CN113820674A - Radar cross-sectional area real-time estimation algorithm - Google Patents
Radar cross-sectional area real-time estimation algorithm 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
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Abstract
The invention provides a radar sectional area real-time estimation algorithm, which belongs to the field of radar data processing and comprises the following steps of 1: measuring RCS coefficients of each waveform mode based on a reference target of known RCS; step 2: based on the known attenuation-distance mapping, the parameters of the waveform mode corresponding to the primary trace point, and the information of the distance, the echo energy and the like in the primary trace point information, the RCS of the primary trace point is obtained through calculation; and step 3: and when the track is associated with the track once, updating the RCS of the latest track point of the track by adopting a recursion filter. The RCS coefficient not only considers parameters such as distance, echo energy and the like in the traditional radar equation, but also considers parameters such as pulse width, coherent accumulation times and the like of different waveform modes. Therefore, the method has the advantages of convenience in operation, good practicability, high estimation precision and the like.
Description
Technical Field
The invention relates to the field of radar data processing, in particular to a radar sectional area real-time estimation algorithm.
Background
How to correctly identify targets such as unmanned aerial vehicles, people and vehicles is a research hotspot of the current anti-unmanned aerial vehicle Radar, the key of the classification identification problem is to select characteristic statistics which can better distinguish the targets, the Radar Cross Section (RCS) can represent the scattering characteristics of the targets, and the RCS of different targets is obviously different, so that the RCS is very suitable for target identification.
The formal definition of RCS is given in the Radar handbook:
in the formula, E0An electric field strength representing an incident wave irradiated onto the target; esAn electric field strength representing a scattered wave where the radar is located; a typical value of R is the distance of the radar to the target.
The existing real-time target RCS estimation results mainly include: the patent document "a method for predicting target RCS in radar tracking state" (application No. CN201410289649, publication No. CN104076342) mainly introduces the method for predicting RCS at the next time by using echo amplitude and distance information; in the patent document, "a method for estimating the flight height and the radar cross-sectional area of a high-altitude target based on position fingerprints" (application number: CN201510325672, publication number: CN105116393), position information and echo amplitude estimation are utilized, and the position information is mainly acquired; "multiple pulse radar target RCS characteristic measurement" (university of Kunming science and technology, science and technology edition, 2007(04):9-12.) of "Xijian et al, 2007] derives the RCS measurement method based on the radar equation, but in the radar of the pulse Doppler system, the radar equation also needs to consider parameters such as pulse width and coherent accumulation times under different waveform modes.
Disclosure of Invention
The invention aims to solve the defects in the prior art and provides a radar cross section real-time estimation algorithm.
In order to achieve the purpose, the invention adopts the following technical scheme: a radar cross-sectional area real-time estimation algorithm comprises the following steps:
step 1: measuring RCS coefficients of each waveform mode based on a reference target of known RCS;
step 2: based on the known attenuation-distance mapping, the parameters of the waveform mode corresponding to the primary trace point, and the information of the distance, the echo energy and the like in the primary trace point information, the RCS of the primary trace point is obtained through calculation;
and step 3: and when the track is associated with the track once, updating the RCS of the latest track point of the track by adopting a recursion filter.
Further, the RCS coefficient in step 1 is calculated by the following formula:
in the formula, alphaiRCS coefficients for the ith waveform mode; tau isiThe pulse width of the transmitted signal in the ith waveform mode is second(s); n is a radical ofiIs the pulse number of coherent accumulation of the ith waveform mode, and is dimensionless; drThe total attenuation of the receiver attenuator when testing the reference target is dimensionless; tau isrA transmission signal pulse width in seconds(s) which is a waveform pattern at the time of testing a reference target; n is a radical ofrIs a test referenceThe pulse number of coherent accumulation of the waveform mode at the target is dimensionless; rrIs the linear distance between the reference target and the radar in meters (m); prIs the echo power of the reference target in watts (W); sigma0RCS as a reference target in square meters (m)2)。
Further, the RCS coefficient in step 1 is measured by the following method:
using different targets, different distances and different attenuations, making M measurements, taking the average of the RCS coefficient measurements, i.e.
