CN115185011B - Target detection method applicable to terahertz detection - Google Patents
Target detection method applicable to terahertz detection Download PDFInfo
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Abstract
The application discloses a target detection method applicable to terahertz detection, which comprises the following steps: receiving terahertz waves emitted by a human body by using a radio frequency module; converting signals with different energy into electric signals with different amplitudes by using a terahertz chip, amplifying the electric signals, and converting analog signals into digital signals; and filtering the obtained digital signal, and judging whether a target object exists or not by combining transient analysis and steady state analysis. When the application is applied to actual detection, the application has the advantages of low delay, high precision, good adaptability and the like.
Description
Technical Field
The invention relates to the technical field of terahertz detection methods, in particular to a target detection method applicable to terahertz detection.
Background
Terahertz waves refer to electromagnetic waves having a frequency between 0.1THz and 10 THz. Because of the specific wavelength and characteristics of terahertz waves, terahertz waves penetrate most of materials, and thus it is very suitable to use their characteristics as signals of detection substances.
In recent years, with the development of terahertz wave acquisition and processing technology, the terahertz technology plays an important role in security inspection, such as civil aviation, large-scale conferences and other places. The detection of forbidden articles by terahertz waves can be mainly divided into an active type and a passive type. The active terahertz security inspection equipment sends out terahertz waves with a certain frequency, detects the reflected terahertz waves, and judges whether a target object exists or not; the passive terahertz security inspection equipment mainly analyzes and judges whether a target object exists by receiving terahertz waves emitted by the target.
Disclosure of Invention
The technical problem to be solved by the invention is how to provide a target detection method which can realize real-time detection, and has low delay, high precision and good adaptability.
In order to solve the technical problems, the invention adopts the following technical scheme: the target detection method applicable to terahertz detection is characterized by comprising the following steps of:
Receiving terahertz waves emitted by a human body by using a radio frequency module;
converting signals with different energy into electric signals with different amplitudes by using a terahertz chip, amplifying the electric signals, and converting analog signals into digital signals;
And filtering the obtained digital signal, and judging whether a target object exists or not by combining transient analysis and steady state analysis.
The further technical scheme is that the method for filtering the obtained digital signal comprises the following steps:
first, the terahertz wave signal processed by the method is a set of discrete one-dimensional vectors, and f (t) represents the t-th terahertz wave signal as shown in the following matrix a:
A＝[f(1),f(2),f(3),...........f(t)] (1)
The preprocessing adopts a moving average algorithm, and the formula of the moving average algorithm is shown as follows:
y (l) represents the signal of the optimized first one-dimensional digital signal, f (l) represents the unprocessed one-dimensional digital signal, g (l) represents the fixed one-dimensional convolution kernel for convolution, t represents the currently optimized digital signal, and n is a fixed parameter.
The further technical scheme is that the method for judging whether the target object exists or not by combining transient analysis and steady-state analysis comprises the following steps:
when the terahertz waves emitted by the human body are collected, the moving speeds of the equipment are different, when the moving speed is high, the signals of the terahertz waves are changed violently, a transient analysis method is suitable, and when the moving speed is low, the signals of the terahertz waves are changed slowly, and a steady analysis method is suitable;
Firstly, transient analysis, wherein a discrete signal after filtering processing is set as A', and y (t) represents a t digital signal;
A'＝[y(1),y(2),y(3),...........y(t)] (3)
firstly, the first N data are obtained to obtain the corresponding average value as the following formula (4)
When the (n+1) th data is acquired again, the methodAnd y (n+1), if the following inequality (5) is satisfied, it is considered that there is a corresponding object, θ is a set threshold value:
Updating, if a target object is detected, then/> If no update is performed and no target object is detected, the update is performed using the following formula (6):
secondly, steady state analysis is carried out, the first N data are taken to obtain corresponding average value as The following formula (7) shows:
Taking the data from the (n+1) th to the (2) N th to perform average calculation The following formula (8) shows:
If it is And/>Satisfying the following inequality (9), it can be considered that the target object is detected, β being a selected threshold:
Updating, if a target object is detected, then/> If no target object is detected, the update is performed using the following formula:
In the transient analysis and the steady-state analysis described above, the transient analysis corresponds to the rapid scan, and the steady-state analysis corresponds to the slower scan, so that when the equation (5) or the equation (9) is satisfied, it can be considered that the target object is detected.
