JP2000338234A - Monitoring system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a monitoring system that is capable of automatic monitoring by automatically identifying whether a reflection object is to enter according to the traveling speed and the changing speed of the reflection object that has been digitized and then what the entering object is if the reflection object is to enter. SOLUTION: Position data 30 for indicating the position change in an entering object is obtained from a Doppler signal obtained from the entering object, the traveling speed of the entering object is digitized from an amount of phase change 31 per unit time, and the speed change of the entering object is digitized from the irregularity, thus automatically identifying what the entering object is from the numeric value using detection parts 1 that is installed at a monitoring field, thus eliminating the need for a monitoring person to monitor the Doppler signal from the control parts 1 and forming a wide range of monitoring system using the plurality of detection parts 1. Also, only identification result information can be outputted from the detection parts 1 for easily transmitting to a remote area by a wireless line and safely monitoring a dangerous region. Also, the identification result can be transmitted to the remote area by a wireless signal for displaying and giving an alarm.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a surveillance system which irradiates a surveillance area with, for example, a radar beam and identifies the presence of an intruder and the identity of the intruder from a change in Doppler frequency of a reflected signal.

[0002]

2. Description of the Related Art FIG. 16 is a diagram for explaining a conventional monitoring system of this type. In the drawing, reference numeral 1A denotes a detector for irradiating a radar beam and receiving a reflected wave reflected from a monitoring area 10. 2 is a power supply section, 3 is a display section, 4 is a listening section, 1
0 is a monitoring area, 11 is an intruder who has entered the monitoring area 10,
Reference numeral 12 denotes a tree existing in the monitoring area.

Next, the operation will be described. A radar beam is emitted from the detection unit 1A toward the monitoring area 10, and a reflected wave reflected on the monitoring area 10 is received. Monitoring area 1
If there is only a stationary object at 0, the frequencies of the transmitted wave and the received wave do not change. However, if there is a moving object such as the intruder 11 in the monitoring area 10, the received wave undergoes frequency shift due to the Doppler effect. Thus, a signal having a frequency different from that of the transmission wave is obtained. Therefore, by canceling the transmitted wave component from the received wave, a signal representing a frequency shift (hereinafter, abbreviated as a Doppler signal) can be extracted.

[0004] The Doppler signal differs depending on the difference of an intruding object, and since this Doppler signal is a signal in a frequency band that can be heard by a human ear, its waveform is displayed on the display unit 3 and monitored through the listening unit 4. A voice signal is sent to a member (not shown), and the observer analyzes the voice signal from the listening section 4 and the waveform displayed on the display section 3 to determine what the intruding object is (for example, whether a person is a person). Vehicle).

[0005]

A conventional monitoring system of this kind is configured as described above, and therefore, a monitoring person who can analyze a waveform and an audio signal to determine what an intruding object is always required. become. That is, since only the Doppler signal is transmitted as data from the detection unit, knowledge and experience are required for the analysis, and it is difficult to make an accurate determination and automatic monitoring cannot be performed. Since a large amount of data is output, one monitoring unit is basically required for one detection unit, and wide area monitoring is difficult. Further, there has been another problem that remote monitoring is difficult because data transmission by wireless signals becomes difficult.

The present invention has been made to solve such a problem, and has as its object to provide a monitoring system capable of automatic monitoring.

[0007]

SUMMARY OF THE INVENTION A monitoring system according to the present invention transmits and receives electromagnetic waves to and from a monitoring area, and detects the presence of an intruding object from a signal indicating a Doppler frequency shift received by a reflected wave (hereinafter referred to as a Doppler signal). And a monitoring system for identifying what is the intruder, means for converting the Doppler signal into phase data representing a change in the position of the reflecting object, measuring a phase change amount per unit time from the phase data, and Means for quantifying the moving speed, means for measuring the irregularity of the phase change from the phase data, and for quantifying the speed change of the reflective object, Is characterized by being provided with means for automatically identifying whether or not is an intruder, and in the case of an intruder, what the intruder is. Further, the method of measuring the irregularity of the phase change from the phase data is characterized in that the irregularity of the phase change is measured by the sum of errors (sum of squares) between the phase data and a polynomial approximation curve of the phase data. Further, the method of measuring the irregularity of the phase change from the phase data is characterized by measuring the sum of errors (linear prediction errors) between the phase data and a linear prediction curve of the phase data.

