CN113589394A - Method and equipment for identifying target detection object based on photoelectric sensor - Google Patents
Method and equipment for identifying target detection object based on photoelectric sensor Download PDFInfo
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Abstract
The method comprises the steps that a first path of electric signals obtained by a photoelectric sensor is used as measured data, and a second path of electric signals obtained by the photoelectric sensor is processed to obtain a time-base signal; processing the measured data according to the time base signal and a Kalman filtering algorithm to obtain observation data; determining a digital signal of a target detection object according to the measured data and the observation data; and identifying the category of the target detection object according to the digital signal. Therefore, the interference of ambient light, sunlight, rainwater and the like can be eliminated, the condition that the photoelectric sensor is misjudged due to the influence of interferents is prevented, and the detection precision is improved.
Description
Technical Field
The present application relates to the field of sensors, and in particular, to a method and apparatus for identifying a target detection object based on a photoelectric sensor.
Background
With the continuous diversified development of the activity places of people and the more and more standard area division, the gate is widely applied to area management and can be seen in places such as airports, subways, banks, hotel scenic spots, markets and the like. The gate is usually provided with an identification device for identifying people or objects, for example, a photoelectric sensor is arranged to detect whether a vehicle passes through or not, people pass through or not through the photoelectric sensor, and the conventional gate using the photoelectric sensor has a misjudgment phenomenon under interference factors such as rainstorm, sunlight and ambient light, and has low identification precision.
Disclosure of Invention
An object of the present application is to provide a method and an apparatus for identifying a target detection object based on a photoelectric sensor, which solve the problems of erroneous judgment and low identification precision caused by the influence of an interference environment when detecting the target detection object in the prior art.
According to an aspect of the present application, there is provided a method of identifying a target detection object based on a photosensor, the method including:
taking a first path of electric signal obtained by a photoelectric sensor as measured data, and processing a second path of electric signal obtained by the photoelectric sensor to obtain a time-base signal;
processing the measured data according to the time base signal and a Kalman filtering algorithm to obtain observation data;
determining a digital signal of a target detection object according to the measured data and the observation data;
and identifying the category of the target detection object according to the digital signal.
Optionally, the method comprises:
and converting an optical signal received by the photoelectric sensor when the target detection object is measured into an electric signal, and dividing the electric signal into a first path of electric signal and a second path of electric signal.
Optionally, the step of processing a second path of electric signal obtained by the photoelectric sensor to obtain a time-based signal, which includes:
transmitting the first path of electric signal obtained by the photoelectric sensor to a control center of the photoelectric sensor as measured data;
and performing square wave shaping on the second path of electric signal obtained by the photoelectric sensor to obtain a time-base signal.
Optionally, the squaring the second path of electrical signal obtained by the photosensor to obtain a time-based signal includes:
and performing square wave shaping on the second path of electric signals obtained by the photoelectric sensor to filter useless electric signals in a time sequence, wherein the filtered electric signals are time-base signals, and the useless electric signals comprise electric signals obtained when the second path of electric signals are switched off by the emitted light of the photoelectric sensor.
Optionally, determining a digital signal of a target detection object according to the measured data and the observation data includes:
determining a dynamic weight fitting data curve of the attribution type of the target detection object according to the measured data, the observation data and a corresponding fitting algorithm;
and carrying out binarization processing on the dynamic weight fitting data curve to obtain a corresponding digital signal.
Optionally, the photoelectric sensor includes a transmitter and a receiver, and identifies the category of the target detection object according to the digital signal, including:
and judging whether the sensitization quantity sent by the emitter is received by the receiver or not according to the digital signal, if so, identifying the category of the target detection object shielding the signal sent by the emitter according to the times of receiving the sensitization signal in a period.
Optionally, processing the measured data according to the time-base signal and a kalman filtering algorithm to obtain observed data, including:
determining a Kalman gain based on the covariance of the state of the Kalman filter used and the covariance of the state at the present time determined by the time-based signal;
and calculating an optimal estimation value of the measured data according to the measured data and the Kalman gain, and obtaining observation data according to the optimal estimation value.
