CN106405518A - Complex system radar signal grade correlating, clustering and sorting method - Google Patents
Complex system radar signal grade correlating, clustering and sorting method Download PDFInfo
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- CN106405518A CN106405518A CN201611115052.9A CN201611115052A CN106405518A CN 106405518 A CN106405518 A CN 106405518A CN 201611115052 A CN201611115052 A CN 201611115052A CN 106405518 A CN106405518 A CN 106405518A
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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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- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
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Abstract
The invention relates to a complex system radar signal grade correlating, clustering and sorting method. The method comprises the following steps: through the study and analysis on the characteristics of the radiation source signal of the existing complex radar system, firstly, using a pulse width domain and frequency domain hierarchical clustering method to classify the different radar signals; secondly, using the PRI algorithm of the small box width adaptive pulse flow density to extract the repetition period parameters; pre-estimating the pulse flow density of the post-clustered signal; using the small box width of the adaptive pulse flow density to detect the signal; performing PRI transform and suppressing harmonic waves; and extracting the repetition period's characteristic parameters from the detection result. This method takes into account the detection capability for radar signal and the identification ability for repetition period, and improves the accuracy of clustering. It also has a good detection and characteristic parameter extraction performance for complex system radar signals such as multi-staggered radar signals and large-scale jitter radar signals.
Description
Technical field
The present invention is applied to signal sorting field, sorts particularly to a kind of complexity radar level of signal association cluster
Method.
Background technology
The feature of Modern Electronic Countermeasure signal environment is that signal density is big, and waveform is complicated and changeable, working frequency range width and have portion
Divide overlap, signal is intensive and overlapping increasingly severe in time domain, the signal reaching reconnaissance system for radar input is random
Stream of pulses.And radar emitter signal has much noise during propagation and reception, SNR changes very greatly, greatly increases
The difficulty of sorting process.These characteristics significantly destroy signal sorting and identify that utilized signal is regular, make radar
The intercept probability of reconnaissance system is subject to extreme influence.The temporal modulation feature of radar signal have the pulse repetition period irregular, shake,
Group becomes, slides change and burst of pulses, pulse code etc.；Pulse width also has group to become and the form such as width, burst pulse combination.With super large rule
Mould digital integrated electronic circuit also more carrys out complicated, its main table in the popularization and application of field of radar, the temporal modulation form of radar signal
Existing form has, and 1：The irregular signal of Gao Zhongying arteries and veins group：The irregular value of such signal is more, has 8 to 10 irregular values, irregular spacing value
Little, common irregular be worth for 2us, the signal of some particular design can reach 0.2us；2：Between middle repetition arteries and veins, irregular signal is irregular
Value is extremely many, and some pathfinders are irregular can to reach 16；3：Dither signal with pseudo-random fashion occur, jitter range up to
To 200us；4：, more than 100, the sliding scope that becomes is more than 500us for sliding varying signal pulse number.In the traditional thunder of pulsewidth domain, frequency domain cluster
Reach emitter Signals sorting model parameter, there is no operation principle, the parameter distribution rule completely with reference to Active Radar, such as common
The main integrated distribution of radar pulsewidth in 0.1us～10us, the features such as frequency high concentration restrains, this may lead to by mistake by several not
Same radiation source gathers for a class or a radiation source mistake is divided into several classes, have impact on follow-up time domain cluster input；Gather in time domain
Traditional in class PRI sorting using the little case of fixed width, to Gao Zhongying signal, irregular interval be less than during little case width it is impossible to
Differentiate subcycle；Irregular signal between centering repetition arteries and veins, can only measure to limited irregular value, be difficult to all of irregular be worth into
Row statistics；To shake, sliding varying signal due to its repetition period distribution very big, detection probability is very low.Rely only on the little case of adjustment
Width and detection threshold cannot adapt to current complicated radar signal.Therefore in the urgent need to using a kind of new sorting mould
Type structure, new sorting thinking and new theory are asked studying the sorting under modern complexity system intensive radar emitter signal environment
Topic.