In a surveillance system for transmitting and receiving electromagnetic waves to and from a monitoring area to identify the presence of an intruding object and the type of intruding object from the Doppler signal, means for converting the Doppler signal into amplitude data representing its level, Means for converting the amplitude data into spectral data representing the level of each frequency, whether or not the reflective object is an intruding object by digitizing the speed and velocity distribution of the reflecting object from the spectral data, if the intruding object It is characterized by having means for automatically identifying what the intruder is. Further, the speed of the reflecting object is quantified from the frequency of the maximum output of the spectrum data, and the speed distribution of the reflecting object is obtained by quantifying the low frequency occupancy and the spectrum spread rate.

In a monitoring system for transmitting and receiving electromagnetic waves to and from a monitoring area to identify the presence of an intruding object and the type of the intruding object from the Doppler signal, means for converting the Doppler signal into amplitude data representing its level, Means for converting the amplitude data into spectrogram data in which the spectrum data is arranged in the order of the start of a time window by using a short-time Fourier transform, and from the spectrogram data, the speed of the reflecting object, the time change of the speed, the speed distribution, and the time change of the speed distribution Is converted into a numerical value, and means for automatically identifying whether or not the reflecting object is an intruding object, and if the reflecting object is an intruding object, what the intruding object is. Further, the speed of the reflecting object is calculated from the average value of the peak frequency for each time window within the measurement time. Further, the time change of the speed of the reflecting object is measured by a sum (error sum of squares) of an error between a time change curve of the peak frequency for each time window in the measurement time and the polynomial approximation curve. I do. Further, the velocity distribution of the reflecting object is obtained by numerically calculating the low frequency occupancy and the spread of the spectrum, and the low frequency occupancy is a low frequency level with respect to the sum of the levels of all frequencies of the spectrum for each different time window. Is determined from the start of measurement to the end of the measurement, and is quantified by the average value.The spread of the spectrum is obtained by calculating the spread of the spectrum for each different time window from the start of the measurement to the end of the measurement. , And digitized by the average value. In addition, as a method of numerically expressing the time change of the velocity distribution, a time change curve of the spread is obtained from the spread of the spectrum for each different time window, and the numerical value is obtained by summing an error between the curve and the polynomial approximation curve (square sum error). It is characterized by doing. Further, the system is characterized in that the identification result is transmitted to a remote place by a radio signal, and is displayed at the remote place to issue an alarm.

[0010]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a diagram for explaining an embodiment of a monitoring system according to the present invention.
a, 1-b, 1-c are a detection unit, 2 is a power supply unit, 3
Is a display unit, 5 is a communication unit, 6 is an alarm unit, 10-a, 10-
Reference numerals b and 10-c denote monitoring areas to be irradiated with the radar beam, 11 denotes an intruder who has entered the monitoring area 10-b, 12
Is a tree existing in the monitoring area 10-b, and 22 is a radio signal for transferring the identification result. In the system shown in FIG. 1, components other than the detection unit 1 are installed in a safe place away from the monitoring area.

FIG. 2 is a block diagram showing the configuration of the detecting unit 1. In the figure, reference numeral 101 denotes a radar signal transmitting / receiving unit for transmitting / receiving a radar beam 20, and 102 denotes a Doppler signal 21 output from the radar signal transmitting / receiving unit 101. A signal processing identification unit 103 that performs signal processing and automatically identifies the presence or absence of an intruding object and what the intruding object is, 103 transmits a determination result from the signal processing identifying unit 102 to the remotely installed communication unit 5 by a wireless signal 22. A wireless communication unit 104 is a power supply unit, and 105 is a control unit that controls the entire detection unit 1. In addition, a secondary battery or a solar battery is used for the power supply unit 104 in consideration of the fact that the detection unit 1 is installed in an unmanned place.

