CN112462344B - Method for extracting characteristic parameters in radar signal pulse through time-frequency domain transformation processing - Google Patents
Method for extracting characteristic parameters in radar signal pulse through time-frequency domain transformation processing Download PDFInfo
- Publication number
- CN112462344B CN112462344B CN202011262631.2A CN202011262631A CN112462344B CN 112462344 B CN112462344 B CN 112462344B CN 202011262631 A CN202011262631 A CN 202011262631A CN 112462344 B CN112462344 B CN 112462344B
- Authority
- CN
- China
- Prior art keywords
- radon
- signal
- radar
- transformation processing
- frequency domain
- 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.)
- Active
Links
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
- G01S7/41—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
- G01S7/418—Theoretical aspects
-
- 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
- G01S7/28—Details of pulse systems
- G01S7/285—Receivers
- G01S7/295—Means for transforming co-ordinates or for evaluating data, e.g. using computers
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The invention relates to the field of radar signals, in particular to a method for extracting characteristic parameters in radar signal pulses through time-frequency domain transformation processing, which comprises the following steps: 1. performing fuzzy function transformation processing on the received radar signals; 2. carrying out Radon transformation processing on the fuzzy function; 3. and (5) obtaining the phase coefficient as a final radar signal intra-pulse characteristic parameter. The method for extracting the characteristic parameters in the radar signal pulse through the time-frequency domain transformation process disclosed by the invention shows that the phase coefficient characteristics of the signal fuzzy function Radon curves of different radar radiation sources are different, namely the method has better separability; on the other hand, the characteristic is less influenced by noise, namely, the characteristic has better stability, and a good foundation is laid for subsequent sorting.
Description
Technical Field
The invention relates to the field of radar signals, in particular to a method for extracting characteristic parameters in radar signal pulses through time-frequency domain transformation processing.
Background
With the increasing proportion of novel complex system radars, the role played by the signal sorting of unknown radar radiation sources in electronic warfare is increasingly important, and the problems to be solved are also increasingly more. Current radar radiation source signal sorting algorithms are mainly based on analyzing various conventional parameters of the intercepted signal, such as arrival time, arrival angle, carrier frequency, pulse width, etc. Among them, time of arrival sorting is a more commonly used method, such as sequence difference histogram, PRI transform, and modified PRI transform algorithm. However, these algorithms have certain drawbacks and are difficult to adapt to the current complex electromagnetic environment. The intra-pulse characteristic is one of the most characteristic parameters of the radar radiation source signals, and although the conventional parameters of some radar radiation source signals are rich in variation, the intra-pulse characteristic parameters have certain stability. Therefore, the invention provides an intra-pulse characteristic parameter based on time-frequency domain transformation processing, provides a detailed extraction process, carries out simulation analysis, and verifies the effectiveness and feasibility of the method.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a method for extracting the characteristic parameters in radar signal pulses through time-frequency domain transformation processing.
The technical scheme adopted for solving the technical problems is as follows: the method for extracting the characteristic parameters in the radar signal pulse through the time-frequency domain transformation process comprises the following steps:
(1) Performing fuzzy function transformation processing on the received radar signals;
for any narrowband radar radiation source signal, the expression is as follows
Wherein f 0 For the carrier frequency of the signal,for the initial phase, u (t) is the complex envelope of the signal;
the blurring function of x (t) is
Wherein τ is a delay, f d Is the Doppler frequency difference;
(2) Radon transformation of fuzzy function
Although the fuzzy function of the radar radiation source signal has better performance, the fuzzy function is a three-dimensional characteristic diagram, which is unfavorable for the subsequent sorting treatment, so that the fuzzy function needs to be considered for simplifying treatment;
the Radon transformation is based on the idea of projection integration, line integration is carried out along a specific direction, and the integrated value is projected onto a Radon transformation plane to obtain a Radon curve, wherein the Radon curve of an image along the theta direction is defined as:
wherein f (x, y) is an original image; g (s, θ) is a Radon curve; delta (·) is an impulse function, and it can be seen that when (s, θ) is determined, the formula (2.42) represents f (x, y) to perform line integration along the straight line l (s=xcos θ+ysin θ), so as to obtain a Radon curve g (s, θ);
(3) The phase coefficient is obtained and used as the final characteristic parameter in the radar signal pulse;
the mathematical expressions of the rectangular pulse sequence rect (k) and the triangular pulse sequence tri (k) constructed by the present invention are given below, as shown in the following formulas, wherein N is the sequence length of the Radon transformation process
Preferably, the common simplification methods mainly include: extracting diagonal information of the fuzzy function matrix; extracting a one-dimensional distance or speed fuzzy function; the method is used for extracting the maximum value of the horizontal slice or the longitudinal slice of the fuzzy function, and the like, but the methods can not avoid losing some useful information, and the noise immunity is not ideal enough.