The beneficial effects of adopting above-mentioned technical scheme to produce lie in: the method comprises the steps of firstly receiving terahertz waves emitted by a human body by using a radio frequency module, then converting signals with different energies into electric signals with different amplitudes by using a terahertz chip, amplifying the electric signals, and converting analog signals into digital signals. And finally, filtering the obtained digital signal, and judging whether a target object exists or not by combining transient analysis and steady state analysis. When the application is applied to actual detection, the application has the advantages of low delay, high precision, good adaptability and the like.
Drawings
The invention will be described in further detail with reference to the drawings and the detailed description.
Fig. 1 is a diagram of a terahertz wave signal directly collected and a terahertz signal after filtering processing in the method according to the embodiment of the present invention;
FIG. 2 is a diagram of terahertz wave signals when a target object is detected in a method according to an embodiment of the present invention;
Fig. 3 is an overall flow chart of a method according to an embodiment of the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present invention is not limited to the specific embodiments disclosed below.
As shown in fig. 3, the embodiment of the invention discloses a target detection method applicable to terahertz detection, which comprises the following steps:
firstly, receiving terahertz waves emitted by a human body by utilizing a radio frequency module;
secondly, converting signals with different energies into electric signals with different amplitudes by using a terahertz chip, amplifying the electric signals, and converting analog signals into digital signals;
And finally, filtering the obtained digital signal, and judging whether a target object exists or not by combining transient analysis and steady state analysis.
The method mainly comprises the steps of preprocessing the acquired terahertz wave signals and judging whether a target object is detected by utilizing the filtered signals.
First, the terahertz wave signals processed by the method are a group of discrete one-dimensional vectors, and f (t) represents the t-th terahertz wave signal as shown in the following matrix A:
A＝[f(1),f(2),f(3),...........f(t)] (1)
in the acquired terahertz wave signals, the existing interference signals can cause burrs or other severe fluctuation of the original signals, which can lead to wrong judgment results, so that the obtained signals are preprocessed before judging whether targets exist or not by using the signals. Excess burrs and irrelevant disturbances are removed as much as possible.
The preprocessing adopts a moving average algorithm, and the formula of the moving average algorithm is shown as the following formula (2).
Y (l) represents the signal of the optimized first one-dimensional digital signal, f (l) represents the unprocessed one-dimensional digital signal, g (l) represents the fixed one-dimensional convolution kernel for convolution, and t represents the currently optimized digital signal. n is a fixed parameter. The moving average algorithm has the advantage that when calculating the value of the digital signal, the average value of a plurality of data is utilized and is continuously updated, so that the moving average algorithm has good self-adaptive characteristic.
The method judges whether the target object is comprehensively judged by transient analysis and steady state analysis.
When terahertz waves emitted by a human body are collected, the moving speeds of the equipment are different. When the moving speed is high, the signal of the terahertz wave changes violently, so that the method is suitable for utilizing transient analysis, and when the moving speed is low, the signal of the terahertz wave changes slowly, so that the method is suitable for utilizing steady-state analysis.
Firstly, transient analysis is carried out, wherein the discrete signal after filtering processing is set as A', and y (t) represents a t-th digital signal:
A'＝[y(1),y(2),y(3),...........y(t)] (3)
firstly, the first N data are obtained to obtain the corresponding average value as the following formula (4)
When the (n+1) th data is acquired again, the methodAnd y (n+1), if the following inequality (5) is satisfied, it is considered that there is a corresponding object, θ is a set threshold value:
Updating, if a target object is detected, then/> If no update is performed and no target object is detected, the update is performed using the following formula (6):
secondly, steady state analysis is carried out, the first N data are taken to obtain corresponding average value as The following formula (7) shows:
Taking the data from the (n+1) th to the (2) N th to perform average calculation The following formula (8) shows:
If it is And/>Satisfying the following inequality (9), it can be considered that the target object is detected, β being a selected threshold:
Updating, if a target object is detected, then/> If no target object is detected, the update is performed using the following formula:
In the transient analysis and steady state analysis described above, the transient analysis corresponds to a fast sweep, while the steady state analysis corresponds to a slower sweep. Thus, when equation (5) or equation (9) is satisfied, it can be considered that the target object is detected.
Comparing the directly collected terahertz wave signal with the terahertz signal after filtering processing, and the situation that the target object is detected at different speeds, fig. 1 is the directly collected terahertz wave signal and the terahertz signal after filtering processing, and fig. 2 is the terahertz wave signal when the target object is detected.
In fig. 1, it can be seen that the disturbance and burr of the unfiltered terahertz wave signal are relatively large, and the signal becomes smooth after the filtering process.
Fig. 2 is a variation of the terahertz wave signal when the target object is detected. When the terahertz waves of the surface of the human body are acquired, if no target object exists, the signal can remain stable and the absolute value of the signal is relatively large.