Optionally, the photoelectric sensor is applied to a gate, and the method comprises:
if the number of times that the receiver receives the photosensitive signals in a period is larger than a first threshold value, outputting a signal of no action to the gate by the photoelectric sensor;
if the number of times that the receiver receives the photosensitive signals in a period is smaller than a second threshold value, the photoelectric sensor outputs signals of action to the gate;
if the number of times of receiving the light sensing signal in one period by the receiver is between the second threshold value and the first threshold value, the operation state of the output of the photoelectric sensor is maintained.
According to still another aspect of the present application, there is also provided an apparatus for recognizing a target detection object based on a photosensor, the apparatus including:
the acquisition device is used for taking the first path of electric signals obtained by the photoelectric sensor as measured data, and processing the second path of electric signals obtained by the photoelectric sensor to obtain time base signals;
the processing device is used for processing the actually measured data according to the time base signal and a Kalman filtering algorithm to obtain observed data;
the determining device is used for determining a digital signal of a target detection object according to the measured data and the observed data;
and the identification device is used for identifying the category of the target detection object according to the digital signal.
According to still another aspect of the present application, there is also provided an apparatus for recognizing a target detection object based on a photosensor, the apparatus including:
one or more processors; and
a memory storing computer readable instructions that, when executed, cause the processor to perform the operations of the method as previously described.
According to yet another aspect of the present application, there is also provided a computer readable medium having computer readable instructions stored thereon, the computer readable instructions being executable by a processor to implement the method as described above.
Compared with the prior art, the method has the advantages that the first path of electric signals obtained by the photoelectric sensor are used as measured data, and the second path of electric signals obtained by the photoelectric sensor are processed to obtain time base signals; processing the measured data according to the time base signal and a Kalman filtering algorithm to obtain observation data; determining a digital signal of a target detection object according to the measured data and the observation data; and identifying the category of the target detection object according to the digital signal. Therefore, the interference of ambient light, sunlight, rainwater and the like can be eliminated, the condition that the photoelectric sensor is misjudged due to the influence of interferents is prevented, and the detection precision is improved.
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Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
fig. 1 illustrates a schematic flow chart of a method for identifying a target detection object based on a photoelectric sensor according to an aspect of the present application;
fig. 2 shows a schematic diagram of an electrical quantity signal collected in an embodiment of the present application;
FIG. 3 is a schematic diagram of a time-based signal in one embodiment of the present application;
FIG. 4 is a schematic diagram illustrating observation data obtained after Kalman filtering in an embodiment of the present application;
FIG. 5 is a schematic diagram illustrating a method for processing an optical signal of a photosensor during recognition of a target detection object according to an embodiment of the present application;
fig. 6 is a schematic structural diagram illustrating an apparatus for recognizing a target detection object based on a photosensor according to still another aspect of the present application.
The same or similar reference numbers in the drawings identify the same or similar elements.
Detailed Description
The present application is described in further detail below with reference to the attached figures.
In a typical configuration of the present application, the terminal, the device serving the network, and the trusted party each include one or more processors (e.g., Central Processing Units (CPUs)), input/output interfaces, network interfaces, and memory.
The Memory may include volatile Memory in a computer readable medium, Random Access Memory (RAM), and/or nonvolatile Memory such as Read Only Memory (ROM) or flash Memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, Phase-Change RAM (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), flash Memory or other Memory technology, Compact Disc Read-Only Memory (CD-ROM), Digital Versatile Disc (DVD) or other optical storage, magnetic cassette tape, magnetic tape storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include non-transitory computer readable media (transient media), such as modulated data signals and carrier waves.
Fig. 1 is a schematic flow chart illustrating a method for identifying a target detection object based on a photoelectric sensor according to an aspect of the present application, the method including: step S11 to step S14, wherein in step S11, the first path of electric signal obtained by the photoelectric sensor is used as measured data, and the second path of electric signal obtained by the photoelectric sensor is processed to obtain a time-base signal; step S12, processing the measured data according to the time base signal and a Kalman filtering algorithm to obtain observed data; step S13, determining the digital signal of the target detection object according to the measured data and the observation data; and step S14, identifying the category of the target detection object according to the digital signal. Therefore, the interference of ambient light, sunlight, rainwater and the like can be eliminated, the condition that the photoelectric sensor is misjudged due to the influence of interferents is prevented, and the detection precision is improved.