Further, the RCS calculation method in step 2 is:
in the formula, σ1The RCS of the target corresponding to the one-time trace point; r1The distance of the one-time trace point is measured in meters (m); p1The power of the one-time trace is in watt (W); i is a waveform mode subscript corresponding to the one-time trace point, and is dimensionless; di(R1) For the ith waveform mode at a distance R1Attenuation of (d), dimensionless; alpha is alphaiIs the RCS coefficient for the ith waveform mode.
Further, the recursive filter in step 3 is of the form:
σT(k)＝(1-β)·σT(k-1)+β·σ1(k)
in the formula, k is the sampling time of the flight path; sigmaT(k) RCS of the flight path at a sampling time k; sigma1(k) RCS of one trace point; beta is the iterative weight of the filter, and RCS mutation caused by occlusion, attitude change and the like can be prevented by recursion of the filter.
Compared with the prior art, the invention has the advantages and positive effects that,
the invention is suitable for a pulse Doppler system radar, firstly, the RCS of a primary trace point detected by the radar is estimated, then, a recursive filter is adopted to update the RCS of the trace, and the detailed steps are as follows: firstly, measuring RCS coefficients of each waveform mode based on a reference target of known RCS; then, based on the known attenuation-distance mapping, parameters such as pulse width and coherent accumulated pulse number of a waveform mode corresponding to the primary trace point and information such as distance and echo energy in the primary trace point information, calculating to obtain the RCS of the primary trace point; and finally, after the track is associated with the flight track once, updating the RCS of the latest track point of the flight track by adopting a recursion filter.
The RCS coefficient provided by the invention not only considers the parameters such as distance, echo energy and the like in the traditional radar equation, but also considers the parameters such as pulse width, coherent accumulation times and the like of different waveform modes, in addition, the measurement of the RCS coefficient does not need a darkroom, can be obtained through an external field test, and the RCS coefficient of one waveform mode can be obtained to obtain the RCS coefficients of other waveform modes, so the method has the advantages of convenience in operation, good practicability, high estimation precision and the like.
Drawings
FIG. 1 is a flow chart of a track RCS real-time estimation algorithm;
fig. 2 is a sequence diagram of RCS coefficients for waveform mode 0;
fig. 3 is a sequence diagram of RCS coefficients for waveform mode 1;
fig. 4 is a diagram showing the results of RCS measurement in the waveform pattern 0 of the target with RCS-20 dBm 2;
fig. 5 is a diagram showing the results of RCS measurement in the waveform pattern 1 of the target with RCS-20 dBm 2.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1 to 5, the present invention provides a technical solution: a radar cross-sectional area real-time estimation algorithm comprises the following steps:
step 1: measuring RCS coefficients of each waveform mode based on a reference target of known RCS;
step 2: based on the known attenuation-distance mapping, the parameters of the waveform mode corresponding to the primary trace point, and the information of the distance, the echo energy and the like in the primary trace point information, the RCS of the primary trace point is obtained through calculation;
and step 3: and when the track is associated with the track once, updating the RCS of the latest track point of the track by adopting a recursion filter.
Wherein, the RCS coefficient in step 1 has a calculation formula:
in the formula, alphaiRCS coefficients for the ith waveform mode; tau isiThe pulse width of the transmitted signal in the ith waveform mode is second(s); n is a radical ofiIs the pulse number of coherent accumulation of the ith waveform mode, and is dimensionless; drThe total attenuation of the receiver attenuator when testing the reference target is dimensionless; tau isrA transmission signal pulse width in seconds(s) which is a waveform pattern at the time of testing a reference target; n is a radical ofrThe pulse number of coherent accumulation of the waveform mode when the reference target is tested is dimensionless; rrIs the linear distance between the reference target and the radar in meters (m); prIs the echo power of the reference target in watts (W); sigma0RCS as a reference target in square meters (m)2)。
Wherein, the RCS coefficient in step 1 is measured by the following method:
using different targets, different distances and different attenuations, making M measurements, taking the average of the RCS coefficient measurements, i.e.
The RCS calculation method in step 2 is:
in the formula, σ1The RCS of the target corresponding to the one-time trace point; r1The distance of the one-time trace point is measured in meters (m); p1The power of the one-time trace is in watt (W); i is a waveform mode subscript corresponding to the one-time trace point, and is dimensionless; di(R1) For the ith waveform mode at a distance R1Attenuation of (d), dimensionless; alpha is alphaiIs the RCS coefficient for the ith waveform mode.