Content of the invention
It is an object of the invention to provide a kind of grade association cluster method for separating of complexity radar signal.
The technical solution realizing the object of the invention is：The present invention analyses in depth and research Advanced Radar Emitter Signals source
The substantive characteristics of signal, on this basis, first passes through the distribution rule that statistical method analyzes radar tactics function and its parameter
Rule, different cluster frequency domains, pulsewidth domain, the time domain cluster impact to analysis result for the mode, establish radar signal analyzing and processing
General frame and basic procedure, and the related algorithm flow process under framework is expanded in detail with research and demonstration it is proposed that radar
The PRI algorithm that signal pulsewidth domain, the hierarchical clustering algorithm of frequency domain cascade little case width self adaptation pulse current density is answering of framework
Miscellaneous radar signal analysis method.By analyze the distribution characteristics in pulsewidth domain and frequency domain for the radar signal, employ pulsewidth domain,
Frequency domain hierarchy clustering method is classified to different radar signals；Carried by the complicated radar signal repetition period characteristic of analysis
Go out the time domain clustering method of the PRI algorithm of little case width self adaptation pulse current density, repeated using stream of pulses density prediction meter
Period profile scope, the method that adaptive little case width is adopted to the signal of different repetition periods, taken into account radar letter simultaneously
Number detectability and repetition period resolution capability, improve the degree of accuracy of cluster, eliminate the interference of radar signal frequency multiplication, join to more
Difference radar signal, the on a large scale complicated radar such as shake radar signal have good detection and characteristic parameter extraction effect.
Brief description
Fig. 1 radar signal pulsewidth is analyzed.
The PRI cluster flow process of Fig. 2 little case width self adaptation pulse current density.
Specific embodiment
The specific implementation step realizing the present invention is as follows：
(1) frequency domain based on radar signal characteristic, pulsewidth domain hierarchy Relational Clustering
Frequency domain, pulsewidth domain cluster main purpose are dilution pulse data stream, prepare for time domain cluster below.In frequency
Domain, pulsewidth domain cluster will be in line with following two principles：(1) data belonging to same radiation source is assigned to same class as far as possible
In.(2) data that will not belong to same Radar emitter makes a distinction as far as possible.Wherein, the importance of first principle is big
In Article 2；Article 2 principle is in the case of meeting first as far as possible, satisfaction as far as possible.If there is no Article 2
The constraint of principle, is satisfactory it is clear that all input datas are considered as a class if only following first principle, but this
Point-score does not have practical significance, therefore it is also contemplated that making the similarity degree between of a sort data as big as possible, and different
Data differences between class are as big as possible, and this is required by Article 2 principle.
Pulse Width Analysis are carried out by common radar parameter table, within most of radar is operated in 0.1～10us, therefore at this
Scope adopts larger division dynamics.The signal that same radar can preferably be will not belong to using such method is separately.
The frequecy characteristic of radar signal, be frequency domain clustering algorithm write criterion.Anti-interference and ambiguity solution in order to meet
Need, the RF parameter of advanced system multimode radar also gradually develops multiple variation patterns, main shape by original preset parameter
Formula includes fixed frequency, frequency diversity, frequency agility, arteries and veins group agile, frequency conversion etc. in arteries and veins.Generally say, the letter of radar Reconnaissance system
Number frequency-measurement accuracy is higher, and in radar system, the RF of common carrier frequency variation pattern is gathered near certain several discrete frequency,
Therefore RF parameter has preferable convergence aggregation.For the characteristic of frequency distribution, using the hierarchical clustering of 1MHz stepping.