Next, the operation will be described. The detection unit 1 of the monitoring system according to the present invention includes not only a radar signal transmission / reception function for obtaining a Doppler signal like the detection unit 1A of the conventional device, but also a signal processing identification unit 102 as shown in FIG. In addition, a function is provided for automatically identifying the presence or absence of an intruding object and what the intruding object is based on the Doppler signal received by the radar signal transmitting / receiving unit 101.

FIG. 3 shows the radar signal transmitting / receiving unit 1 shown in FIG.
FIG. 2 is a block diagram showing an embodiment of the configuration of FIG. The transmission signal 23 output from the transmission device 201 is
2 and is radiated as a transmission wave 24 to the monitoring area 10. Further, the reception wave 25 from the monitoring area 10 is received again by the antenna 202, and is received as a reception signal 26 by the reception device 20.
3 is input. Here, if there is a moving object in the monitoring area 10, the received wave 25 undergoes frequency shift due to the Doppler effect, and the received signal 26 becomes a signal having a different frequency from the transmission signal 23. The transmission signal 23 is directly input from the transmission device 201 to the reception device 203, and the transmission signal 23 is canceled from the reception signal 26 to obtain the Doppler signal 21.
Output only

In the embodiment shown in FIG. 3, as described later, the identification of an intruding object is performed by signal processing using phase data.
The phase of the I-channel data obtained by phase-detecting the reception signal 26 with the transmission signal 23 from the transmission device 201 and the phase of the transmission signal 23 from the transmission device 201 are set to 90 degrees. It is configured to output a Doppler signal 21 composed of Q-channel data obtained by phase-detecting a received signal 26 with a different signal. Doppler signal 2 output from radar signal transmitting / receiving section 101
1 is input to the signal processing identification unit 102, and from the Doppler signal 21, what the intruder is is identified.

Next, a description will be given of an operation for identifying an intruding object in the present embodiment. In the present embodiment, the intruder is identified by focusing on the fact that the moving speed and the speed change are different depending on the difference of the intruder. For example, comparing the case where the intruding object entering the monitoring area 10 is a person and the case of a vehicle, the moving speed is generally slow in the case of the intruder 11, and the speed changes every time the foot touches the ground. However, in the case of a vehicle, its moving speed is fast, and it accelerates and decelerates smoothly,
It can be seen that the speed change also changes smoothly. Therefore, in the present embodiment, the moving speed of the intruding object is measured by the amount of phase change per unit time, and the irregularity of the position change is captured by the speed change, and this is measured by the irregularity of the phase change. And

FIGS. 4 to 6 are diagrams for explaining the measurement of the amount of phase change per unit time and the measurement of the irregularity of the phase change performed by the signal processing identification unit 102.
As shown in the figure, these measurements are performed by the radar signal transmitting / receiving unit 10.
In order to analyze the Doppler signal 21 output from 1 and numerically characterize the characteristic, the signal processing identifying unit 102 includes an arithmetic unit and software.

The signal processing identifying unit 102 first converts the Doppler signal 21 into phase data 30 indicating a change in the position of an intruding object as shown in the upper diagram of FIG. For example, assuming that the intruder 11 moves with respect to the detection unit 1 as shown in the lower diagram of FIG. 4, the intruder 11 is present at the point of the initial phase value ra at the start of measurement ta. When the intruder 11 comes closest to the detection unit 1 (at time tm), the maximum value rm is obtained. After changing the moving direction at time tm, the phase value decreases. At the end of measurement, the phase value becomes rb at time tb. Let's say in this case,
The moving speed of the intruding object is (final phase value rb−initial phase value r
a) / (measurement time), and it is possible to obtain from the moving speed data whether the intruding object is approaching or moving away from the detection unit 1 and at what speed the moving object can move.