Preferably, although the influence of noise is improved and the difference between different radar signals is highlighted after the fuzzy function Radon curve of the radar radiation source signal is obtained, the dimension is larger, the characteristic of the signal and the subsequent sorting identification are inconvenient, and the dimension reduction processing needs to be considered by utilizing some characteristics with simple extraction and strong applicability.
The invention has the beneficial effects that:
the method for extracting the characteristic parameters in the radar signal pulse through the time-frequency domain transformation process disclosed by the invention shows that the phase coefficient characteristics of the signal fuzzy function Radon curves of different radar radiation sources are different, namely the method has better separability; on the other hand, the characteristic is less influenced by noise, namely, the characteristic has better stability, and a good foundation is laid for subsequent sorting.
Drawings
The invention will be further described with reference to the drawings and examples.
FIG. 1 is a flowchart of a method for extracting characteristic parameters in radar signal pulses through time-frequency domain transformation processing;
FIG. 2 is a two-dimensional distribution of phase coefficient characteristics of class 8 radar radiation source signals in an environment corresponding to a 0dB signal-to-noise ratio;
FIG. 3 is a two-dimensional distribution diagram of phase coefficient characteristics of 8 types of radar radiation source signals in an environment corresponding to a 5dB signal-to-noise ratio;
FIG. 4 is a two-dimensional distribution of phase coefficient characteristics of 8-class radar radiation source signals in an environment corresponding to a 10dB signal-to-noise ratio;
fig. 5 is a two-dimensional distribution of phase coefficient characteristics of 8-class radar radiation source signals in an environment corresponding to a 15dB signal-to-noise ratio.
Detailed Description
The invention is further described in connection with the following detailed description in order to make the technical means, the creation characteristics, the achievement of the purpose and the effect of the invention easy to understand.
As shown in fig. 1 to 5, the method for extracting the characteristic parameters in the radar signal pulse through the time-frequency domain transformation processing according to the invention comprises the following steps:
(1) Performing fuzzy function transformation processing on the received radar signals;
for any narrowband radar radiation source signal, the expression is as follows
Wherein f 0 For the carrier frequency of the signal,for the initial phase, u (t) is the complex envelope of the signal;
the blurring function of x (t) is
Wherein τ is a delay, f d Is the Doppler frequency difference;
(2) Radon transformation of fuzzy function
Although the fuzzy function of the radar radiation source signal has better performance, the fuzzy function is a three-dimensional characteristic diagram, which is unfavorable for the subsequent sorting treatment, so that the fuzzy function needs to be considered for simplifying treatment, and the common simplifying method mainly comprises the following steps: extracting diagonal information of the fuzzy function matrix; extracting a one-dimensional distance or speed fuzzy function; the maximum value of the horizontal slice or the longitudinal slice of the fuzzy function is extracted, but the methods can not avoid losing some useful information, and the noise immunity is not ideal enough, in order to overcome the problems, the invention selects Radon transformation for simplifying processing, the transformation can realize the full-angle observation of the image, and the method is widely applied to the field of image processing;
the Radon transformation is based on the idea of projection integration, line integration is carried out along a specific direction, and the integrated value is projected onto a Radon transformation plane to obtain a Radon curve, wherein the Radon curve of an image along the theta direction is defined as:
wherein f (x, y) is an original image; g (s, θ) is a Radon curve; delta (·) is an impulse function, and it can be seen that when (s, θ) is determined, the formula (2.42) represents f (x, y) to perform line integration along the straight line l (s=xcos θ+ysin θ), so as to obtain a Radon curve g (s, θ);
(3) The phase coefficient is obtained and used as the final characteristic parameter in the radar signal pulse;
although the influence of noise is improved and the difference between different radar signals is highlighted after the fuzzy function Radon curve of the radar radiation source signal is obtained, the dimension is larger, the characteristic of the signal and the subsequent sorting identification are inconvenient to characterize, and the dimension reduction processing needs to be considered by utilizing some characteristics with simple extraction and strong applicability;
the mathematical expressions of the rectangular pulse sequence rect (k) and the triangular pulse sequence tri (k) constructed by the present invention are given below, as shown in the following formulas, wherein N is the sequence length of the Radon transformation process
In order to analyze the performance of the phase coefficient characteristics, when the signal to noise ratio is 0, 5, 10 and 15dB, the phase coefficients of the fuzzy function Radon curve, rectangular pulse and triangular pulse sequence of the 8 types of radar radiation source signals are respectively obtained, 200 signals are generated in each type of signal, and a two-dimensional distribution diagram of the phase coefficient characteristics of the 8 types of radar radiation source signals in the corresponding signal to noise ratio environment is obtained, as shown in fig. 2-5. 1-8 in FIGS. 2-5 represent CW, LFM, FSK, BPSK, QPSK, LFM-BPSK, FSK-BPSK and NLFM, respectively.
