CN112162247A - Method for calculating target discovery probability of multi-radar networking detection system - Google Patents
Method for calculating target discovery probability of multi-radar networking detection system Download PDFInfo
- Publication number
- CN112162247A CN112162247A CN202010848455.4A CN202010848455A CN112162247A CN 112162247 A CN112162247 A CN 112162247A CN 202010848455 A CN202010848455 A CN 202010848455A CN 112162247 A CN112162247 A CN 112162247A
- Authority
- CN
- China
- Prior art keywords
- radar
- target
- sub
- detection
- probability
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- 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
- G01S7/40—Means for monitoring or calibrating
Abstract
The application provides a method and a device for calculating target discovery probability of a multi-radar networking detection system, wherein the method comprises the following steps: determining the detection times of each sub radar on the target and the state parameter during each detection according to the radar scattering cross section, the flight speed, the flight path of the detected target and the characteristic parameters and the coordinates of a plurality of sub radars in the radar system; determining the instantaneous discovery probability of each sub radar in each target detection according to the detection times of the sub radars to the target and the state parameter in each detection; determining the accumulated discovery probability of each sub radar to the target according to the instantaneous discovery probability of each sub radar to the target during each detection; and fusing the accumulated discovery probability of the target according to each sub radar to determine the discovery probability of the target. Therefore, the coverage of space, time and frequency can be enlarged through radar networking, and the spatial resolution and the target discovery probability in an overlapping area are improved.
Description
Technical Field
The application relates to the technical field of radar detection, in particular to a method and a device for calculating target discovery probability of a multi-radar networking detection system.
Background
In the information-based war, air attacks and anti-air attacks have become a main battle mode of the war. The types of the air attack targets present diversified trends, meanwhile, the air attack targets present the characteristics of multi-batch, multi-azimuth and continuous saturated attack, and in addition, a plurality of non-attack targets exist in the air.
At present, when an early warning detection system is formed after a plurality of ground air defense early warning radars are networked, targets flying through the early warning detection system in a combined detection envelope can be found. However, the existing radar networking detection system has low accuracy in finding the target and cannot accurately find the target flying through the detection range.
Disclosure of Invention
The present application is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, the method for calculating the target discovery probability of the multi-radar networking detection system is provided, so as to solve the technical problem that the accuracy of the radar networking detection system in the prior art for discovering the target is low.
An embodiment of one aspect of the present application provides a method for calculating a target discovery probability of a multi-radar networking detection system, including:
determining the detection times of each sub radar on the target and the state parameter of each detection according to the radar scattering cross section, the flight speed, the flight path of the detected target and the characteristic parameters and the coordinates of a plurality of sub radars in the radar system;
determining the instantaneous discovery probability of each sub radar in each detection of the target according to the detection times of the sub radars to the target and the state parameters in each detection;
determining the accumulated discovery probability of each sub radar to the target according to the instantaneous discovery probability of each sub radar to the target during each detection;
and fusing the accumulated discovery probability of each sub-radar to the target by adopting a data fusion criterion so as to determine the discovery probability of the multi-radar networking detection system to the target.
Optionally, the determining, according to the number of times of detection of the target by the multiple sub-radars and the state parameter during each detection, an instantaneous discovery probability during each detection of the target by each sub-radar includes:
determining the relative position of the target and the sub radar according to the real-time position of each sub radar and the target;
acquiring a radar scattering sectional area of the target;
determining the signal-to-noise ratio of the sub-radar receiving end according to the relative position of the target and the sub-radar and the radar scattering cross section area of the target;
and determining the instantaneous discovery probability of the sub radar in each target detection according to the signal-to-noise ratio of the sub radar receiving end.
Optionally, the determining, according to the instantaneous discovery probability of each sub radar for each detection of the target, an accumulated discovery probability of each sub radar for the target includes:
inputting the instantaneous discovery probability of each sub radar in each detection of the target into a calculation formula to obtain the accumulated discovery probability of each sub radar in the target, wherein the calculation formula is as follows:
wherein, PDFor the sub radar toCumulative probability of discovery of an object, pdiAnd M is the instantaneous discovery probability of the sub radar in the ith detection of the target, wherein M is the detection times of the sub radar on the target, and i is a positive integer.
