression results are selected in the Doppler dimension to perform coherent accumulation to extract a zero channel background; combining the Doppler window smoothing coefficient to obtain a Doppler threshold, and calculating the distance dimension threshold according to a distance unit where the target is and an STC attenuation curve; the constant false alarm detection is carried out on the sum channel by using two groups of self-adaptive thresholds, and the constant false alarm detection is compared with the position data corresponding to the difference channel, so that sidelobe interference is eliminated; and finally, carrying out fusion processing on the target, calculating track associated information, guiding the photoelectric equipment to carry out image detection and identification, and matching with a corresponding early warning processing mode. The method can remove the static target on the Doppler zero channel, effectively reserve the characteristic of the slow target and reduce the spurious false alarm.
Claims (10)
1. The low-speed small target detection method based on the self-adaptive threshold is characterized by comprising the following steps of:
and a data acquisition step: receiving signals from an antenna unit, and obtaining sum and difference channel echo data after preset processing;
and (3) pulse compression: pulse compression is carried out on return data collected by radar equipment;
and a phase-coherent accumulation step: performing coherent accumulation processing on the result output by the pulse compression step to obtain data to be detected, and performing coherent accumulation on the pulse compression result of the Doppler dimension selection part to extract zero channel background;
and a self-adaptive threshold calculating step: combining the Doppler window smoothing coefficient and the zero channel background to obtain a Doppler threshold, and calculating a distance threshold according to a distance unit where a target is and a short-range gain control attenuation curve;
and (3) constant false alarm detection: searching corresponding threshold values on a distance threshold curve and a Doppler threshold curve respectively according to a distance unit X and a Doppler channel Y where each detection point to be detected is located;
target fusion and early warning steps: and according to the target data information, matching the corresponding early warning grade and the early warning mode, guiding the photoelectric equipment to acquire the target image information, and sending an early warning notice to early warning personnel according to the early warning mode.
2. The adaptive threshold-based low-speed small target detection method according to claim 1, wherein the receiving the signal from the antenna unit and performing a preset process to obtain sum and difference channel echo data specifically includes:
the receiving channel receives signals from the antenna unit, outputs zero intermediate frequency IQ signals after amplification, filtering, attenuation control and twice down-conversion, wherein the sampling rate is 120MHz, the bandwidth is 25MHz or 50MHz, and finally FIR low-pass filtering is adopted to remove out-of-band spurious to obtain sum and difference channel echo data;
and selecting 1/16 pulse compression result in the phase-coherent accumulation step to perform phase-coherent accumulation.
3. The method for detecting a low-speed small target based on an adaptive threshold according to claim 1, wherein the method for detecting the low-speed small target based on the adaptive threshold is characterized by searching corresponding threshold values on a distance threshold curve and a doppler threshold curve according to a distance unit X and a doppler channel Y where each to-be-detected point is located, and specifically comprises the following steps:
when constant false alarm detection is carried out, corresponding threshold values are respectively searched on a distance threshold curve and a Doppler threshold curve according to the distance unit X and the Doppler channel Y where each detection point to be detected is located, so that a decision threshold is adaptively adjusted, and compared with position data corresponding to a symmetrical position data and a difference channel of the channel, and sidelobe interference is eliminated.
4. The adaptive threshold-based slow small target detection method as claimed in claim 1, wherein,
the return data collected by the radar device is pulse compressed,
the method specifically comprises the following steps:
and the return data acquired by the radar equipment is subjected to pulse compression after the direct current component is removed in the distance dimension, and the average value of all channels is subtracted in the Doppler dimension after the pulse compression.
5. The method for detecting a low-speed small target based on an adaptive threshold according to claim 1, wherein the steps of target fusion and early warning specifically comprise:
calculating target measurement information, utilizing a sum-difference channel amplitude comparison angle measurement, carrying out centroid fusion on a detected target by taking a signal-to-noise ratio as a reference, carrying out track association in a plurality of scanning periods, matching corresponding early warning grades and early warning modes according to target data information, guiding the photoelectric equipment to acquire target image information, and sending early warning notification to early warning personnel according to the early warning modes.
6. The adaptive threshold-based slow and small target detection method according to claim 1, wherein the slow and small target comprises an unmanned plane or a bird;
the radar equipment is an air-to-air low-speed small radar, adopts a pulse system, has three channels of sum, azimuth and pitch, and works in linkage with the photoelectric equipment;
the constant false alarm detection algorithm is a CA_CFAR algorithm, and a decision threshold value is adaptively adjusted in a distance dimension and a Doppler dimension according to a threshold curve;
the early warning step specifically comprises the following steps: and displaying the data information and the image information of the target to early warning personnel through a display.
7. The adaptive threshold-based slow small target detection method of claim 1, wherein the target data information includes a distance, a speed, a size, and an echo energy value of a target and a track correlation condition among a plurality of scan periods; the distance and the speed of the target are the radial distance and the radial speed, and the size of the target comprises the radial size and the transverse size; the radial dimension refers to the dimension obtained after the target fusion in a single coherent processing interval period; the transverse dimension refers to the dimension obtained after the targets are fused in a plurality of coherent processing interval periods; the echo energy value refers to the reflected energy value of the target to the radar signal of the radar apparatus.
8. The adaptive threshold-based slow small target detection method of claim 5, wherein the track association is a determination of target information during a plurality of scan cycles, if there is no track association point, it may be an isolated stray point or a stationary target, and if there is a stable track, it is a threatening moving target.
9. A low-speed small target detection device based on an adaptive threshold, comprising:
a memory for storing a program;
a processor for loading the program to perform the adaptive threshold based low slow small object detection method of any one of claims 1-8.
10. A computer readable storage medium, characterized in that it stores a program, which when executed by a processor, implements the adaptive threshold based slow small object detection method according to any of claims 1-8.
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