阅读说明：本技术 基于太赫兹的物体检测方法 (Object detection method based on terahertz ) 是由 王跃东 胡志富 任玉兴 何美林 曹健 刘亚男 彭志农 于 2020-11-27 设计创作，主要内容包括：本发明公开了一种基于太赫兹的物体检测方法,所述方法涉及太赫兹检测技术领域。所述方法包括如下步骤：利用接收装置对目标自身发射的太赫兹信号进行接收,然后利用太赫兹芯片将不同能量的信号转换成不同幅度的电信号并放大,并将模拟信号转换成数字信号；对得到的数字信号进行移动均值处理,再利用瞬时能量分析的方法,判断是否存在相应物体。所述方法在应用于实际检测时,具有延时地,精度高,适应性好等优点。(The invention discloses an object detection method based on terahertz, and relates to the technical field of terahertz detection. The method comprises the following steps: the method comprises the steps that a receiving device is used for receiving terahertz signals emitted by a target, then terahertz chips are used for converting signals with different energies into electric signals with different amplitudes and amplifying the electric signals, and analog signals are converted into digital signals; and (4) carrying out moving average processing on the obtained digital signals, and judging whether corresponding objects exist by using an instantaneous energy analysis method. When the method is applied to actual detection, the method has the advantages of time delay, high precision, good adaptability and the like.)

1. An object detection method based on terahertz is characterized by comprising the following steps:

receiving a terahertz signal emitted by a target by using a receiving device;

then, converting signals with different energies into electric signals with different amplitudes by utilizing a terahertz chip, amplifying the electric signals, and converting analog signals into digital signals;

and (4) carrying out moving average processing on the obtained digital signals, and judging whether corresponding objects exist by using an instantaneous energy analysis method.

2. The terahertz-based object detection method as claimed in claim 1, wherein: the digital signal is a discrete string of signals, and is a one-dimensional matrix which is continuously updated, as shown in the following matrix A, f (t) represents the t-th digital signal:

A＝[f(1),f(2),f(3),...........f(t)]。

3. the terahertz-based object detecting method according to claim 2, wherein: the formula of the moving average algorithm is shown as follows:

in the formula: y (l) represents 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 used for convolution, t represents the currently optimized digital signal, and n is a fixed parameter.

4. The terahertz-based object detecting method according to claim 3, wherein: the method adopts terahertz waves of a plurality of channels to detect objects, and the threshold values of different channels are set to be theta respectively₁，θ₂，θ₃.......θ_mAnd respectively calculating the variable quantities of the terahertz signals on different paths, wherein the variable quantities are shown in the following formula:

wherein: m denotes the number of independent channels, T denotes the interval of two discrete signals, y_m' obtaining variable y representing the intensity of the signal change of the m-th channel₁’，y₂’,......y_mThen, in a larger time interval N, the corresponding variation of different time periods y is obtained, a plurality of variations in the data are respectively compared with corresponding thresholds, and if the number of variations satisfying the preset threshold reaches a certain value, the object is considered to be detected.

5. The terahertz-based object detection method as claimed in claim 1, wherein: the terahertz waves of all the channels exist in parallel in receiving, processing and analyzing, and the detection results of all the channels are mutually independent.

Technical Field

The invention relates to the technical field of terahertz detection, in particular to an object detection method based on terahertz.

Background

In recent years, with artificial intelligence, industries such as fire heating, automatic driving, intelligent transportation, and three-dimensional modeling security inspection of bulk goods have made higher demands on object detection. The automatic driving needs to acquire the contour of a surrounding object in time, the intelligent transportation needs to detect people and vehicles at any time, and the modeling and security inspection need to monitor dangerous goods by computer vision or electromagnetic waves. It is necessary to develop a substance detection algorithm suitable for different situations.

In the aspect of object detection, the electromagnetic wave has wider application range compared with computer vision. The detection of objects using electromagnetic wave detection techniques is also currently one of the main flow directions. The method for detecting the object by using the electromagnetic wave can be divided into a passive mode and an active mode, the active mode detection depends on relevant equipment to emit the electromagnetic wave, the attribute of the object is judged by analyzing the reflected electromagnetic wave, the passive mode detection depends on the electromagnetic wave emitted by the object to analyze, the two methods have advantages and disadvantages, the active mode detection is mainly used for large-scale equipment, and the passive mode detection is mainly used for convenient detection. Terahertz waves refer to electromagnetic waves having a frequency of from 0.1THz to 10 THz. Because the terahertz wave can penetrate most materials at a special position on an electromagnetic spectrum, the terahertz wave is quite suitable for being used as a signal for detecting a substance by utilizing the transmission and reflection characteristics of the terahertz wave, but the method for detecting the object by the terahertz wave in the prior art is generally low in accuracy, high in false alarm rate and poor in detection effect.