Optionally, the determining the number of detections of each sub radar on the target includes:
determining the time of the target passing through the detection area of each sub-radar according to the flying speed and the flying route of the target;
acquiring the scanning period of each sub radar;
respectively calculating the ratio of the time of the target passing through the detection area of each sub-radar to the scanning period of the corresponding sub-radar;
and rounding each ratio to determine the detection times of each sub radar on the target.
Optionally, the fusing the accumulated discovery probability of each sub-radar on the target by using a data fusion criterion to determine the discovery probability of the multi-radar networking detection system on the target, further includes:
if the number of the sub-radars with the accumulated discovery probability of the target larger than the probability threshold is larger than the preset number, determining that the multi-radar networking detection system discovers the target;
and if the number of the sub-radars with the accumulated discovery probability of the target larger than the probability threshold is smaller than or equal to the preset number, determining that the target is not discovered by the multi-radar networking detection system.
According to the method for calculating the target discovery probability of the multi-radar networking detection system, the detection times of each sub-radar on the target and the state parameter of each detection are determined according to the radar scattering sectional area, the flight speed, the flight path of the detected target and the characteristic parameters and the coordinates of a plurality of sub-radars in the radar system; determining the instantaneous discovery probability of each sub radar in each target detection according to the detection times of the sub radars to the target and the state parameter in each detection; determining the accumulated discovery probability of each sub radar to the target according to the instantaneous discovery probability of each sub radar to the target during each detection; and fusing the accumulated discovery probability of each sub-radar to the target by adopting a data fusion criterion so as to determine the discovery probability of the multi-radar networking detection system to the target. Therefore, the coverage of space, time and frequency can be enlarged through radar networking, the spatial resolution and the target discovery probability in an overlapping area can be improved, and the observation precision is improved.
In another embodiment of the present application, a device for calculating a target discovery probability of a multi-radar networking detection system is provided, including:
the first determination module is used for determining the detection times of each sub radar on the target and the state parameter during each detection according to the radar scattering cross section area, the flight speed, the flight path of the detected target and the characteristic parameters and the coordinates of the sub radars in the radar system;
the second determination module is used for determining the instantaneous discovery probability of each sub radar in each detection of the target according to the detection times of the sub radars to the target and the state parameters in each detection;
a third determining module, configured to determine, according to the instantaneous discovery probability of each sub-radar in each detection of the target, an accumulated discovery probability of each sub-radar for the target;
and the fourth determination module is used for fusing the accumulated discovery probability of each sub-radar on the target by adopting a data fusion criterion so as to determine the discovery probability of the multi-radar networking detection system on the target.
According to the target discovery probability calculation device of the multi-radar networking detection system, the detection times of each sub-radar on the target and the state parameter of each detection are determined according to the radar scattering sectional area, the flight speed, the flight path of the detected target and the characteristic parameters and the coordinates of the sub-radars in the radar system; determining the instantaneous discovery probability of each sub radar in each target detection according to the detection times of the sub radars to the target and the state parameter in each detection; determining the accumulated discovery probability of each sub radar to the target according to the instantaneous discovery probability of each sub radar to the target during each detection; and fusing the accumulated discovery probability of each sub-radar to the target by adopting a data fusion criterion so as to determine the discovery probability of the multi-radar networking detection system to the target. Therefore, the coverage of space, time and frequency can be enlarged through radar networking, the space resolution and the target discovery probability in an overlapping area are improved, and the observation precision is improved.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
Drawings
The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a schematic flowchart of a method for calculating a target discovery probability of a multi-radar networking detection system according to an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of a device for calculating a target discovery probability of a multi-radar networking detection system according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
The following describes a method and an apparatus for calculating a target discovery probability of a multi-radar networking detection system according to an embodiment of the present application with reference to the drawings.
Fig. 1 is a schematic flowchart of a method for calculating a target discovery probability of a multi-radar networking detection system according to an embodiment of the present application.
As shown in fig. 1, the method for calculating the target discovery probability of the multi-radar networking detection system includes the following steps:
The detected target can be a cruise missile. The characteristic parameters of the radar can be the detection area, the maximum detection distance, the scanning period and the like of the radar. The state parameter when each sub radar detects the target may be a position of each sub radar.
It should be explained that there is a corresponding relationship between the maximum detection distance of the radar and the radar scattering cross-sectional area of the target. Therefore, the radar cross-sectional area of the target is closely related to the threat level.