As can be seen from fig. 2 to fig. 5, when the signal-to-noise ratio is low, the 8 types of radar radiation source signals have overlapping of part of signal phase coefficient characteristics, and the same type of signal distribution is more dispersed; when the signal-to-noise ratio is high, the phase coefficient characteristics of 8 types of radar radiation source signals are easy to distinguish, and the same type of signals are concentrated in distribution. On one hand, the difference exists between the phase coefficient characteristics of the Radon curves of the signal blurring functions of different radar radiation sources, namely the better separability is achieved; on the other hand, the characteristic is less influenced by noise, namely, the characteristic has better stability, and a good foundation is laid for subsequent sorting.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the foregoing examples, and that the foregoing description and description are merely illustrative of the principles of this invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (1)
1. The method for extracting the characteristic parameters in the radar signal pulse through the time-frequency domain transformation processing is characterized by comprising the following steps:
(1) Performing fuzzy function transformation processing on the received radar signals;
for any narrowband radar radiation source signal, the expression is as follows
Wherein f 0 For the carrier frequency of the signal,for the initial phase, u (t) is the complex envelope of the signal;
the blurring function of x (t) is
Wherein τ is a delay, f d Is Doppler frequency difference；
(2) Radon transformation of fuzzy function
The Radon transformation is based on the idea of projection integration, line integration is carried out along a specific direction, and the integrated value is projected onto a Radon transformation plane to obtain a Radon curve, wherein the Radon curve of an image along the theta direction is defined as:
wherein f (x, y) is an original image; g (s, θ) is a Radon curve; delta (·) is an impulse function, and it can be seen that when (s, θ) is determined, the formula (2.42) represents f (x, y) to perform line integration along the straight line l (s=xcos θ+ysin θ), so as to obtain a Radon curve g (s, θ);
(3) The phase coefficient is obtained and used as the final characteristic parameter in the radar signal pulse;
the mathematical expressions of the rectangular pulse sequence rect (k) and the triangular pulse sequence tri (k) constructed by the method are given below, as shown in the following formulas, wherein N is the sequence length of the Radon transformation process
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011262631.2A CN112462344B (en) | 2020-11-12 | 2020-11-12 | Method for extracting characteristic parameters in radar signal pulse through time-frequency domain transformation processing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011262631.2A CN112462344B (en) | 2020-11-12 | 2020-11-12 | Method for extracting characteristic parameters in radar signal pulse through time-frequency domain transformation processing |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112462344A CN112462344A (en) | 2021-03-09 |
| CN112462344B true CN112462344B (en) | 2023-09-19 |
Family
ID=74825646
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011262631.2A Active CN112462344B (en) | 2020-11-12 | 2020-11-12 | Method for extracting characteristic parameters in radar signal pulse through time-frequency domain transformation processing |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112462344B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113238200B (en) * | 2021-04-20 | 2024-09-17 | 上海志良电子科技有限公司 | Classification method of radar linear frequency modulation signals based on validity verification |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8044846B1 (en) * | 2007-11-29 | 2011-10-25 | Lockheed Martin Corporation | Method for deblurring radar range-doppler images |
| CN102279390A (en) * | 2011-05-06 | 2011-12-14 | 西南交通大学 | Intra-pulse modulation and recognition method of low signal-to-noise radar radiation source signal |