Specifically, in step S11, the first electrical signal obtained by the photoelectric sensor is used as measured data, and the second electrical signal obtained by the photoelectric sensor is processed to obtain a time-base signal; here, photoelectric sensor includes the photoelectricity correlation switch, can be used for receiving the light signal to convert received light signal into the signal of telecommunication, in this application, can divide into two way signals with the signal of telecommunication after the conversion, electric quantity signal of the same way is as the measured signal, and another way electric quantity signal obtains time base signal after handling, thereby obtains the chronogenesis that hardware circuit obtained.
Step S12, processing the measured data according to the time base signal and a Kalman filtering algorithm to obtain observed data; the obtained actual measurement data is processed according to the obtained time sequence (namely, time base signal) and the algorithm of the Kalman filter, so that useless data can be removed, observation data is obtained, namely, the data obtained when the photoelectric sensor measures the target detection object is filtered according to the time base signal, and then the real observation data is obtained, and the interference of the external environment is avoided.
In step S13, determining a digital signal of a target detection object according to the measured data and the observation data; here, the actual measured data and the observation data are used to perform dynamic weight calculation, so as to obtain a digital signal of a target detection object, the target detection object is a detected object when the photoelectric sensor performs detection, and the digital signal is a discrete signal given a numerical value, such as a binarized signal; thereby identifying the category to which the target detection object belongs from the digital signal in step S14. Whether a signal which is sent by the photoelectric sensor and used for detecting a target detection object is received again or not and whether a vehicle or a pedestrian or other objects are shielded or not is judged according to the obtained digital signal, the category of the target detection includes an object and no object, and the object includes the vehicle, the pedestrian or other objects.
In some embodiments of the present application, the method comprises: and converting an optical signal received by the photoelectric sensor when the target detection object is measured into an electric signal, and dividing the electric signal into a first path of electric signal and a second path of electric signal. Here, the electric quantity signal obtained by processing the optical signal received by the photoelectric sensor when measuring the target detection object by the hardware circuit is positively correlated with the intensity of the photosensitive signal, and the electric quantity signal is divided into two paths of electric signals, namely a first circuit signal and a second circuit signal.
In step S11, the first path of electrical signal obtained by the photoelectric sensor is transmitted to the control center of the photoelectric sensor as measured data; and performing square wave shaping on the second path of electric signal obtained by the photoelectric sensor to obtain a time-base signal. The control center of the photoelectric sensor is a photoelectric sensor embedded main control Chip (CPU), and the first circuit signal is transmitted to the CPU to be used as measured data; the second path of electric signals are shaped by a circuit to obtain square waves as time base signals for software filtering, the time base signals are transmitted to a CPU, actual measurement data shown in figure 2 are obtained, square wave shaping processing is carried out on the obtained electric signals, time base signals are obtained as shown in figure 3, the actual measurement data on a time axis are screened by the time base signals, and the time base signals are transmitted to a Kalman filtering algorithm to obtain observation data, such as the observation data shown in figure 4; the measured data is the light receiving quantity of the photoelectric tube including the photoelectric sensor and an electric quantity signal matched with the light receiving quantity, and the electric quantity signal is amplified by a circuit. Wherein the abscissa in fig. 2, 3 and 4 denotes time and the ordinate denotes voltage.
In some embodiments of the present application, in step S11, the second electrical signal obtained by the photosensor is square-wave shaped to filter out useless electrical signals in time sequence, where the filtered electrical signals are time-based signals, and the useless electrical signals include the electrical signals obtained when the emission light of the photosensor is turned off in the second electrical signal. Here, filtering processing is performed on the useless time signals through square waves to obtain time base signals, so that time delay is avoided, namely, electric quantity signals on synchronous and useful time sequences are avoided; the light emitted by the photoelectric sensor is in a pulse modulation mode, the electric signal converted by the received light quantity can also be periodically changed along with the emission period, when the emitted light is turned off, the corresponding electric quantity signal is a useless signal, and the useless signal comprises a signal interfered by ambient light. Therefore, the obtained second circuit signal is filtered, and a useful time base signal which is not interfered by ambient light can be obtained, so that the time base signal can be used for identifying the target detection object more accurately.