For example, since the flight altitude of the main cruise flight section of the cruise missile does not exceed 1km, the main cruise flight section of the cruise missile can be regarded as head-up illumination when being irradiated by a ground (sea) based radar, namely, the radar scattering cross section value of the target can be regarded as a function of the detection azimuth angle only. For example, the radar scattering cross-sectional area value of the target may be 0.2m2。
According to the method and the device, the deployment position of each sub radar can be determined by acquiring the coordinates of each sub radar in the radar system, and then the detection area of each sub radar is determined.
In the method, the time that the target passes through the detection area of each sub-radar can be determined according to the flying speed and the flying route of the target, the scanning period of each sub-radar is obtained, the ratio of the time that the target passes through the detection area of each sub-radar to the scanning period of the corresponding sub-radar is calculated respectively, and then, each ratio is rounded so as to determine the detection times of each sub-radar to the target.
And step 102, determining the instantaneous discovery probability of each sub radar in each target detection according to the detection times of the sub radars to the target and the state parameters in each detection.
In the present application, the probability of finding a target by each sub-radar is the most important performance index of various radars aiming at finding the target. The radar discovery probability model can visually describe the spatial distribution of the radar to the discovery probability of the aerial target. The discovery probability of each sub radar to the target comprises an instantaneous discovery probability and an accumulated discovery probability.
The instantaneous discovery probability, also referred to as radar working frame discovery probability, is a probability that a target is determined to exist by one-time scanning of a radar. For the radar of the conventional mechanical scanning system, the working frame period is the scanning period (generally expressed by RPM, and the rotating speed per minute); for phased array systems, the working frame period corresponds to the beam scheduling period.
The instantaneous discovery probability calculation of the radar is to give the discovery probability value of the radar to the cruise missile in a working frame period according to the working frame period of a given radar (such as a search radar and an air-ground missile guidance radar) and the real-time position of a target, in combination with the scanning characteristics of a radar antenna (for a machine-scanning radar, the initial antenna pointing direction and the beam scanning rule are included; for a phased array system, the beam scheduling period and the beam residence time are included).
In this application, according to the real-time position of each minute radar and target, confirm the relative position of target and branch radar, acquire the radar scattering sectional area of target, according to the relative position of target and branch radar and the radar scattering sectional area of target, confirm the SNR of dividing the radar receiving terminal, and then, according to the SNR of dividing the radar receiving terminal, confirm the instantaneous probability of finding when dividing the radar to target each time of exploring.
In the radar beam scanning process, when a target falls into a radar lobe, the target is in energy contact with the radar, and whether a target signal can be detected on a radar fluorescent screen depends on the ratio of signal energy to noise energy.
According to the statistical characteristics of noise and signals passing through a radar receiver, the calculation formula of the radar instantaneous discovery probability during monopulse detection is as follows:
wherein, PdFor radar instantaneous probability of discovery, PfaThe false alarm probability is expressed, and S/N is the signal-to-noise ratio of the radar receiving end. According to the formula, under the condition of giving false alarm probability, the instantaneous discovery probability of the radar is calculated, and the key is to calculate the signal-to-noise ratio or the signal-to-interference ratio of the radar receiving end.
The calculation formula of the signal-to-noise ratio of the radar receiving end is as follows:
wherein, (S/N)minMaximum detection range R given for radar performance manualmax0Discovery probability PdThen, the corresponding minimum detectable signal-to-noise ratio; sigma0Maximum detection range R given for radar performance manualmax0Discovery probability PdAnd the corresponding target radar scattering cross section area.
And 103, determining the accumulated discovery probability of each sub radar to the target according to the instantaneous discovery probability of each sub radar to the target during each detection.
When a target flies through a radar detection area according to a certain route shortcut, the target can be detected by the radar for multiple times, the instantaneous discovery probability is different due to the difference of the distance, the direction and the radar scattering sectional area in each detection, and the instantaneous discovery probabilities can be comprehensively considered to reflect the detection condition of the whole route. The radar cannot recognize the radar as intercepting the target when detecting the target in a single scanning, but at least needs to detect the target continuously for a plurality of times to recognize the target as intercepting the target, and the cumulative probability of detection of each time is generally considered as the cumulative discovery probability.
In this application, the instantaneous probability of finding when each branch radar is to the target each time is input into the computational formula to obtain the accumulation probability of finding of each branch radar to the target, wherein, the computational formula is:
wherein, PDFor cumulative probability of finding targets by sub-radar, PdiThe instantaneous discovery probability of the sub radar in the ith detection of the target is shown, M is the detection frequency of the sub radar on the target, and i is a positive integer.
