CN105259538A - Signal quality evaluation method and device based on signal characteristic convergence - Google Patents

Signal quality evaluation method and device based on signal characteristic convergence Download PDF

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CN105259538A
CN105259538A CN201510712858.5A CN201510712858A CN105259538A CN 105259538 A CN105259538 A CN 105259538A CN 201510712858 A CN201510712858 A CN 201510712858A CN 105259538 A CN105259538 A CN 105259538A
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pulse
pulse signal
signal
value
feature
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CN105259538B (en
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孙盼杰
卫颖卓
谢爱平
张媛
吴耀云
刘正彬
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CETC 2 Research Institute
Southwest China Research Institute Electronic Equipment
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/36—Means for anti-jamming, e.g. ECCM, i.e. electronic counter-counter measures

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  • 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 present invention discloses a signal quality evaluation method and a device based on signal characteristic convergence, relating to the field of object identification of electronic reconnaissance. The method and the device are characterized in that the radar pulse signals of air are received, the detection parameter of each radar pulse signal is measured, the detection parameter of each pulse signal is obtained, according to the detection parameter of the pulse signal, the received pulse signals are clustered, the pulse signals emitted by the same radar signal emission source in the same working mode is categorized in one group, each pulse signal in each of the pulse signal group is subjected to characteristic value extraction, N characteristic value vectors Vi are obtained, the Euclidean distance value di of the characteristic value vectors of any two pulse signals in each pulse group is calculated, and a value CD which reflects the average value of each distance value is calculated if the CD reflects the pulse signal characteristic convergence in the pulse group.

Description

A kind of signal quality evaluating method based on signal characteristic convergence and device
Technical field
The present invention relates to the field of target recognition of electronic reconnaissance specialty.
Background technology
Usually need to scout to the radar pulse signal in environment objective emission in target identification technology field, carry out there is various undesired signal in the actual environment of radar signal reconnaissance, make to scout environment condition that is very complicated so that signal transacting at different levels and often do not reach perfect condition.Such as scout in environment and there is the situations such as reflection, multipath, low signal-to-noise ratio, receiver burr signal, spurious signal, these all can have adverse influence to signal characteristic parameter extraction, finally may cause the information of system generation error.
Existing application system just simply judges signal amplitude, does not have signal because the factor such as reception environment and delivering path brings quality influence effectively to assess.
Summary of the invention
Technical matters to be solved by this invention is: for above-mentioned Problems existing, provides a kind of signal quality evaluating method based on signal characteristic convergence and device.
Signal quality evaluating method based on signal characteristic convergence provided by the invention, comprising:
Step 1: receive aerial radar pulse signal, measures the detected parameters of each radar pulse signal, obtains the detected parameters of each pulse signal;
Step 2: the detected parameters according to pulse signal carries out cluster to the pulse signal received, is classified as one group by the pulse signal that same radar signal source sends under same mode of operation;
Step 3: carry out characteristics extraction to each pulse signal in each pulse signal group, obtains N number of feature value vector V i, V irepresent the feature value vector of i-th pulse; Wherein, i get 1,2,3 ..., N; N is the sum of the pulse signal in pulse signal group;
Step 4: the Euclidean distance value d calculating the feature value vector of any two pulse signals in each pulse group i; Wherein i get 1,2,3 ...,
Calculate reaction the value C of individual distance value average size d; If described value C dreact pulse signal feature convergence in this pulse group.
Step 4 comprises further:
Step 41: to V ibe normalized and make its each element be numerical value between 0 ~ 1; Wherein, i get 1,2,3 ..., N;
Step 42: the Euclidean distance value calculating the feature value vector of any two pulse signals in each pulse group obtains Distance matrix D, D = d 11 d 12 d 13 ... d 1 N d 21 d 22 d 23 ... d 2 N d 31 d 32 d 33 ... d 3 N · · · · · · · · · · · · · · · d N 1 d N 2 d N 3 ... d N N ; Wherein, d i j = Σ k = 1 M ( v i k - v j k ) 2 ; D ijbe the Euclidean distance value of i-th feature value vector to a jth feature value vector, v ikbe a kth element of i-th feature value vector, v jkfor a kth element of a jth feature value vector; M is the sum of element in feature value vector;
Step 43: computing formula wherein i get 1,2,3 ..., N, j get 1,2,3 ..., N, and i ≠ j.
Further, described detected parameters comprises at least one in following parameter: pulse signal time of arrival, pulse signal frequency, pulse signal pulsewidth, pulse amplitude, pulse signal orientation.
Further, described eigenwert comprises at least one in following characteristics value: the characteristic parameters of spectra of pulse signal, waveform character value, intrapulse modulation characteristic value.
Present invention also offers a kind of Signal quality assessment device based on signal characteristic convergence, comprising:
Detected parameters measuring unit, for receiving aerial radar pulse signal, measuring the detected parameters of each radar pulse signal, obtaining the detected parameters of each pulse signal;
Cluster cell, carries out cluster for the detected parameters according to pulse signal to the pulse signal received, and the pulse information that same radar signal source sends under same mode of operation is classified as one group;
Characteristics extraction unit, for carrying out characteristics extraction to each pulse signal in each pulse signal group, obtains N number of feature value vector V i, V irepresent the feature value vector of i-th pulse; Wherein, i get 1,2,3 ..., N; N is the sum of the pulse signal in pulse signal group;
Pulse signal feature convergence acquiring unit, for calculating the Euclidean distance value d of the feature value vector of any two pulse signals in each pulse group i; Wherein i get 1,2,3 ...,
And for calculating reaction the value C of individual distance value average size d; If described value C dreact pulse signal feature convergence in this pulse group.
Pulse signal feature convergence acquiring unit comprises further:
Normalization unit, for V ibe normalized and make its each element be numerical value between 0 ~ 1; Wherein, i get 1,2,3 ..., N;
Distance matrix acquiring unit, the Euclidean distance value for the feature value vector calculating any two pulse signals in each pulse group obtains Distance matrix D, D = d 11 d 12 d 13 ... d 1 N d 21 d 22 d 23 ... d 2 N d 31 d 32 d 33 ... d 3 N · · · · · · · · · · · · · · · d N 1 d N 2 d N 3 ... d N N ; Wherein, d ijbe the Euclidean distance value of i-th feature value vector to a jth feature value vector, v ikbe a kth element of i-th feature value vector, v jkfor a kth element of a jth feature value vector; M is the sum of element in feature value vector;
Pulse signal feature convergency value acquiring unit, for computing formula obtain pulse signal feature convergency value C d, wherein i get 1,2,3 ..., N, j get 1,2,3 ..., N, and i ≠ j.
In sum, owing to have employed technique scheme, the invention has the beneficial effects as follows:
Find in Practical Project experiment, signal characteristic abstraction error is mainly from three reasons: one is because the factor such as multipath, burr causes feature to distort in pulse collection; Two be target pulse signal to noise ratio (S/N ratio) more weak time, feature restrains not; Three be signal sorting exist leak batch time, other signals mixed cause interference to echo signal feature extraction.These three kinds of situations all can cause the convergence of eigenmatrix on the low side, then affect follow-up identifying processing.
The invention provides the signal quality evaluating method of a kind of feature based convergence, can from each category feature extracted, select a part of feature of better astringency as final feature extraction result, reduce above-mentioned three kinds of non-idealities to the impact of signal quality as far as possible, improve the accuracy of follow-up signal identification.
Accompanying drawing explanation
Examples of the present invention will be described by way of reference to the accompanying drawings, wherein:
Fig. 1 is the inventive method process flow diagram.
Embodiment
All features disclosed in this instructions, or the step in disclosed all methods or process, except mutually exclusive feature and/or step, all can combine by any way.
Arbitrary feature disclosed in this instructions, unless specifically stated otherwise, all can be replaced by other equivalences or the alternative features with similar object.That is, unless specifically stated otherwise, each feature is an example in a series of equivalence or similar characteristics.
For in electronic reconnaissance process, signal quality quality has tremendous influence to feature extraction and identification.The present invention proposes the signal estimation method of a kind of feature based convergence, utilize the signal characteristic degree of convergence to judge signal quality.The higher signal quality of the signal characteristic degree of convergence is better, and the signal characteristic degree of convergence more low signal quality is poorer.Concrete steps, as Fig. 1, comprising:
Step 1: receive aerial radar pulse signal, measures the detected parameters of each radar pulse signal, obtains the detected parameters of each pulse signal.The detection method that this area is commonly used has tim e-domain detection and frequency domain detection, and detected parameters includes but not limited to the time of arrival, frequency, pulsewidth, amplitude, orientation etc. of pulse signal.
Step 2: the detected parameters according to pulse signal carries out cluster to the pulse signal received, the object of cluster is that the pulse signal by same radar signal source sends under same mode of operation is classified as one group.The clustering method that this area is commonly used has: based on CDIF and the SDIF clustering method of PRI or based on parameter Euclidean distance clustering method etc.
Step 3: carry out characteristics extraction to each pulse signal in each pulse signal group, obtains N number of feature value vector V i, V irepresent the feature value vector of i-th pulse; Wherein, i get 1,2,3 ..., N; N is the sum of the pulse signal in pulse signal group.Eigenwert includes but not limited to spectrum signature, the waveform character and intrapulse modulation characteristic etc. of pulse signal.
Step 4: feature convergence judges, by calculating signal characteristic convergence, judges whether signal characteristic is stablized.
Feature convergence computing method comprise:
Calculate the Euclidean distance value d of the feature value vector of any two pulse signals in each pulse group i; Wherein i get 1,2,3 ..., euclidean distance can measuring vector V iwith vectorial V jbetween consistance.
Calculate reaction the value C of individual distance value average size d; Described value C dreact pulse signal feature convergence in this pulse group, if value C dless, then think the better astringency of this eigenwert, react pulse signal with this eigenwert comparatively accurate.
Be worth C in one embodiment dfor the arithmetic mean of individual distance value.In a preferred embodiment, value C dobtained by following steps:
Step 41: to V ibe normalized and make its each element be numerical value between 0 ~ 1; Wherein, i get 1,2,3 ..., N; The mode of normalized has multiple, and wherein one is compute vector V iin the summation of each element, then remove vectorial V by summation iin each element obtain the value after the normalization of this element.
Step 42: the Euclidean distance value calculating the feature value vector of any two pulse signals in each pulse group obtains Distance matrix D, D = d 11 d 12 d 13 ... d 1 N d 21 d 22 d 23 ... d 2 N d 31 d 32 d 33 ... d 3 N · · · · · · · · · · · · · · · d N 1 d N 2 d N 3 ... d N N ; Wherein, i-th feature value vector to the Euclidean distance value of a jth feature value vector, v ikbe a kth element of i-th feature value vector, v jkfor a kth element of a jth feature value vector; M is the sum of element in feature value vector.
Step 43: computing formula wherein i get 1,2,3 ..., N, j get 1,2,3 ..., N, and i ≠ j.
Due to vectorial V ihave passed through normalized, therefore d ijthe numerical value between 0 ~ 1, d ijless, represent from i-th pulse with from a jth DISCHARGE PULSES EXTRACTION to feature more consistent, otherwise loose all the more.By d ijavailable N × N Distance matrix D.Be not difficult to learn, the element on the diagonal line in Distance matrix D is 0, and element d ijequal element d ji, i ≠ j.
Generally, a feature extraction accurately mark mutually restrains the feature of each DISCHARGE PULSES EXTRACTION of same target, i.e. d ijlittle as far as possible.Theoretically, the feature of the signal of same radar signal source radiation under same mode of operation is constant, and why changing is because the impact of environment, radiation, receiving cable various factors, it is generally acknowledged that these impacts are normally random.Experiment proves, the factor of various impact is less, and feature is convergence more.For this reason, in the present embodiment, defined feature convergence is:
C D = 1 - Σd i j N × ( N - 1 ) ;
Wherein i get 1,2,3 ..., N, j get 1,2,3 ..., N, and i ≠ j.Interpulse proper vector is convergence more, C dvalue more close to 1, otherwise more close to 0, therefore C dcan be used as the evaluation index of feature extraction quality.Technician just can according to signal characteristic convergency value C dchoose optimum feature and carry out characterization signal, improve the accuracy of follow-up signal identification.
The present invention is not limited to aforesaid embodiment.The present invention expands to any new feature of disclosing in this manual or any combination newly, and the step of the arbitrary new method disclosed or process or any combination newly.

Claims (8)

1., based on a signal quality evaluating method for signal characteristic convergence, it is characterized in that, comprising:
Step 1: receive aerial radar pulse signal, measures the detected parameters of each radar pulse signal, obtains the detected parameters of each pulse signal;
Step 2: the detected parameters according to pulse signal carries out cluster to the pulse signal received, is classified as one group by the pulse information that same radar signal source sends under same mode of operation;
Step 3: carry out characteristics extraction to each pulse signal in each pulse signal group, obtains N number of feature value vector V i, V irepresent the feature value vector of i-th pulse; Wherein, i get 1,2,3 ..., N; N is the sum of the pulse signal in pulse signal group;
Step 4: the Euclidean distance value d calculating the feature value vector of any two pulse signals in each pulse group i; Wherein i get 1,2,3 ..., ;
Calculating reactions steps 4 obtains the value C of individual distance value average size d; If described value C dreact pulse signal feature convergence in this pulse group.
2. a kind of signal quality evaluating method based on signal characteristic convergence according to claim 1, it is characterized in that, step 4 comprises further:
Step 41: to V ibe normalized and make its each element be numerical value between 0 ~ 1; Wherein, i get 1,2,3 ..., N;
Step 42: the Euclidean distance value calculating the feature value vector of any two pulse signals in each pulse group obtains Distance matrix D, D = d 11 d 12 d 13 ... d 1 N d 21 d 22 d 23 ... d 2 N d 31 d 32 d 33 ... d 3 N . . . . . . . . . . . . . . . d N 1 d N 2 d N 3 ... d N N ; Wherein, d i j = Σ k = 1 M ( v i k - v j k ) 2 , D ijbe the Euclidean distance value of i-th feature value vector to a jth feature value vector, v ikbe a kth element of i-th feature value vector, v jkfor a kth element of a jth feature value vector; M is the sum of element in feature value vector;
Step 43: computing formula wherein i get 1,2,3 ..., N, j get 1,2,3 ..., N, and i ≠ j.
3. a kind of signal quality evaluating method based on signal characteristic convergence according to claim 1, it is characterized in that, described detected parameters comprises at least one in following parameter: pulse signal time of arrival, pulse signal frequency, pulse signal pulsewidth, pulse amplitude, pulse signal orientation.
4. a kind of signal quality evaluating method based on signal characteristic convergence according to claim 1 and 2, it is characterized in that, described eigenwert comprises at least one in following characteristics value: the characteristic parameters of spectra of pulse signal, waveform character value, intrapulse modulation characteristic value.
5., based on a Signal quality assessment device for signal characteristic convergence, it is characterized in that, comprising:
Detected parameters measuring unit, for receiving aerial radar pulse signal, measuring the detected parameters of each radar pulse signal, obtaining the detected parameters of each pulse signal;
Cluster cell, carries out cluster for the detected parameters according to pulse signal to the pulse signal received, and the pulse information that same radar signal source sends under same mode of operation is classified as one group;
Characteristics extraction unit, for carrying out characteristics extraction to each pulse signal in each pulse signal group, obtains N number of feature value vector V i, V irepresent the feature value vector of i-th pulse; Wherein, i get 1,2,3 ..., N; N is the sum of the pulse signal in pulse signal group;
Pulse signal feature convergence acquiring unit, for calculating the Euclidean distance value d of the feature value vector of any two pulse signals in each pulse group i; Wherein i get 1,2,3 ..., ;
And for calculating reaction the value C of individual distance value average size d; If described value C dreact pulse signal feature convergence in this pulse group.
6. a kind of Signal quality assessment device based on signal characteristic convergence according to claim 5, it is characterized in that, pulse signal feature convergence acquiring unit comprises further:
Normalization unit, for V ibe normalized and make its each element be numerical value between 0 ~ 1; Wherein, i get 1,2,3 ..., N;
Distance matrix acquiring unit, the Euclidean distance value for the feature value vector calculating any two pulse signals in each pulse group obtains Distance matrix D, D = d 11 d 12 d 13 ... d 1 N d 21 d 22 d 23 ... d 2 N d 31 d 32 d 33 ... d 3 N . . . . . . . . . . . . . . . d N 1 d N 2 d N 3 ... d N N ; Wherein, for the sum of element in feature value vector;
Pulse signal feature convergency value acquiring unit, for computing formula obtain pulse signal feature convergency value C d, wherein i get 1,2,3 ..., N, j get 1,2,3 ..., N, and i ≠ j.
7. a kind of Signal quality assessment device based on signal characteristic convergence according to claim 5, it is characterized in that, described detected parameters comprises at least one in following parameter: pulse signal time of arrival, pulse signal frequency, pulse signal pulsewidth, pulse amplitude, pulse signal orientation.
8. a kind of Signal quality assessment device based on signal characteristic convergence according to claim 5 or 6, it is characterized in that, described eigenwert comprises at least one in following characteristics value: the characteristic parameters of spectra of pulse signal, waveform character value, intrapulse modulation characteristic value.
CN201510712858.5A 2015-10-28 2015-10-28 One kind is based on the convergent signal quality evaluating method of signal characteristic and device Active CN105259538B (en)

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