In some embodiments of the present application, in step S13, a dynamic weight fitting data curve of the attribution category of the target detection object is determined according to the measured data, the observation data and a corresponding fitting algorithm; and carrying out binarization processing on the dynamic weight fitting data curve to obtain a corresponding digital signal. The dynamic weight fitting data curve is given according to the measured data, the obtained observation data and the corresponding fitting algorithm, wherein the corresponding fitting algorithm can comprise sine regression fitting, the fitting algorithm can use decision tree regression algorithm to fit the dynamic weight fitting data curve, then the dynamic weight fitting data curve is subjected to binarization processing and converted into a digital signal, and therefore whether the measured object is a vehicle, a pedestrian or other objects is judged according to the digital signal, and the rainstorm interference is eliminated.
In some embodiments of the present application, the photoelectric sensor includes a transmitter and a receiver, and in step S14, it is determined whether the amount of light received by the receiver is greater than or equal to a predetermined amount of light received by the transmitter according to the digital signal, and if so, the type of the target object that blocks the signal sent by the transmitter is identified according to the number of times the light is received within a period. The photoelectric sensor comprises a transmitter and a receiver, the transmitter sends out a photosensitive quantity, the receiver receives a light signal returned after the photosensitive quantity is shielded by a detected object, whether the photosensitive quantity sent out by the transmitter is received by the receiver is judged according to a binary signal of dynamic weight obtained through calculation, if yes, the object is shielded, and the type of the target detected object is continuously judged according to the number of times of the photosensitive signal received in one period of the receiver, namely, whether the target detected object belongs to a vehicle or a pedestrian or other objects is judged.
In some embodiments of the present application, the photoelectric sensor is applied to a gate, and the method includes: if the number of times that the receiver receives the photosensitive signals in a period is larger than a first threshold value, outputting a signal of no action to the gate by the photoelectric sensor; if the number of times that the receiver receives the photosensitive signals in a period is smaller than a second threshold value, the photoelectric sensor outputs signals of action to the gate; if the number of times of receiving the light sensing signal in one period by the receiver is between the second threshold value and the first threshold value, the operation state of the output of the photoelectric sensor is maintained. The photoelectric sensor is applied to gates, such as a barrier gate for detecting vehicles, a subway gate for detecting pedestrians, a security gate and the like, the time-base signal is used as time sequence control, binarization processing is carried out after a filtering algorithm is combined to obtain a binarization signal, so as to utilize the binary signal to obtain that the photosensitive quantity signal sent by transmitter is received by receiver or not, and then, the number of times of receiving the photosensitive signals in a period (such as 20ms) is used to determine whether the signal sent by the emitter is blocked by a target detection object such as a vehicle or a pedestrian, for example, if the signal is greater than a first threshold (8 times), the signal is regarded as not acting, if the number of times of receiving the photosensitive signals is less than a second threshold (3 times), the signal is regarded as an object passing through the waiting area, the signal is determined as acting, and 3-8 times, determining that interference signals such as rainwater and sunlight exist in the measurement period, and keeping the output action state as the original state.
In some embodiments of the present application, in step S12, a kalman gain is determined from the covariance of the state of the kalman filter used and the covariance of the state at the present time determined from the time base signal; and calculating an optimal estimation value of the measured data according to the measured data and the Kalman gain, and obtaining observation data according to the optimal estimation value. And the measured data comprises the influence of noise and interference in the system, and the filtered data is obtained through the optimal estimation, so that the observed data is obtained. Wherein, the process of using the Kalman filter is as follows:
q ═ 0.00001, representing the covariance of the noise, i.e. the deviation of the noise between two moments; r ═ 0.1, representing the covariance of the state, i.e. the deviation of the state between two moments; pk1, representing the state covariance at the previous moment, with an input parameter xk＝xk1，Pk＝Pk1+ Q, Kalman gain Kg＝Pk/(Pk+ R) so that the optimum estimation value kalman _ adc is xk+Kg*(Zk-kalman_adcold) Updating the state covariance: pk＝Pk1Recording the output parameters: ADC _ Valueold＝ADC_Value，kalman_adcoldKalman _ adc; where ADC _ Value ═ 0 denotes the last ADC Value, kalman _ ADColdAnd 0 represents the optimal estimation value obtained by the last kalman filtering.