And step 104, fusing the accumulated discovery probability of each sub-radar to the target by adopting a data fusion criterion so as to determine the discovery probability of the multi-radar networking detection system to the target.
The discovery probability of the multi-radar networking detection system on the target refers to the target discovery probability obtained by the information fusion center. Taking a typical distributed multi-radar detection system as an example, it is assumed that the detection system is composed of N radars, and data sharing and information fusion are realized among the radars through a data link and the like. And (3) adopting a 'K out of N' fusion criterion for finding the target, namely judging that the target is found when the number of the radars of the target found in the detection system exceeds a detection threshold K, and otherwise, judging that the target is not found.
In one case, if the number of the sub-radars with the accumulated discovery probability of the target larger than the probability threshold is larger than the preset number, it is determined that the multi-radar networking detection system discovers the target.
For example, if the multi-radar networking detection system is composed of 5 radars, if the preset number is 3, and the number of the sub radars with the accumulated discovery probability of the target being greater than the probability threshold is greater than 3, it is determined that the multi-radar networking detection system can discover the target.
In another case, if the number of the sub-radars with the accumulated discovery probability of the target larger than the probability threshold is smaller than or equal to the preset number, it is determined that the multi-radar networking detection system does not discover the target.
For example, if the multi-radar networking detection system is composed of 5 radars, if the preset number is 3, and the number of sub-radars with the accumulated discovery probability of the target being greater than the probability threshold is less than 3, it is determined that the multi-radar networking detection system does not discover the target.
Let A denote the decision vector formed by each distributed radar, i.e. A ═ a1，a2，…，aN) The decision vector is sent to the data fusion center, the data fusion centerMake global decision according to A, all combinations of A have 2NThe method comprises the following steps:
assuming that the data fusion criterion is represented by the function r (a), the "K out of N" fusion criterion can be expressed as:
wherein K is an integer from 1 to N, H0Indicating that the target is not present; h1Indicating that the target is present.
The total discovery probability of the multi-radar networking detection system to the target after data fusion is as follows:
wherein, PD0Total probability of discovery of targets for multi-radar networked detection system, S0Representing a radar set with an element value of 0 in the decision vector A, namely that all radars in the set judge that a target does not exist; s1Representing a radar set with a judgment result of 1 in the step A; pDkAnd finding the probability of the accumulation of the target for the kth radar.
According to the method for calculating the target discovery probability of the multi-radar networking detection system, the detection times of each sub-radar on the target and the state parameter of each detection are determined according to the radar scattering sectional area, the flight speed, the flight path of the detected target and the characteristic parameters and the coordinates of a plurality of sub-radars in the radar system; determining the instantaneous discovery probability of each sub radar in each target detection according to the detection times of the sub radars to the target and the state parameter in each detection; determining the accumulated discovery probability of each sub radar to the target according to the instantaneous discovery probability of each sub radar to the target during each detection; and fusing the accumulated discovery probability of each sub-radar to the target by adopting a data fusion criterion so as to determine the discovery probability of the multi-radar networking detection system to the target. Therefore, the coverage of space, time and frequency can be enlarged through radar networking, the space resolution and the target discovery probability in an overlapping area are improved, and the observation precision is improved.
In order to implement the foregoing embodiment, an embodiment of the present application further provides a device for calculating a target discovery probability of a multi-radar networking detection system.
Fig. 2 is a schematic structural diagram of a device for calculating a target discovery probability of a multi-radar networking detection system according to an embodiment of the present application.
As shown in fig. 2, the apparatus 200 for calculating a target discovery probability of the multi-radar networking detection system may include: a first determination module 210, a second determination module 220, a third determination module 230, and a fourth determination module 240.
The first determining module 210 is configured to determine, according to a radar scattering cross-sectional area, a flight speed, a flight path of a detected target, and characteristic parameters and coordinates of a plurality of sub-radars in a radar system, the number of times that each sub-radar detects the target and a state parameter during each detection.
The second determining module 220 is configured to determine, according to the detection times of the targets by the multiple sub-radars and the state parameter during each detection, an instantaneous discovery probability during each detection of the targets by each sub-radar.
And a third determining module 230, configured to determine an accumulated discovery probability of each sub-radar for the target according to the instantaneous discovery probability of each sub-radar for the target during each detection.