(2) the PRI clustering method of little case width self adaptation pulse current density
The brief flow process of little case width self adaptation pulse current density PRI algorithm is：
1) stream of pulses density prediction meter T/N, total time is divided by pulse number；
2) set reaching time-difference upper limit Tmax, lower limit Tmin, little case width Delta t；
3) calculate pulse arrival time poor；
4) statistics falls into each time difference little case number；
5) calculate little case detection threshold aT/ Δ tn, a is detection coefficient：0≤α≤1, Δ tnIt is each little case central point；
6) harmonics restraint；
7) time domain cluster.
Can be seen that two key parameters of impact PRI histogram clustering algorithm from above-mentioned flow process：
1st, time difference upper limit Tmax, lower limit TminDirectly affect circulation execution number of times during histogram calculation, when choosing rational
Between difference bound will improve algorithm ageing.
2nd, little case width Delta t：Little case width is the time difference minimum resolution of PRI algorithm, and little case width is wider, the time divides
Resolution is lower, under same detection thresholding detection probability improve, cluster elapsed time less, false-alarm stronger to signal detection ability
Rate is higher, the time spent by harmonics restraint is fewer；Little case width is narrower, and temporal resolution is higher, same detection Threshold detection
Probability reduces, cluster elapsed time is longer, lower to the detectability of signal, false alarm rate is lower, spent by harmonics restraint when
Between fewer.Therefore little case width directly determines the amount of calculation of PRI algorithm, detectability, time sense.
The repetition of the difference tactics function radar such as fire control radar, airborne radar, short-range radar, medium range radar, long-range radar
Cycle parameter distribution is different, if adopting same little case width and time difference bound, necessarily can not meet letter simultaneously
Number detectability, calculate the conditions such as time-consuming, time sense.Therefore this patent proposes by little case width self adaptation pulse
Current density method, carries out the pre-estimation of stream of pulses to the radar signal classified, and is adopted adaptive little according to the result estimated
Case width and time difference bound, have taken into account repetition period detectability, time sense simultaneously, improve PRI algorithm to complexity
The adaptive faculty of signal is it is achieved that to how irregular signal, on a large scale dither signal.
Its flow process of PRI clustering method of little case width self adaptation pulse current density is as shown in Figure 2.
Claims (1)
1. a kind of complexity radar level of signal association cluster method for separating it is characterised in that：First, analysis radar signal exists
Different radar signals are classified by pulsewidth domain and the distribution characteristics of frequency domain using pulsewidth domain, frequency domain hierarchy clustering method；Its
Secondary, the PRI algorithm using little case width self adaptation pulse current density extracts repetition period parameter：The arteries and veins of signal after pre-estimation cluster
Swash of wave density, the little case width using self adaptation pulse current density detects to signal, does PRI conversion, harmonics restraint, to inspection
Survey result cluster and extract its repetition period characteristic parameter.
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| CN107561499A (en) * | 2017-07-27 | 2018-01-09 | 中国船舶重工集团公司第七二四研究所 | A kind of how irregular signal sorting method of complexity based on EDW fusions |
| CN107576942A (en) * | 2017-07-27 | 2018-01-12 | 中国船舶重工集团公司第七二四研究所 | A kind of radiation source scan period real-time estimation method based on signal cluster |