In a specific embodiment of the present application, the wavelength range of the light is matched by a transmitting tube and a receiving tube of the photoelectric sensor, the transmitting tube preferably selects a 940nm wavelength transmitting tube, and the receiving tube selects a receiving peak value in a range near the wavelength; as shown in fig. 5, two paths of processing are performed on the original data received by the receiving tube, one path of processing is performed by hardware binarization to obtain a time base signal, the time base signal is used as a software recording time sequence, the other path of processing is performed by analog-to-digital conversion (ADC conversion), kalman filtering is performed to obtain a software binarization signal, and according to the obtained time base signal and the binarization signal and the comprehensively recorded pulse frequency, whether the pulse frequency within a unit time (for example, 1ms) is greater than 80 is judged, if so, no object is occluded, and at this time, the output of the photoelectric sensor is not operated, if not, whether the pulse frequency within the unit time is less than 30 is continuously judged, if so, an object is occluded, at this time, the sensor outputs an operation, and gives a main control signal to the gate machine, and prevents people or vehicles from being crushed, and if not, the output of the sensor is maintained. When the hardware binarization is carried out, the time-base signal is obtained mainly by a comparator part in a hardware circuit, the part exceeding a set threshold value is binarized into 1, and the part lower than the set threshold value is binarized into 0.
In addition, the embodiment of the present application also provides a computer readable medium, on which computer readable instructions are stored, the computer readable instructions being executable by a processor to implement the aforementioned method for identifying a target detection object based on a photoelectric sensor.
In correspondence with the method described above, the present application also provides a terminal, which includes modules or units capable of executing the steps of the method described in fig. 1 or each embodiment, and these modules or units can be implemented by hardware, software or a combination of hardware and software, and this application is not limited thereto. For example, in an embodiment of the present application, there is also provided an apparatus for identifying a target detection object based on a photosensor, the apparatus including:
one or more processors; and
a memory storing computer readable instructions that, when executed, cause the processor to perform the operations of the method as previously described.
For example, the computer readable instructions, when executed, cause the one or more processors to:
taking a first path of electric signal obtained by a photoelectric sensor as measured data, and processing a second path of electric signal obtained by the photoelectric sensor to obtain a time-base signal;
processing the measured data according to the time base signal and a Kalman filtering algorithm to obtain observation data;
determining a digital signal of a target detection object according to the measured data and the observation data;
and identifying the category of the target detection object according to the digital signal.
Fig. 6 shows a schematic structural diagram of an apparatus for identifying a target detection object based on a photosensor, the apparatus including: the device comprises an acquisition device 11, a processing device 12, a determination device 13 and an identification device 14, wherein the acquisition device 11 is used for taking a first path of electric signals obtained by a photoelectric sensor as measured data, and processing a second path of electric signals obtained by the photoelectric sensor to obtain a time-base signal; the processing device 12 is configured to process the measured data according to the time-base signal and a kalman filtering algorithm to obtain observed data; the determining device 13 is used for determining a digital signal of a target detection object according to the measured data and the observed data; the identification device 14 is used for identifying the category of the target detection object according to the digital signal.
It should be noted that the content executed by the obtaining device 11, the processing device 12, the determining device 13 and the identifying device 14 is the same as or corresponding to the content in the above steps S11, S12, S13 and S14, respectively, and for brevity, the description is omitted here.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
It should be noted that the present application may be implemented in software and/or a combination of software and hardware, for example, implemented using Application Specific Integrated Circuits (ASICs), general purpose computers or any other similar hardware devices. In one embodiment, the software programs of the present application may be executed by a processor to implement the steps or functions described above. Likewise, the software programs (including associated data structures) of the present application may be stored in a computer readable recording medium, such as RAM memory, magnetic or optical drive or diskette and the like. Additionally, some of the steps or functions of the present application may be implemented in hardware, for example, as circuitry that cooperates with the processor to perform various steps or functions.
In addition, some of the present application may be implemented as a computer program product, such as computer program instructions, which when executed by a computer, may invoke or provide methods and/or techniques in accordance with the present application through the operation of the computer. Program instructions which invoke the methods of the present application may be stored on a fixed or removable recording medium and/or transmitted via a data stream on a broadcast or other signal-bearing medium and/or stored within a working memory of a computer device operating in accordance with the program instructions. An embodiment according to the present application comprises an apparatus comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to perform a method and/or a solution according to the aforementioned embodiments of the present application.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it is obvious that the word "comprising" does not exclude other elements or steps, and the singular does not exclude the plural. A plurality of units or means recited in the apparatus claims may also be implemented by one unit or means in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.