And a fourth determining module 240, configured to fuse the accumulated discovery probability of each sub-radar on the target by using a data fusion criterion, so as to determine the discovery probability of the multi-radar networking detection system on the target.
Optionally, the second determining module 220 may be further configured to:
determining the relative positions of the target and the sub-radars according to the real-time positions of each sub-radar and the target; acquiring a radar scattering sectional area of a target; determining the signal-to-noise ratio of the sub-radar receiving end according to the relative position of the target and the sub-radar and the radar scattering cross section area of the target; and determining the instantaneous discovery probability of the sub radar in each target detection according to the signal-to-noise ratio of the sub radar receiving end.
Optionally, the third determining module 230 may be further configured to:
inputting the instantaneous discovery probability of each sub radar in each target detection into a calculation formula to obtain the accumulated discovery probability of each sub radar in the targets, wherein the calculation formula is as follows:
wherein, PDFor cumulative probability of discovery of targets by sub-radar, pdiThe instantaneous discovery probability of the sub radar in the ith detection of the target is shown, M is the detection frequency of the sub radar on the target, and i is a positive integer.
Optionally, the first determining module 210 may be further configured to:
determining the time of the target passing through the detection area of each sub-radar according to the flying speed and the flying route of the target; acquiring the scanning period of each sub radar; respectively calculating the ratio of the time of the target passing through the detection area of each sub radar to the scanning period of the corresponding sub radar; and rounding each ratio to determine the detection times of each sub radar to the target.
Optionally, the fourth determining module 240 may be further configured to:
if the number of the sub-radars with the accumulated discovery probability of the target larger than the probability threshold is larger than the preset number, determining that the multi-radar networking detection system discovers the target;
and if the number of the sub-radars with the accumulated discovery probability of the target larger than the probability threshold is smaller than or equal to the preset number, determining that the multi-radar networking detection system does not discover the target.
According to the target discovery probability calculation device of the multi-radar networking detection system, the detection times of each sub-radar on the target and the state parameter of each detection are determined according to the radar scattering sectional area, the flight speed, the flight path of the detected target and the characteristic parameters and the coordinates of the sub-radars in the radar system; determining the instantaneous discovery probability of each sub radar in each target detection according to the detection times of the sub radars to the target and the state parameter in each detection; determining the accumulated discovery probability of each sub radar to the target according to the instantaneous discovery probability of each sub radar to the target during each detection; and fusing the accumulated discovery probability of each sub-radar to the target by adopting a data fusion criterion so as to determine the discovery probability of the multi-radar networking detection system to the target. Therefore, the coverage of space, time and frequency can be enlarged through radar networking, the space resolution and the target discovery probability in an overlapping area are improved, and the observation precision is improved.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (10)
1. A method for calculating a target discovery probability of a multi-radar networking detection system, the method comprising:
determining the detection times of each sub radar on the target and the state parameter of each detection according to the radar scattering cross section area of the detected target, the flight speed, the flight path and the characteristic parameters and the coordinates of a plurality of sub radars in the radar system;
determining the instantaneous discovery probability of each sub radar in each detection of the target according to the detection times of the sub radars to the target and the state parameters in each detection;
determining the accumulated discovery probability of each sub radar to the target according to the instantaneous discovery probability of each sub radar to the target during each detection;
and fusing the accumulated discovery probability of each sub-radar to the target by adopting a data fusion criterion so as to determine the discovery probability of the multi-radar networking detection system to the target.
2. The calculation method according to claim 1, wherein the determining the instantaneous discovery probability of each sub radar in each detection of the target according to the detection times of the sub radars on the target and the state parameter in each detection comprises:
determining the relative position of the target and the sub radar according to the real-time position of each sub radar and the target;
acquiring a radar scattering sectional area of the target;
determining the signal-to-noise ratio of the sub-radar receiving end according to the relative position of the target and the sub-radar and the radar scattering cross section area of the target;
and determining the instantaneous discovery probability of the sub radar in each target detection according to the signal-to-noise ratio of the sub radar receiving end.
3. The method of claim 1, wherein the determining the cumulative probability of discovery of the target for each of the sub-radars based on the instantaneous probability of discovery of the target for each of the sub-radars comprises:
inputting the instantaneous discovery probability of each sub radar in each detection of the target into a calculation formula to obtain the accumulated discovery probability of each sub radar in the target, wherein the calculation formula is as follows:
wherein, PDFor the accumulated discovery probability, P, of the sub-radar to the targetdiAnd M is the instantaneous discovery probability of the sub radar in the ith detection of the target, wherein M is the detection times of the sub radar on the target, and i is a positive integer.