Disclosure of Invention

The invention aims to solve the technical problem of how to provide a terahertz-based object detection method with high detection precision and good adaptability.

In order to solve the technical problems, the technical scheme adopted by the invention is as follows: an object detection method based on terahertz is characterized by comprising the following steps:

the terahertz signal emitted by the target is received by using a receiving device,

then, converting signals with different energies into electric signals with different amplitudes by utilizing a terahertz chip, amplifying the electric signals, and converting analog signals into digital signals;

and (4) carrying out moving average processing on the obtained digital signals, and judging whether corresponding objects exist by using an instantaneous energy analysis method.

Adopt the produced beneficial effect of above-mentioned technical scheme to lie in: according to the method, the terahertz signals transmitted by the target are received by the receiving device, the terahertz chips are used for converting the signals with different energies into electric signals with different amplitudes and amplifying the electric signals, the analog signals are converted into digital signals, the obtained digital signals are subjected to moving average processing, and whether corresponding objects exist or not is judged by using an instantaneous energy analysis method.

Drawings

The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.

FIG. 1 is a flow chart of a method according to an embodiment of the invention;

FIG. 2 is a graph of an unprocessed terahertz wave signal in a method according to an embodiment of the present invention;

FIG. 3 is a signal diagram of a method according to an embodiment of the present invention processed by mean filtering;

fig. 4 is a diagram of the change of the signal when the target object is detected by the method according to the embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention are clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present 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 than those specifically described and will be readily apparent to those of ordinary skill in the art without departing from the spirit of the present invention, and therefore the present invention is not limited to the specific embodiments disclosed below.

As shown in fig. 1, an embodiment of the present invention discloses a terahertz-based object detection method, including the following steps:

receiving a terahertz signal emitted by a target by using a receiving device;

the terahertz chip is used for converting signals with different energies into electric signals with different amplitudes, amplifying the electric signals, and converting analog signals into digital signals;

and (4) carrying out moving average processing on the obtained digital signals, and judging whether corresponding objects exist by using an instantaneous energy analysis method.

The raw data processed by this method is a discrete, continuously updated one-dimensional matrix, as shown in the following matrix a, where f (t) represents the t-th digital signal.

A＝[f(1),f(2),f(3),...........f(t)] (1)

In the acquired digital signal, the existence of the interference signal may cause the algorithm to make a false judgment when there is no detected object or cause a short and drastic change in the signal, which is very disadvantageous for the subsequent processing and analysis of the signal, so that the obtained signal is preprocessed before the analysis and judgment of the signal are performed. The purpose of the preprocessing is to smooth the digital signal and reduce the influence of external interference.

The preprocessing adopts a moving average algorithm, and the formula of the moving average algorithm is shown as the following formula (2).

Wherein y (l) represents the signal of the first optimized 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 moving average algorithm has the advantages that when the value of the digital signal is calculated, the average value of a plurality of items of data is utilized and is continuously updated, and the moving average algorithm has good self-adaptive characteristics.

The method adopts an instantaneous energy analysis method for judging whether an object exists or not, and realizes dynamic instantaneous rapid analysis. Secondly, in order to improve the success rate of object detection, the method utilizes multiple paths of parallel terahertz signals to carry out detection.

In the experimental stage of the algorithm, terahertz waves of a plurality of channels are adopted for object detection, and the threshold values of different paths are set to be theta respectively₁，θ₂，θ₃.......θ_mAnd respectively calculating the variation of the terahertz signals on different paths, as shown in the following formulas (3-5).

Wherein: m denotes the number of independent channels, T denotes the interval of two discrete signals, y_m' indicates the strength of the signal change of the mth channel, and the other symbols are defined in accordance with equation 1. Finding the variable y₁’，y₂’,……y_mThen, in a larger time interval N, the corresponding variation of different time periods y is obtained, the plurality of variations in the data are respectively compared with corresponding thresholds, and if the number of variations satisfying the preset threshold reaches a certain value, it can be considered that an object is detected. Secondly, the terahertz waves of each channel are received, processed and analyzed in parallel, so that the detection nodes of each channel existThe fruits are independent of each other.

In order to visually see the optimization of the signal and determine whether the target object exists by using the signal, as shown in fig. 2-3, fig. 2 shows the unprocessed terahertz wave signal and the signal after the mean value filtering process, and fig. 3 shows the change of the signal when the target object is detected.

In fig. 2, it can be seen that there are many interference signals in the unprocessed signal, and in many cases, there are short and sharp fluctuations, while the processed signal has almost no spike and sharp fluctuation, and the curve is smooth. Fig. 4 shows the change of the signal when an object is detected.

In conclusion, the method has the advantages of time delay, high precision, good adaptability and the like when being applied to actual detection.