Next, the signal processing identification unit 102 measures the irregularity of the phase change from the phase data shown in the upper diagram of FIG. As a method of digitizing the irregularity of the phase change, for example, a method of obtaining a sum-of-squares error 33 with a polynomial approximation curve 32 as shown in FIG. 5 or a method of obtaining a linear prediction curve 34 as shown in FIG. A method of obtaining the prediction error 35 can be used. The sum-of-squares error 33 is the sum of the approximation errors between the phase data 30 and the approximation curve 32 of the polynomial, and the linear prediction error 35 is the linear prediction curve obtained by using the phase data 30 and the linear prediction method. These are the sums of the approximation errors with respect to 34, and these errors increase when the speed change of the approaching object has a large variation, because the position change of the approaching object viewed from the detection unit 1 becomes large. Further, since the error becomes small when the intruding object has a constant speed change, the speed change can be quantified from the position change of the intruding object.

That is, as shown in FIG. 4 to FIG. 6, when the intruder is the intruder 11, the signal processing identifying unit 102 does not move so quickly, and the sum of squares error 33 and the linear prediction error 35 Since it has occurred, it can be identified that the intruding object is a person, that is, the intruder 11, and conversely, if the moving speed is high and the sum of squares error 33 or the linear prediction error 35 is small, the intruding object can be identified as a vehicle. The information of the identification result is output to the wireless communication unit 103. Then, the wireless communication unit 103 transmits the information of the identification result to the communication unit 5 by the wireless signal 22. The communication unit 5 that has received this information displays the identification result on the display unit 3 and, if necessary, an alarm unit. An alarm is issued from 6.

As described above, the monitoring system of this embodiment obtains the phase data indicating the position change of the intruding object from the Doppler signal obtained from the intruding object, and obtains the phase change amount 31 of the intruding object from the phase change amount 31 per unit time. The moving speed is converted into a numerical value, and the speed change of the intruding object is converted into a numerical value from the irregularity of the phase change, and the detecting unit 1 installed at the monitoring site automatically identifies what the intruding object is from these numerical values. With this configuration, it is not necessary for the observer to monitor the Doppler signal from the detection unit 1, and a wide-range monitoring system can be formed using the plurality of detection units 1. Further, since only information of the identification result is output from the detection unit 1, the information can be easily transmitted to a remote place via the wireless line 22, and the dangerous area can be safely monitored.

FIGS. 7 to 10 are views for explaining a second embodiment of the present invention. In the above-described embodiment, the moving speed of the intruding object is quantified from the amount of phase change per unit time, and the speed change of the intruding object is quantified from the irregularity of the phase change. Is automatically identified. However, in this method, for example, as shown in FIG. 1, when a tree 12 exists in the monitoring area 10-b, and a branch of the tree 12 swings by the wind,
Since the reflected wave reflected from the tree 12 becomes a Doppler signal, the tree 12 may be erroneously identified as an intruding object. In order to prevent such an identification error and to accurately identify what an intruding object is, it is necessary to make a judgment based on the speed information of each part of the intruding object. Therefore, in the second embodiment, the signal processing identification unit 102 performs signal processing using a so-called filter bank, and digitizes the velocity and velocity distribution of the intruding object from the Doppler signal 21 to determine what the intruding object is. It was configured to automatically identify.

That is, in the receiving device 203, the received signal 2
6 is phase-detected by the transmission signal 23, and the signal subjected to the detection processing is output as the Doppler signal 21. Signal processing identification unit 102
Then, the Doppler signal 21 is converted into amplitude data 36 as shown in FIG. 7, and a narrow band LPF (low-pass filter) 37a having a different pass band frequency as shown in FIG.
And a BPF (Band Pass Filter) 37b. FIG. 9 shows the output of each filter,.
In other words, which frequency band the signal is strong is obtained by the sum of the respective areas 38, and this is rearranged in the order of the filter, as shown in the lower diagram of FIG. 9 (referred to as spectrum data). This is normalized so that the characteristics of the intruder can be easily extracted, and the speed and the velocity distribution of the intruder are obtained from the normalized spectrum data as shown in FIG.