4. The method of claim 1, wherein the determining the number of detections of the target by each sub-radar comprises:
determining the time of the target passing through the detection area of each sub-radar according to the flying speed and the flying route of the target;
acquiring the scanning period of each sub radar;
respectively calculating the ratio of the time of the target passing through the detection area of each sub-radar to the scanning period of the corresponding sub-radar;
and rounding each ratio to determine the detection times of each sub radar on the target.
5. The method of any one of claims 1-4, wherein the fusing the accumulated discovery probability of each sub-radar on the target using a data fusion criterion to determine the discovery probability of the multi-radar networking probe system on the target, further comprises:
if the number of the sub-radars with the accumulated discovery probability of the target larger than the probability threshold is larger than the preset number, determining that the multi-radar networking detection system discovers the target;
and if the number of the sub-radars with the accumulated discovery probability of the target larger than the probability threshold is smaller than or equal to the preset number, determining that the target is not discovered by the multi-radar networking detection system.
6. An apparatus for calculating a target discovery probability of a multi-radar networking detection system, comprising:
the first determination module is used for determining the detection times of each sub radar on the target and the state parameter during each detection according to the radar scattering cross section area, the flight speed, the flight path of the detected target and the characteristic parameters and the coordinates of the sub radars in the radar system;
the second determination module is used for determining the instantaneous discovery probability of each sub radar in each detection of the target according to the detection times of the sub radars to the target and the state parameters in each detection;
a third determining module, configured to determine, according to the instantaneous discovery probability of each sub-radar in each detection of the target, an accumulated discovery probability of each sub-radar for the target;
and the fourth determination module is used for fusing the accumulated discovery probability of each sub-radar on the target by adopting a data fusion criterion so as to determine the discovery probability of the multi-radar networking detection system on the target.
7. The computing device of claim 6, the second determination module to further:
determining the relative position of the target and the sub radar according to the real-time position of each sub radar and the target;
acquiring a radar scattering sectional area of the target;
determining the signal-to-noise ratio of the sub-radar receiving end according to the relative position of the target and the sub-radar and the radar scattering cross section area of the target;
and determining the instantaneous discovery probability of the sub radar in each target detection according to the signal-to-noise ratio of the sub radar receiving end.
8. The computing device of claim 6, the third determination module to further:
inputting the instantaneous discovery probability of each sub radar in each detection of the target into a calculation formula to obtain the accumulated discovery probability of each sub radar in the target, wherein the calculation formula is as follows:
wherein, PDCumulative probability of discovery of said target for said sub-radar, pdiAnd M is the instantaneous discovery probability of the sub radar in the ith detection of the target, wherein M is the detection times of the sub radar on the target, and i is a positive integer.
9. The computing device of claim 6, the first determination module further to:
determining the time of the target passing through the detection area of each sub-radar according to the flying speed and the flying route of the target;
acquiring the scanning period of each sub radar;
respectively calculating the ratio of the time of the target passing through the detection area of each sub-radar to the scanning period of the corresponding sub-radar;
and rounding each ratio to determine the detection times of each sub radar on the target.