| CN108197146A (en) * | 2017-11-29 | 2018-06-22 | 山东航天电子技术研究所 | The essence classification in-orbit generation system of Radar recognition parameter based on pulse flow data |
| CN108345864A (en) * | 2018-03-06 | 2018-07-31 | 中国电子科技集团公司第二十八研究所 | Random set mould assembly radar emitter signal parameter high frequency mode method for digging based on weighted cluster |
| CN109143180A (en) * | 2018-09-17 | 2019-01-04 | 江西洪都航空工业集团有限责任公司 | A kind of Passive Radar Seeker pulse choice method under complex electromagnetic environment |
| CN109270497A (en) * | 2018-10-28 | 2019-01-25 | 西南电子技术研究所（中国电子科技集团公司第十研究所） | The multi-Dimensional parameters Pre-sorting method of radar pulse signal |
| CN110806563A (en) * | 2019-11-19 | 2020-02-18 | 西南交通大学 | Radiation source signal clustering and sorting method based on radar pulse aliasing degree judgment |
| CN111257839A (en) * | 2020-03-30 | 2020-06-09 | 吉林大学 | Radar signal sorting method |
| CN111708020A (en) * | 2020-07-14 | 2020-09-25 | 南京理工大学 | Radar signal sorting and tracking method and system based on anti-radiation seeker |
| CN111722188A (en) * | 2020-05-18 | 2020-09-29 | 中国人民解放军63892部队 | PRI (pulse repetition index) conversion radar signal sorting method based on STFT (space time Fourier transform) pre-sorting |
| CN111796261A (en) * | 2020-06-12 | 2020-10-20 | 中国船舶重工集团公司第七二四研究所 | Radar signal self-adaptive detection method based on frequency domain multi-channel statistics |
| CN111796239A (en) * | 2020-06-12 | 2020-10-20 | 中国船舶重工集团公司第七二四研究所 | Harmonic suppression method for small-range repetition frequency jitter signal |
| CN112633427A (en) * | 2021-03-15 | 2021-04-09 | 四川大学 | Ultrahigh-order harmonic emission signal detection method based on outlier detection |
| CN113156391A (en) * | 2021-04-25 | 2021-07-23 | 电子科技大学 | Radar signal multi-dimensional feature intelligent sorting method |
| CN113721219A (en) * | 2021-10-08 | 2021-11-30 | 中国电子科技集团公司第三十八研究所 | Radar signal sorting method and system based on multi-parameter clustering |
| CN116738259A (en) * | 2023-08-14 | 2023-09-12 | 西南交通大学 | Multi-harmonic-based electromagnetic leakage radiation source fingerprint extraction and identification method and device |
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| CN107576942A (en) * | 2017-07-27 | 2018-01-12 | 中国船舶重工集团公司第七二四研究所 | A kind of radiation source scan period real-time estimation method based on signal cluster |
| CN107576942B (en) * | 2017-07-27 | 2020-05-01 | 中国船舶重工集团公司第七二四研究所 | Radiation source scanning period real-time estimation method based on signal clustering |
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| CN109143180A (en) * | 2018-09-17 | 2019-01-04 | 江西洪都航空工业集团有限责任公司 | A kind of Passive Radar Seeker pulse choice method under complex electromagnetic environment |
| CN109270497A (en) * | 2018-10-28 | 2019-01-25 | 西南电子技术研究所（中国电子科技集团公司第十研究所） | The multi-Dimensional parameters Pre-sorting method of radar pulse signal |
| CN110806563A (en) * | 2019-11-19 | 2020-02-18 | 西南交通大学 | Radiation source signal clustering and sorting method based on radar pulse aliasing degree judgment |
| CN111257839A (en) * | 2020-03-30 | 2020-06-09 | 吉林大学 | Radar signal sorting method |
| CN111722188B (en) * | 2020-05-18 | 2024-03-15 | 中国人民解放军63892部队 | PRI conversion radar signal sorting method based on STFT pre-sorting |
| CN111722188A (en) * | 2020-05-18 | 2020-09-29 | 中国人民解放军63892部队 | PRI (pulse repetition index) conversion radar signal sorting method based on STFT (space time Fourier transform) pre-sorting |
| CN111796261A (en) * | 2020-06-12 | 2020-10-20 | 中国船舶重工集团公司第七二四研究所 | Radar signal self-adaptive detection method based on frequency domain multi-channel statistics |
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| CN113156391A (en) * | 2021-04-25 | 2021-07-23 | 电子科技大学 | Radar signal multi-dimensional feature intelligent sorting method |
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| CN113721219A (en) * | 2021-10-08 | 2021-11-30 | 中国电子科技集团公司第三十八研究所 | Radar signal sorting method and system based on multi-parameter clustering |
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