If the target object is detected, the transient analysis is reduced, the transient analysis proposed by the application is mainly aimed at the state of rapid scanning in fig. 2, and when the target object is detected, the signal change is intense and the duration is short; the steady state analysis is mainly aimed at the slow scanning state in fig. 2, when a target is detected, the signal amplitude is reduced and the duration is longer, and the steady state analysis can avoid the deviation of the reference quantity and accurately judge the target.
Claims (1)
1. The target detection method applicable to terahertz detection is characterized by comprising the following steps of:
Receiving terahertz waves emitted by a human body by using a radio frequency module;
converting signals with different energy into electric signals with different amplitudes by using a terahertz chip, amplifying the electric signals, and converting analog signals into digital signals;
Filtering the obtained digital signal, and judging whether a target object exists or not by combining transient analysis and steady state analysis;
The method for filtering the obtained digital signal comprises the following steps:
first, the terahertz wave signal processed by the method is a set of discrete one-dimensional vectors, and f (t) represents the t-th terahertz wave signal as shown in the following matrix a:
A＝[f(1),f(2),f(3),...........f(t)] (1)
The preprocessing adopts a moving average algorithm, and the formula of the moving average algorithm is shown as follows:
y (l) represents the signal of the optimized first one-dimensional digital signal, f (l) represents the unprocessed one-dimensional digital signal, g (l) represents the fixed one-dimensional convolution kernel for convolution, t represents the currently optimized digital signal, and n is a fixed parameter;
The method for judging whether the target object exists or not by combining transient analysis and steady-state analysis comprises the following steps:
when the terahertz waves emitted by the human body are collected, the moving speeds of the equipment are different, when the moving speed is high, the signals of the terahertz waves are changed violently, a transient analysis method is suitable, and when the moving speed is low, the signals of the terahertz waves are changed slowly, and a steady analysis method is suitable;
Firstly, transient analysis, wherein a discrete signal after filtering processing is set as A', and y (t) represents a t digital signal;
A'＝[y(1),y(2),y(3),...........y(t)] (3)
firstly, the first N data are obtained to obtain the corresponding average value as the following formula (4)
When the (n+1) th data is acquired again, the methodAnd y (n+1), if the following inequality (5) is satisfied, it is considered that there is a corresponding object, θ is a set threshold value:
Updating, if a target object is detected, then/> If no update is performed and no target object is detected, the update is performed using the following formula (6):
secondly, steady state analysis is carried out, the first N data are taken to obtain corresponding average value as The following formula (7) shows:
Taking the data from the (n+1) th to the (2) N th to perform average calculation The following formula (8) shows:
If it is And/>Satisfying the following inequality (9), then it is assumed that the target object is detected, β being the selected threshold:
Updating, if a target object is detected, then/> If no target object is detected, the update is performed using the following formula:
In the transient analysis and the steady-state analysis described above, the transient analysis corresponds to the fast scan, and the steady-state analysis corresponds to the slower scan, so that when the equation (5) or the equation (9) is satisfied, it is considered that the target object is detected.
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| CN102280103A (en) * | 2011-08-02 | 2011-12-14 | 天津大学 | Audio signal transient-state segment detection method based on variance |
| CN106990062A (en) * | 2017-03-14 | 2017-07-28 | 天津大学 | A kind of contaminated product detection method based on Terahertz rotation effect |
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| JP4654996B2 (en) * | 2006-07-12 | 2011-03-23 | 株式会社島津製作所 | Terahertz wave response measuring device |
| FR2944103B1 (en) * | 2009-04-01 | 2011-06-10 | Centre Nat Rech Scient | TERA-HERTZ IMAGING WITH IMPROVED INFRARED CONVERTER. |
| CN107092040A (en) * | 2017-06-01 | 2017-08-25 | 上海理工大学 | Terahertz imaging rays safety detection apparatus and video procession method |
| KR20190143148A (en) * | 2018-06-20 | 2019-12-30 | (주)레이텍 | Noise Elimination TerahertzWave Object Inspection Apparatus |
| CN112505798B (en) * | 2020-11-27 | 2022-07-01 | 河北雄安太芯电子科技有限公司 | Object detection method based on terahertz |
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| CN102280103A (en) * | 2011-08-02 | 2011-12-14 | 天津大学 | Audio signal transient-state segment detection method based on variance |
| CN106990062A (en) * | 2017-03-14 | 2017-07-28 | 天津大学 | A kind of contaminated product detection method based on Terahertz rotation effect |
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