That is, as shown in the upper diagram of FIG. 10, the speed of the intruding object is detected by obtaining the pass band frequency of the filter (BPF in the embodiment) having the maximum output of 40 from the normalized spectrum, and for example, the lowest pass frequency is obtained. The ratio of the output value from the band-pass filter (referred to as low frequency occupancy ratio 41) is obtained, and the sum of the filter outputs excluding the maximum output 40 is obtained as shown in the lower diagram of FIG. Become That is, if the Doppler signal captures tree 12 as described above,
Since the low-frequency occupancy 41 increases, the size of the low-frequency occupancy can be automatically distinguished from the case where a person or a vehicle enters, and in addition to the normal walking speed when the entry is a person,
Since the Doppler signal is composed of a plurality of speeds different from the walking speed, such as the speed of waving the hand and the speed of shaking the head, the spreading rate increases, and when the intruding object is a vehicle, the Doppler frequency does not spread, Therefore, by obtaining information on the speed and the speed distribution as described above, it is possible to relatively accurately identify what the intruder is.

FIGS. 11 to 15 are views for explaining a third embodiment of the present invention. In the above-described second embodiment, the signal processing identification unit 102 performs signal processing using a filter bank, obtains the speed and speed distribution of the intruding object, and automatically identifies what the intruding object is. In this method, when the speed of an intruding object greatly changes during measurement, a speed change component is added to the normalized spectrum, so that an accurate speed distribution cannot be extracted. Therefore, in the third embodiment of the present invention, the signal processing using the short-time Fourier transform is performed by the signal processing identification unit 102, and the velocity of the intruding object, the time change of the velocity, the velocity distribution, and the velocity distribution are calculated from the Doppler signal 21. The four pieces of information on the time change were quantified to automatically identify what the intruder was.

That is, as shown in FIG. 11, the same amplitude data 36 as in the second embodiment is obtained from the radar signal transmission / reception unit 101, and this amplitude data 36 is obtained in an arbitrary fixed time window 51 from the measurement start time ta. Cut out Fourier transform. Next, the time window start time is delayed by an arbitrary overlap 52 (ts2), cut out with a new time window and subjected to Fourier transform, and this is repeated until the end of the time window becomes the end of measurement. Then, by arranging the obtained Fourier transform outputs obtained in different time windows in the order of the time window start time, a spectrogram as shown in FIG. 12 is obtained. From the spectrogram, information on the speed of the intruding object, the time change of the speed, the speed distribution, and the time change of the speed distribution are extracted.

That is, since the speed of the intruding object is proportional to the speed of the peak frequency, the speed can be quantified by obtaining the average value of the peak frequency for each time window within the measurement time. Further, the time change of the speed can be obtained from the time change 53 of the peak frequency because the speed is proportional to the peak frequency. As a method of quantifying the time change of the speed from the time change 53 of the peak frequency, for example, As shown in FIG. 13, a polynomial approximation curve 54 of the peak frequency temporal change 53 is obtained, and a numerical value can be obtained by summing an error between the polynomial approximate curve 54 and the peak frequency temporal change 53 (square sum error 55). Then, the sum-of-squares error 55 increases as the time change of the speed of the intruding object is complicated and cannot be approximated, and the sum-of-squares error decreases if the speed and acceleration of the intruding object are constant within the identification processing time.

The following method has been devised as a method of digitizing the velocity distribution. For example, the low frequency occupancy is shown in FIG.
As shown in (1), the ratio of the sum of the levels in the low frequency range to the sum of the levels in all the frequencies of the spectrum for each different time window is obtained. Then, this ratio is obtained from the start of measurement to the end of measurement, and the low frequency occupancy 56 is calculated by obtaining the average value. The low frequency occupancy 56 is used to prevent the trees 12 and the like existing in the monitoring area 10 from being erroneously recognized as intruders as described above. As shown in FIG. 14, the spread of the spectrum at each different time window is determined by detecting the spread of the spectrum at a predetermined level or less (h) from the peak frequency 57 and defining the spread as a spread 58 at the start of measurement. From the measurement to the end of the measurement, and the average value is obtained to quantify the spread of the spectrum. This spread of the spectrum identifies whether the intruding object has a different moving speed depending on each part, such as a person, as described above, or whether the entire object has the same moving speed, such as a vehicle. Used for

The following method has been devised as a method for quantifying the time change of the velocity distribution. As shown in FIG.
From the spread of the spectrum for each different time window, a time change curve 59 of the spread is obtained. Then, the polynomial approximation curve 60 is obtained from the time change curve 59 of the spread, and the sum of errors between them, that is, the sum of squares error 61 is obtained and quantified.