Wherein, the recursive filter in the step 3 has the following form:
σT(k)＝(1-β)·σT(k-1)+β·σ1(k)
in the formula, k is the sampling time of the flight path; sigmaT(k) RCS of the flight path at a sampling time k; sigma1(k) RCS of one trace point; beta is the iterative weight of the filter, and RCS mutation caused by occlusion, attitude change and the like can be prevented by recursion of the filter.
The invention is suitable for the pulse Doppler system radar. The RCS coefficient provided by the invention not only considers the parameters such as distance, echo energy and the like in the traditional radar equation, but also considers the parameters such as pulse width, coherent accumulation times and the like of different waveform modes, in addition, the measurement of the RCS coefficient does not need a darkroom, can be obtained through an external field test, and the RCS coefficient of one waveform mode can be obtained, namely the RCS coefficients of other waveform modes, so that the method has the advantages of good practicability, high estimation precision and the like.
The actual measurement results of the RCS coefficients of two different waveform modes are given below, the waveform parameters adopted by the two waveform modes and the RCS of the reference target are shown in the following table, and the RCS coefficients of the waveform mode 0 and the waveform mode 1 are shown in fig. 2 and fig. 3, respectively.
The results of the RCS measurement of the target RCS in the waveform pattern 0 and the waveform pattern 1 are shown in fig. 4 and 5, respectively, when the RCS is-20 dBm 2.
The above description is only a preferred embodiment of the present invention, and not intended to limit the present invention in other forms, and any person skilled in the art may apply the above modifications or changes to the equivalent embodiments with equivalent changes, without departing from the technical spirit of the present invention, and any simple modification, equivalent change and change made to the above embodiments according to the technical spirit of the present invention still belong to the protection scope of the technical spirit of the present invention.
Claims (5)
1. A radar cross section real-time estimation algorithm is characterized by comprising the following steps:
step 1: measuring RCS coefficients of each waveform mode based on a reference target of known RCS;
step 2: based on the known attenuation-distance mapping, the parameters of the waveform mode corresponding to the primary trace point, and the information of the distance, the echo energy and the like in the primary trace point information, the RCS of the primary trace point is obtained through calculation;
and step 3: and when the track is associated with the track once, updating the RCS of the latest track point of the track by adopting a recursion filter.
2. A radar cross-sectional area real-time estimation algorithm according to claim 1, wherein: the RCS coefficient in step 1 has a calculation formula:
in the formula, alphaiRCS coefficients for the ith waveform mode; tau isiThe pulse width of the transmitted signal in the ith waveform mode is second(s); n is a radical ofiIs the ith waveform modeThe pulse number of coherent accumulation of the formula (I) is dimensionless; drThe total attenuation of the receiver attenuator when testing the reference target is dimensionless; tau isrA transmission signal pulse width in seconds(s) which is a waveform pattern at the time of testing a reference target; n is a radical ofrThe pulse number of coherent accumulation of the waveform mode when the reference target is tested is dimensionless; rrIs the linear distance between the reference target and the radar in meters (m); prIs the echo power of the reference target in watts (W); sigma0RCS as a reference target in square meters (m)2)。
3. A radar cross-sectional area real-time estimation algorithm according to claim 1, wherein: the measurement method of the RCS coefficient in the step 1 is as follows:
using different targets, different distances and different attenuations, making M measurements, taking the average of the RCS coefficient measurements, i.e.
4. A radar cross-sectional area real-time estimation algorithm according to claim 1, wherein: the RCS calculation method in step 2 is:
in the formula, σ1The RCS of the target corresponding to the one-time trace point; r1The distance of the one-time trace point is measured in meters (m); p1The power of the one-time trace is in watt (W); i is a waveform mode subscript corresponding to the one-time trace point, and is dimensionless; di(R1) For the ith waveform mode at a distance R1Attenuation of (d), dimensionless; alpha is alphaiIs the RCS coefficient for the ith waveform mode.
5. A radar cross-sectional area real-time estimation algorithm according to claim 1, wherein: the recursive filter in step 3 is in the form of:
σT(k)＝(1-β)·σT(k-1)+β·σ1(k)
in the formula, k is the sampling time of the flight path; sigmaT(k) RCS of the flight path at a sampling time k; sigma1(k) RCS of one trace point; beta is the iterative weight of the filter, and RCS mutation caused by occlusion, attitude change and the like can be prevented by recursion of the filter.
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