Claims (11)
1. A method for identifying a target detection object based on a photoelectric sensor, the method comprising:
taking a first path of electric signal obtained by a photoelectric sensor as measured data, and processing a second path of electric signal obtained by the photoelectric sensor to obtain a time-base signal;
processing the measured data according to the time base signal and a Kalman filtering algorithm to obtain observation data;
determining a digital signal of a target detection object according to the measured data and the observation data;
and identifying the category of the target detection object according to the digital signal.
2. The method according to claim 1, characterized in that it comprises:
and converting an optical signal received by the photoelectric sensor when the target detection object is measured into an electric signal, and dividing the electric signal into a first path of electric signal and a second path of electric signal.
3. The method according to claim 1 or 2, wherein the step of obtaining a time-based signal after processing a first path of electric signal obtained by a photoelectric sensor as measured data comprises:
transmitting the first path of electric signal obtained by the photoelectric sensor to a control center of the photoelectric sensor as measured data;
and performing square wave shaping on the second path of electric signal obtained by the photoelectric sensor to obtain a time-base signal.
4. The method of claim 3, wherein squaring the second electrical signal obtained by the photosensor to obtain a time-based signal comprises:
and performing square wave shaping on the second path of electric signals obtained by the photoelectric sensor to filter useless electric signals in a time sequence, wherein the filtered electric signals are time-base signals, and the useless electric signals comprise electric signals obtained when the second path of electric signals are switched off by the emitted light of the photoelectric sensor.
5. The method of claim 1, wherein determining a digital signal of a target test object from the measured data and the observed data comprises:
determining a dynamic weight fitting data curve of the attribution type of the target detection object according to the measured data, the observation data and a corresponding fitting algorithm;
and carrying out binarization processing on the dynamic weight fitting data curve to obtain a corresponding digital signal.
6. The method of claim 1, wherein the photosensor comprises a transmitter and a receiver, and identifying the class of the target detection object from the digital signal comprises:
and judging whether the sensitization quantity sent by the emitter is received by the receiver or not according to the digital signal, if so, identifying the category of the target detection object shielding the signal sent by the emitter according to the times of receiving the sensitization signal in a period.
7. The method of claim 1, wherein processing the measured data according to the time-based signal and a kalman filter algorithm to obtain observed data comprises:
determining a Kalman gain based on the covariance of the state of the Kalman filter used and the covariance of the state at the present time determined by the time-based signal;
and calculating an optimal estimation value of the measured data according to the measured data and the Kalman gain, and obtaining observation data according to the optimal estimation value.
8. The method of claim 6, wherein the photosensor is applied to a gate, the method comprising:
if the number of times that the receiver receives the photosensitive signals in a period is larger than a first threshold value, outputting a signal of no action to the gate by the photoelectric sensor;
if the number of times that the receiver receives the photosensitive signals in a period is smaller than a second threshold value, the photoelectric sensor outputs signals of action to the gate;
if the number of times of receiving the light sensing signal in one period by the receiver is between the second threshold value and the first threshold value, the operation state of the output of the photoelectric sensor is maintained.
9. An apparatus for identifying a target detection object based on a photosensor, the apparatus comprising:
the acquisition device is used for taking the first path of electric signals obtained by the photoelectric sensor as measured data, and processing the second path of electric signals obtained by the photoelectric sensor to obtain time base signals;
the processing device is used for processing the actually measured data according to the time base signal and a Kalman filtering algorithm to obtain observed data;
the determining device is used for determining a digital signal of a target detection object according to the measured data and the observed data;
and the identification device is used for identifying the category of the target detection object according to the digital signal.
10. An apparatus for identifying a target detection object based on a photosensor, the apparatus comprising:
one or more processors; and
a memory storing computer readable instructions that, when executed, cause the processor to perform the operations of the method of any of claims 1 to 8.
11. A computer readable medium having computer readable instructions stored thereon which are executable by a processor to implement the method of any one of claims 1 to 8.
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