As described above, in the third embodiment of the present invention, even when the measurement time is the same, the time from the start of the time window to the end of the time window is shortened, so that the intruder greatly changes the speed during the measurement. In this case, the effect of the speed change component added to the speed distribution can be suppressed, and the identification processing time can be shortened.This can also suppress the effect of the speed change component added to the speed distribution, and more accurate speed distribution data can be extracted. It becomes possible. In addition, since the time change of the speed and the time change of the speed distribution can be added to the parameter for determining what the intruding object is, more accurate identification can be performed.

Although the above embodiment has been described as a system using a radar beam, it goes without saying that the present invention can be applied to a system using a sound wave and the like. In the above-described embodiment, a system in which the identification result is wirelessly transmitted from the detection unit 1 is described. However, it is needless to say that the detection unit 1 itself may automatically generate an alarm based on the identification result.

[0031]

As described above, the monitoring system according to the present invention is provided with a signal processing identifying section in the detecting section, and converts the Doppler signal into phase data and amplitude data to perform signal processing, thereby numerically characterizing an intruding object. Since it is configured to automatically identify what the intruding object is based on the data, accurate identification can be performed. In addition, it is not necessary for the observer to monitor the detection unit, and a plurality of detection units can be installed to perform wide area monitoring. Since only the identification result is output from the detection unit, there is an effect that a system capable of remote monitoring by wireless can be provided.

[Brief description of the drawings]

FIG. 1 is a diagram illustrating an embodiment of a monitoring system according to the present invention.

FIG. 2 is a block diagram illustrating a configuration of a detection unit 1.

FIG. 3 is a block diagram illustrating an embodiment of a configuration of a radar signal transmission / reception unit 101.

FIG. 4 is a diagram for explaining measurement of a phase change amount and measurement of irregularity of a phase change.

FIG. 5 is a diagram for explaining measurement of a phase change amount and measurement of irregularity of a phase change.

FIG. 6 is a diagram for explaining measurement of a phase change amount and measurement of irregularity of a phase change.

FIG. 7 is a diagram for explaining a second embodiment of the present invention.

FIG. 8 is a diagram for explaining a second embodiment of the present invention.

FIG. 9 is a diagram for explaining a second embodiment of the present invention.

FIG. 10 is a diagram for explaining a second embodiment of the present invention.

FIG. 11 is a diagram for explaining a third embodiment of the present invention.

FIG. 12 is a diagram for explaining a third embodiment of the present invention.

FIG. 13 is a diagram for explaining a third embodiment of the present invention.

FIG. 14 is a diagram for explaining a third embodiment of the present invention.

FIG. 15 is a diagram for explaining a third embodiment of the present invention.

FIG. 16 is a diagram for explaining this type of conventional monitoring system.

[Explanation of symbols]

 References 1-a, 1-b, 1-c Detecting unit 2 Power supply unit 3 Display unit 4 Listening unit 5 Communication unit 6 Alarm unit 10-a, 10-b, 10-c Monitoring area 11 Intruder 12 Tree 22 Radio signal Reference Signs List 101 radar signal transmitting / receiving unit 102 signal processing identification unit 103 wireless communication unit 104 power supply unit 105 control unit 201 transmitting device 202 antenna 203 receiving device

 ──────────────────────────────────────────────────続 き Continuing on the front page (72) Inventor Hiroki Sugawara 5-1-1 Shimorenjaku, Mitaka City, Tokyo Japan Radio Inside (72) Inventor Daisuke Akamine 5-1-1 Shimorenjaku, Mitaka City, Tokyo Japan Radio In-house F-term (reference) 2F073 AA40 AB01 BB01 BC02 CC03 CC08 CD00 DD02 DE06 EE11 EF07 FF01 FG04 FG20 GG01 GG04 GG07 GG09 2G005 DA04 5C084 AA01 AA06 BB31 DD07 GG17 GG80 5J070 AAA AH AAH A31H AH40 AH50 AK14 AK31 BA01 BG01 BG28 BG40

Claims (11)

[Claims] 1. A monitoring system for transmitting and receiving an electromagnetic wave to and from a monitoring area and identifying the presence of an intruding object and what the intruding object is from a signal (hereinafter referred to as a Doppler signal) indicating a Doppler frequency shift received by a reflected wave. In, means for converting the Doppler signal into phase data representing a change in the position of a reflecting object, means for measuring the amount of phase change per unit time from the phase data and quantifying the moving speed of the reflecting object, from the phase data Means for measuring the irregularity of the phase change and quantifying the change in the speed of the reflective object, based on the digitized moving speed and speed change of the reflective object, whether or not the reflective object is an intruding object; A means for automatically identifying what the intruder is, a surveillance system comprising: 2. The monitoring system according to claim 1, wherein the method of measuring the irregularity of the phase change from the phase data comprises summing an error between the phase data and a polynomial approximation curve of the phase data. A surveillance system characterized by measuring the sum of squared errors. 3. The monitoring system according to claim 1, wherein the method of measuring the irregularity of the phase change from the phase data comprises summing an error between the phase data and a linear prediction curve of the phase data. A monitoring system characterized in that measurement is performed using linear prediction errors). 4. A monitoring system for transmitting and receiving electromagnetic waves to and from a monitoring area to identify the presence of an intruding object and the type of intruding object from a Doppler signal, wherein the means for converting the Doppler signal into amplitude data representing its level; Means for converting the amplitude data into spectral data representing a level for each frequency, whether or not the reflective object is an intruding object by digitizing the speed and velocity distribution of the reflecting object from the spectral data, if the intruding object A surveillance system comprising means for automatically identifying what the intruder is. 5. The monitoring system according to claim 4, wherein the speed of the reflecting object is quantified from a frequency of the maximum output of the spectrum data, and the speed distribution of the reflecting object is a numerical value representing a low frequency occupancy and a spectrum spread rate. A surveillance system characterized in that it is sought after. 6. A monitoring system for transmitting and receiving electromagnetic waves to and from a monitoring area to identify the presence of an intruding object and what the intruding object is from a Doppler signal, comprising: means for converting the Doppler signal into amplitude data representing its level; Means for converting the amplitude data into spectrogram data in which the spectral data is arranged in the order of the start of a time window by using a short-time Fourier transform; from the spectrogram data, the speed of the reflecting object, the time change of the speed, the speed distribution, and the time of the speed distribution Means for quantifying the change and automatically identifying whether or not the reflecting object is an intruding object, and if the reflecting object is an intruding object, automatically identifying the intruding object. 7. The monitoring system according to claim 6, wherein the speed of the reflection object is calculated from the average value of the peak frequency for each time window within the measurement time. 8. The monitoring system according to claim 6, wherein the time change of the speed of the reflecting object is obtained by calculating an error between the time change curve of the peak frequency for each time window in the measurement time and the polynomial approximation curve. A monitoring system characterized by measuring the sum (sum of squared errors). 9. The monitoring system according to claim 6, wherein the velocity distribution of the reflecting object is obtained by quantifying the low frequency occupancy and the spread of the spectrum, and the low frequency occupancy is different for each different time window. The ratio of the sum of the low-frequency levels to the sum of the levels of all the frequencies of the spectrum is determined from the start to the end of the measurement, and is quantified by the average value.The spread of the spectrum is the spectrum for each different time window. A monitoring system characterized in that the spread of each is obtained from the start to the end of each measurement, and is quantified by the average value. 10. The monitoring system according to claim 6, wherein the time change of the velocity distribution is digitized by obtaining a time change curve of the spread from the spread of the spectrum for each different time window, A monitoring system characterized in that a numerical value is expressed by a sum of errors between the two (sum of square errors). 11. The monitoring system according to claim 1, wherein the identification result is transmitted to a remote place by a radio signal, and is displayed at the remote place to issue an alarm. A monitoring system characterized by the following.