| CN106772308A (en) * | 2017-03-21 | 2017-05-31 | 中国人民解放军国防科学技术大学 | Terahertz wideband radar micro-doppler ambiguity solution method based on arteries and veins internal interference |
| CN109613489A (en) * | 2018-11-21 | 2019-04-12 | 昆明理工大学 | A kind of Radar Signal Sorting Method based on ambiguity function geomorphic feature |
-
2020
- 2020-11-12 CN CN202011262631.2A patent/CN112462344B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8044846B1 (en) * | 2007-11-29 | 2011-10-25 | Lockheed Martin Corporation | Method for deblurring radar range-doppler images |
| CN102279390A (en) * | 2011-05-06 | 2011-12-14 | 西南交通大学 | Intra-pulse modulation and recognition method of low signal-to-noise radar radiation source signal |
| CN106772308A (en) * | 2017-03-21 | 2017-05-31 | 中国人民解放军国防科学技术大学 | Terahertz wideband radar micro-doppler ambiguity solution method based on arteries and veins internal interference |
| CN109613489A (en) * | 2018-11-21 | 2019-04-12 | 昆明理工大学 | A kind of Radar Signal Sorting Method based on ambiguity function geomorphic feature |
Non-Patent Citations (1)
| Title |
|---|
| 基于AF的多相编码脉冲脉内调制参数估计;李宏;秦玉亮;李彦鹏;王宏强;黎湘;;系统工程与电子技术(第09期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112462344A (en) | 2021-03-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111142105B (en) | ISAR imaging method for complex moving target | |
| CN104901909B (en) | The method for parameter estimation of chirp signals under a kind of α non-Gaussian noises | |
| CN111680737B (en) | Radar radiation source individual identification method under differential signal-to-noise ratio condition | |
| CN108562884A (en) | A kind of Air-borne Forward-looking sea-surface target angle ultra-resolution method based on maximum a posteriori probability | |
| CN111948618B (en) | Forward scattering target detection method and system based on satellite external radiation source | |
| CN112462343B (en) | Method for extracting characteristic parameters in radar signal pulse through frequency domain transformation processing | |
| CN112859014A (en) | Radar interference suppression method, device and medium based on radar signal sorting | |
| Golbon-Haghighi et al. | Detection of ground clutter for dual-polarization weather radar using a novel 3D discriminant function | |
| CN112462344B (en) | Method for extracting characteristic parameters in radar signal pulse through time-frequency domain transformation processing | |
| Guan et al. | Strong echo cancellation based on adaptive block notch filter in passive radar | |
| CN112213697A (en) | Feature fusion method for radar deception jamming recognition based on Bayesian decision theory | |
| CN110568415B (en) | Signal detection method based on Arctan function under Gaussian mixture model | |
| Li et al. | LPI Radar signal modulation recognition with feature fusion based on time-frequency transforms | |
| CN113205564B (en) | SAR intelligent target edge reconstruction method | |
| CN111832632B (en) | Radar signal sorting method and system based on high-order spectrum symmetry Holder coefficient | |
| CN106569182B (en) | Phase-coded signal carrier frequency estimation method based on minimum entropy | |
| CN112578359B (en) | Method for extracting characteristic parameters in radar signal pulse through bispectrum conversion processing | |
| CN112578360B (en) | Method for extracting characteristic parameters in radar signal pulse based on transform domain | |
| CN115327483B (en) | Radar main lobe interference suppression method based on blind extraction | |
| CN110441749A (en) | Frequency stepping radar target motion parameter estimation method | |
| CN116359854A (en) | YOLOv 5-based anti-air warning radar composite interference parameter estimation method | |
| CN101639530B (en) | SAR echo signal de-noising preprocessing method based on two-dimensional mixed transformation | |
| CN108983189B (en) | Two-dimensional micro-motion track estimation method for vibration target | |
| Chen et al. | Feature extraction using wavelet transform for radar emitter signals | |
| CN110082748A (en) | A kind of passive radar object detection method and device |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |