CN101860866B - Intrusion detection and positioning method of n anti-intrusion system sensing network - Google Patents

Intrusion detection and positioning method of n anti-intrusion system sensing network Download PDF

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CN101860866B
CN101860866B CN201010181996.2A CN201010181996A CN101860866B CN 101860866 B CN101860866 B CN 101860866B CN 201010181996 A CN201010181996 A CN 201010181996A CN 101860866 B CN101860866 B CN 101860866B
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invasion
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intrusion
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吴慧娟
饶云江
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University of Electronic Science and Technology of China
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Abstract

The invention discloses an intrusion detection and positioning method of an anti-intrusion system sensing network. The intrusion detection and positioning method is characterized in that the existence of an intrusion signal is judged by using the related characteristic of a signal that the self-correlation time of a signal with intrusion is longer than that of a signal without intrusion, calculating a self-correlation function of the signal and comparing the signal correlation coefficient value at the non-zero delay tap. The method is suitable for detecting the non-uniform sensitivity sensing nodes without performing consistent software or hardware calibration, has extremely high detection and positioning accuracy and low error alarm rate, and is applicable to the anti-intrusion application of a large or long-distance circumferential rail made of many kinds of mixed materials. Moreover, by adopting the method, the multi-point weak intrusion can be accurately detected.

Description

The intrusion detection of anti-intrusion system sensing network and localization method
Technical field
The present invention relates to security and guard technology and sensing network signal processing method field, be specifically related to non-uniform sensitivity nodes of anti-intrusion system sensing network intrusion detection and localization method.
Background technology
In anti-intrusion system sensing network, no matter quasi-distributed array sensing node adopts traditional electric sensor, or adopt have anti-strong electromagnetic, passive Fibre Optical Sensor, because the difference of the difference of each sensor node of network self hardware condition and mounting condition, installation environment, fence material, cause each node transducer sensitivity inconsistent, or identical invasion signal is different in the output response of each Nodes, impact is accurate detection and the location of invasion signal truly, therefore need to carry out to each sensing node the consistency calibration of hardware and software.Disclosed China applied for a patent on October 22nd, 2008: 200810059962.9 be exactly for address this problem proposition for a kind of consistency calibration method that shakes electric sensor.Yet along with the increase of anti-intrusion detection circumference or the expansion of sensing network scale, the sensor node number can increase greatly, consistency calibration method not only bother and cost higher, and the rear growth along with monitoring time of demarcation, each node transducer self-condition changes, or the difference of the installation environment consistency variation gradually still that causes each node in the sensing network, system need to re-start consistency calibration at set intervals, otherwise can affect equally the accuracy that anti-intrusion system detects.Especially for optical pickocff, transducer sensitivity is high, carry out relatively difficulty of consistency calibration, cost is higher, and the inhomogeneous sensing node noise energy difference of sensitivity is larger, and change in time, if the noise energy of certain Nodes and faint invasion signal energy quite or greater than the invasion signal energy, can cause undetected or the flase drop situation.Invade situation because inhomogeneous more being difficult to of sensitivity judged and identify for multiple spot.
Summary of the invention
Problem to be solved by this invention is: intrusion detection and localization method that how a kind of non-uniform sensitivity nodes of anti-intrusion system sensing network is provided, the method can overcome existing defective in the prior art, need not to carry out consistency software or hardware demarcates, the accuracy rate that detects is high, and the alert rate of mistake is low.
Technical problem proposed by the invention is to solve like this: intrusion detection and localization method that a kind of non-uniform sensitivity nodes of anti-intrusion system sensing network is provided, it is characterized in that, utilize the correlation properties of signal self, the signal autocorrelation time span of invasion is namely arranged greater than the signal autocorrelation time span without invasion, by calculating the auto-correlation function of signal, relatively the signal correction coefficient value at non-zero time delay tap place is distinguished having or not of invasion signal.Signal without invasion mainly is made of various noises such as system, environment, no matter its amplitude intensity and energy have much, a little less than the signal correlation, the downward trend of signal auto-correlation function curve is very fast, except time delay is that the signal autocorrelation coefficient value at 0 place is 1, the auto-correlation coefficient value at other time delay tap places all is close to 0; And the signal of invasion is arranged, the power of signal no matter, the correlation of signal self is stronger, and the downward trend of signal auto-correlation function curve is slow, in the auto-correlation coefficient value at non-zero time delay tap place much larger than 0, and near 0 time delay tap place auto-correlation coefficient close to 1.
If the transducing signal array that receives is X=x i(n), i=1,2 ..., N; N=1,2 ..., M}, N are the nodes of sensing network, and M is the analysis length of each node signal, and the normalized autocorrelation functions of each node signal is C i={ E i(x (n), x (n-l)), l=0,1 ..., M}, l are time delay, unit is sampled point, | C i|≤1; If the I node is the node without invasion, signal time auto-correlation length is l during without invasion 1, the J node is the node that invasion is arranged, signal time auto-correlation length was l when invasion was arranged 2, the two, length relation always had 0≤l correlation time 1<l 2
Select a definite time delay l 1<L<l 2, normalizated correlation coefficient E must be arranged 1(x (n), x (n-L))<E J(x (n), x (n-L)), and have Or E J(x (n), x (n-L))>>0.Set a normalized autocorrelation coefficient threshold value η c, 0.5<η c<1, can judge whether the invasion signal exists according to following formula:
R i = 1 , | E i ( x ( n ) , x ( n - L ) ) | &GreaterEqual; &eta; c 0 , | E i ( x ( n ) , x ( n - L ) ) | < &eta; c - - - ( 1 )
When
Figure GSA00000132368300024
The time, judge not invasion of circumference; When
Figure GSA00000132368300025
The time, judge that circumference has invasion, signal that invasion is arranged is judged it is to be caused or environmental change causes by artificial invasion according to its frequecy characteristic or the sensing node number that affects and scope again; To defining artificial invasion after the environmental factor eliminating, corresponding R i≠ 0 node subscript i is the sensing node that invasion action affects, the location of invading according to the installation site of this node.
If Be the single-point invasion; If
Figure GSA00000132368300032
To R iContinuous several node i of=1 are carried out cluster, several nodes that can cluster judge it is that invasion action by a point causes, the number of the class of finally determining after the cluster is actual invasion and counts, and the node ordinal number in each class is averaging again round, and carries out the location of multiple spot invasion.
Useful technique effect of the present invention is, avoid the trouble of multinode consistency calibration in the sensing network, greatly save installation, maintenance and the whole system operating cost of anti-intrusion system, and the method is from distinguishing true invasion and nothing invasion signal in essence, system's intrusion detection highly sensitive is fit to the faint invasion input of hard fence.After defining the existence of invasion signal, artificially invade again the difference with the environmental change such as wind impact, the method detect and the accuracy rate of location invasion high, the alert rate of mistake is low, the accurate differentiation of suitable multiple spot invasion, and be applicable to the anti-invasion application of circumference fence that various material is mixed.
Description of drawings
Fig. 1 is the signal auto-correlation function comparison diagram of one embodiment of the invention.
Fig. 2 is an embodiment of invasion detecting device of the present invention, based on the fiber fence anti-intrusion system of quasi-distributed FBG transducer.
Embodiment
The invention will be further described below in conjunction with accompanying drawing:
The invention provides a kind of intrusion detection and localization method of non-uniform sensitivity nodes of anti-intrusion system sensing network.The present invention utilizes self correlation properties of invasion signal to identify the existence of having or not of invasion or faint invasion, so that each node of anti-intrusion system sensing network need not to carry out consistency software or hardware is demarcated.Described signal self correlation properties are: length correlation time of signal self.Signal without invasion mainly is made of various noises such as system, environment, no matter its amplitude intensity and energy have much, a little less than the signal correlation, the autocorrelative time is shorter, shown in Fig. 1 solid line, except time delay is that the auto-correlation coefficient at 0 place is 1, the auto-correlation coefficient at other time delay tap places all is close to 0, and signal auto-correlation function suddenly descends; And the signal of invasion is arranged, the power of signal no matter, the correlation of signal self is stronger, the signal auto-correlation function curve is slow decreasing trend, shown in Fig. 1 dotted line, the signal autocorrelation coefficient value much larger than 0, and is that 1 or 2 sample place auto-correlation coefficient values are still close to 1 in time delay tap at non-zero time delay tap place.According to this difference, can be by calculating the auto-correlation function of signal, the signal autocorrelation coefficient value at non-zero time delay tap place relatively is from distinguishing in essence signal that invasion is arranged or without the signal of invasion.The method is simple and practical, has stronger noise inhibiting ability, and is therefore less demanding to the preliminary treatment such as front end denoising of anti-intrusion system.
The below take based on the fiber fence anti-intrusion system of quasi-distributed FBG transducer as example, by reference to the accompanying drawings specific implementation method of the present invention is further described:
Paper is the invasion detecting device that adopts of the specific embodiment of the invention one once, as shown in Figure 2, formed by three parts: be hung on the fence or be embedded in circumferentially under armored optical cable (be in series with N FBG Fibre Optical Sensor, can detect N point), be used for vibration or the strain signal of invading on the perception circumference; The signal (FBG) demodulator is used for providing light source, and light signal is carried out demodulation, opto-electronic conversion and A/D analog-to-digital conversion; Warning system or processing host are used for the sensing network node signal that transmits is processed in real time, judge that invasion has or not and carries out sound and light alarm, provide and show intrusion detection and positioning result thereof.What next introduce is exactly specific implementation method of the present invention:
The light transducing signal that carries invasion information by optical cable transmission to (FBG) demodulator, through demodulation, opto-electronic conversion and A/D analog-to-digital conversion, be transferred to processing host by Ethernet or serial port form, main frame is processed the signal of all nodes of sensing network of receiving in real time, judges having or not and positioning according to the signal energy size of invasion.
Processing to signal is key point of the present invention.Because each node sensitivity of sensing network is inhomogeneous, directly carry out energy comparison and judge having or not of invasion signal, cause easily false dismissal and mistake alert, and the threshold size of setting is relevant with conditions such as fence material, weather, environment, be not easy to determine, therefore need a kind of new intrusion detection method.As embodiment two, the detection method of invasion is:
If the transducing signal array that receives is X={x i(n), i=1,2 ..., N; N=1,2 ..., M}, N are the nodes of sensing network, and M is the analysis length of each node signal, and the normalized autocorrelation functions of each node signal is C i={ E i(x (n), x (n-l)), l=0,1 ..., M}, l are time delay, unit is sampled point, | C i|≤1; If the I node is the node without invasion, signal time auto-correlation length is l during without invasion 1, the J node is the node that invasion is arranged, signal time auto-correlation length was l when invasion was arranged 2, the two, length relation always had 0≤l correlation time 1<l 2
Select a definite time delay l 1<L<l 2, normalizated correlation coefficient E must be arranged I(x (n), x (n-L))<E J(x (n), x (n-L)), and have
Figure GSA00000132368300051
Figure GSA00000132368300052
Or E J(x (n), x (n-L))>>0.Set a normalized autocorrelation coefficient threshold value η c, 0.5<η c<1, can judge whether the invasion signal exists according to following formula:
R i = 1 , | E i ( x ( n ) , x ( n - L ) ) | &GreaterEqual; &eta; c 0 , | E i ( x ( n ) , x ( n - L ) ) | < &eta; c - - - ( 1 )
When
Figure GSA00000132368300054
The time, judge not invasion of circumference; When
Figure GSA00000132368300055
The time, judge that circumference has invasion, signal that invasion is arranged is judged it is to be caused or environmental change causes by artificial invasion according to its frequecy characteristic or the sensing node number that affects and scope again; To defining artificial invasion after the environmental factor eliminating, corresponding R i≠ 0 node subscript i is the sensing node that invasion action affects, the location of invading according to the installation site of this node.
If Be the single-point invasion; If
Figure GSA00000132368300057
To R iContinuous several node i of=1 are carried out cluster, several nodes that can cluster judge it is that invasion action by a point causes, the number of the class of finally determining after the cluster is actual invasion and counts, and the node ordinal number in each class is averaging again round, and carries out the location of multiple spot invasion.
The specific implementation method of the anti-intrusion system that is based on quasi-distributed FBG Fibre Optical Sensor of enumerating in the embodiment of the invention, the signal processing method of this invention can be applied to based on other optics, electric class fully or mix in the anti-intrusion system of quasi-distributed sensor network.

Claims (3)

1. the intrusion detection of a non-uniform sensitivity nodes of anti-intrusion system sensing network and localization method, it is characterized in that, utilize the correlation properties of signal self, the signal autocorrelation time span of invasion is namely arranged greater than the signal autocorrelation time span without invasion, by calculating the auto-correlation function of signal, the signal correction coefficient value that compares non-zero time delay tap place, distinguish having or not of invasion signal:
Signal without invasion: mainly consisted of by system and ambient noise, no matter its amplitude intensity and energy have much, a little less than signal self correlation, the auto-correlation time span of signal is short, the downward trend of signal auto-correlation function curve is very fast, except time delay is that the signal autocorrelation coefficient value at 0 place is 1, the auto-correlation coefficient value at other time delay tap places all is close to 0;
The signal that invasion is arranged: the power of no matter invading signal, the correlation of this signal is strong, the auto-correlation time of signal is long, the downward trend of signal auto-correlation function curve is slow, in the auto-correlation coefficient value at non-zero time delay tap place much larger than 0, and near the auto-correlation coefficient at 0 time delay tap place still close to 1.
2. the intrusion detection of non-uniform sensitivity nodes of anti-intrusion system sensing network according to claim 1 and localization method is characterized in that:
If the transducing signal array that receives is X={x i(n), i=1,2 ..., N; N=1,2 ..., M}, N are the nodes of sensing network, and M is the analysis length of each node signal, and the normalized autocorrelation functions of each node signal is C i={ E i(x (n), x (n-l)), l=0,1 ..., M}, l are time delay, unit is sampled point, | C i|≤1; If the I node is the node without invasion, signal time auto-correlation length is l during without invasion 1, the J node is the node that invasion is arranged, signal time auto-correlation length was l when invasion was arranged 2, the two, length relation always had 0≤l correlation time 1<l 2
Select a definite time delay l 1<L<l 2, normalizated correlation coefficient E must be arranged I(x (n), x (n-L))<E J(x (n), x (n-L)), and have
Figure FSA00000132368200011
,
Figure FSA00000132368200012
Or E JA normalized autocorrelation coefficient threshold value η is set in (x (n), x (n-L))>>0 c, 0.5<η c<1, judge according to following formula whether the invasion signal exists:
R i = 1 , | E i ( x ( n ) , x ( n - L ) ) | &GreaterEqual; &eta; c 0 , | E i ( x ( n ) , x ( n - L ) ) | < &eta; c - - - ( 1 )
When
Figure FSA00000132368200014
The time, judge not invasion of circumference;
When
Figure FSA00000132368200021
The time, judge that circumference has invasion, signal that invasion is arranged is judged it is to be caused or environmental change causes by artificial invasion according to its frequecy characteristic or the sensing node number that affects and scope again;
To defining artificial invasion after the environmental factor eliminating, corresponding R i≠ 0 node subscript i is the sensing node that invasion action affects, the location of invading according to the installation site of this node.
3. the intrusion detection of non-uniform sensitivity nodes of anti-intrusion system sensing network according to claim 2 and localization method is characterized in that:
If Be the single-point invasion;
If
Figure FSA00000132368200023
To R iContinuous several node i of=1 are carried out cluster, several nodes that can cluster judge it is that invasion action by a point causes, the number of the class of finally determining after the cluster is actual invasion and counts, and the node ordinal number in each class is averaging again round, and carries out the location of multiple spot invasion.
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CN102034330A (en) * 2010-11-05 2011-04-27 电子科技大学 Fire-prevention and invasion-prevention synchronous early warning system and signal processing method thereof
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CN101282266A (en) * 2008-03-05 2008-10-08 中科院嘉兴中心微***所分中心 Intelligent instruction-preventing microwave radar wireless sensor network
CN101290705A (en) * 2008-03-05 2008-10-22 中科院嘉兴中心微***所分中心 Vibration transducer network node consistency calibration method in invasion-proof system
CN101409617A (en) * 2008-10-08 2009-04-15 东南大学 Method for generating inbreak-tolerated wireless sensor network topological

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CN101282266A (en) * 2008-03-05 2008-10-08 中科院嘉兴中心微***所分中心 Intelligent instruction-preventing microwave radar wireless sensor network
CN101290705A (en) * 2008-03-05 2008-10-22 中科院嘉兴中心微***所分中心 Vibration transducer network node consistency calibration method in invasion-proof system
CN101409617A (en) * 2008-10-08 2009-04-15 东南大学 Method for generating inbreak-tolerated wireless sensor network topological

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