10. The computing device of any of claims 6-9, wherein the fourth determination module is further configured to:
if the number of the sub-radars with the accumulated discovery probability of the target larger than the probability threshold is larger than the preset number, determining that the multi-radar networking detection system discovers the target;
and if the number of the sub-radars with the accumulated discovery probability of the target larger than the probability threshold is smaller than or equal to the preset number, determining that the target is not discovered by the multi-radar networking detection system.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010848455.4A CN112162247A (en) | 2020-08-21 | 2020-08-21 | Method for calculating target discovery probability of multi-radar networking detection system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010848455.4A CN112162247A (en) | 2020-08-21 | 2020-08-21 | Method for calculating target discovery probability of multi-radar networking detection system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112162247A true CN112162247A (en) | 2021-01-01 |
Family
ID=73859696
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010848455.4A Pending CN112162247A (en) | 2020-08-21 | 2020-08-21 | Method for calculating target discovery probability of multi-radar networking detection system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112162247A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113391305A (en) * | 2021-06-11 | 2021-09-14 | 森思泰克河北科技有限公司 | False target suppression method and device for multi-radar fusion and terminal equipment |
| CN113640760A (en) * | 2021-10-14 | 2021-11-12 | 中国人民解放军空军预警学院 | Radar discovery probability evaluation method and equipment based on air situation data |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002328164A (en) * | 2001-05-02 | 2002-11-15 | Mitsubishi Electric Corp | Target tracking method and radar system |
| CN104007424A (en) * | 2014-05-28 | 2014-08-27 | 电子科技大学 | Maneuvering target detection method based on time-frequency analysis |
| CN110687512A (en) * | 2019-07-02 | 2020-01-14 | 中国航空工业集团公司雷华电子技术研究所 | Multi-machine heterogeneous radar cooperative TBD processing method based on probability matrix |
-
2020
- 2020-08-21 CN CN202010848455.4A patent/CN112162247A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002328164A (en) * | 2001-05-02 | 2002-11-15 | Mitsubishi Electric Corp | Target tracking method and radar system |
| CN104007424A (en) * | 2014-05-28 | 2014-08-27 | 电子科技大学 | Maneuvering target detection method based on time-frequency analysis |
| CN110687512A (en) * | 2019-07-02 | 2020-01-14 | 中国航空工业集团公司雷华电子技术研究所 | Multi-machine heterogeneous radar cooperative TBD processing method based on probability matrix |
Non-Patent Citations (1)
| Title |
|---|
| 王旭 等: "飞行器被雷达发现概率的计算方法研究", 系统工程理论与实践, no. 6, pages 130 - 134 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113391305A (en) * | 2021-06-11 | 2021-09-14 | 森思泰克河北科技有限公司 | False target suppression method and device for multi-radar fusion and terminal equipment |
| CN113391305B (en) * | 2021-06-11 | 2022-09-30 | 森思泰克河北科技有限公司 | False target suppression method and device for multi-radar fusion and terminal equipment |
| CN113640760A (en) * | 2021-10-14 | 2021-11-12 | 中国人民解放军空军预警学院 | Radar discovery probability evaluation method and equipment based on air situation data |
| CN113640760B (en) * | 2021-10-14 | 2022-02-22 | 中国人民解放军空军预警学院 | Radar discovery probability evaluation method and equipment based on air situation data |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8013781B2 (en) | Method and apparatus for radar surveillance and detection of sea targets | |
| ES2634111T3 (en) | Method and apparatus for integration of distributed sensors and surveillance radar in airports to mitigate blind spots | |
| US7750840B2 (en) | Method and apparatus for assessing contact clusters | |
| KR101248045B1 (en) | Apparatus for identifying threat target considering maneuvering patterns | |
| CN112162247A (en) | Method for calculating target discovery probability of multi-radar networking detection system | |
| US6850186B2 (en) | System for determining position and velocity of targets from signals scattered by the targets | |
| Matuszewski | The analysis of modern radar signals parameters in electronic intelligence system | |
| KR0167430B1 (en) | Radar system and method for detecting targets in clutter using target intensity and angular position | |
| JP5622533B2 (en) | Radar equipment | |
| KR102264073B1 (en) | Formation flying tracking method and device | |
| CA2858440C (en) | Method for determining the impact point of a projectile fired at a target above sea surface, and radar system implementing such method | |
| Matuszewski | Specific emitter identification | |
| CN109407054A (en) | Wide interval radar node with non-fuzzy beam pattern | |
| CN103728615A (en) | Method and system for detecting a plurality of targets of phased array secondary radars | |
| CA2593436A1 (en) | Dual beam radar system | |
| US10277356B2 (en) | Multi-platform location deception system | |
| Smith et al. | Methods of associating CODAR SeaSonde vessel detection data into unique tracks | |
| CN112182501B (en) | Method and device for calculating burst prevention probability of cruise missile | |
| US6816109B1 (en) | Method for automatic association of moving target indications from entities traveling along known route | |
| EP3264649B1 (en) | Multi-platform location deception detection system | |
| JP3732123B2 (en) | Aircraft target classification device | |
| Matuszewski et al. | Knowledge-based signal processing for radar identification | |
| Umar et al. | Design, development and experimental validation of multi-target tracking framework for passive radar | |
| CN112149276A (en) | Method and device for calculating defense probability of batch flight path | |
| Singh et al. | Missile Trajectory Tracking Using IMM and GNN |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |