WO2015083348A1 - 信号処理装置 - Google Patents
信号処理装置 Download PDFInfo
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- WO2015083348A1 WO2015083348A1 PCT/JP2014/005930 JP2014005930W WO2015083348A1 WO 2015083348 A1 WO2015083348 A1 WO 2015083348A1 JP 2014005930 W JP2014005930 W JP 2014005930W WO 2015083348 A1 WO2015083348 A1 WO 2015083348A1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/50—Systems of measurement based on relative movement of target
- G01S13/52—Discriminating between fixed and moving objects or between objects moving at different speeds
- G01S13/56—Discriminating between fixed and moving objects or between objects moving at different speeds for presence detection
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/28—Details of pulse systems
- G01S7/285—Receivers
- G01S7/292—Extracting wanted echo-signals
- G01S7/2921—Extracting wanted echo-signals based on data belonging to one radar period
- G01S7/2922—Extracting wanted echo-signals based on data belonging to one radar period by using a controlled threshold
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/28—Details of pulse systems
- G01S7/285—Receivers
- G01S7/292—Extracting wanted echo-signals
- G01S7/2923—Extracting wanted echo-signals based on data belonging to a number of consecutive radar periods
- G01S7/2927—Extracting wanted echo-signals based on data belonging to a number of consecutive radar periods by deriving and controlling a threshold value
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/35—Details of non-pulse systems
- G01S7/352—Receivers
- G01S7/354—Extracting wanted echo-signals
Definitions
- the present invention generally relates to a signal processing device, and more particularly to a signal processing device that performs signal processing of a sensor signal from a sensor that receives a radio signal reflected by an object.
- This lighting system includes an object detection device 101 including a sensor 110 that detects the presence or absence of a detection target in a detection area and outputs a sensor signal, and a lighting fixture 102 whose lighting state is controlled by the object detection device 101. I have.
- the sensor 110 transmits the millimeter wave toward the detection area, receives the millimeter wave reflected by the detection object moving in the detection area, and determines the frequency difference between the transmitted millimeter wave and the received millimeter wave.
- This is a millimeter wave sensor that outputs a sensor signal having a corresponding Doppler frequency.
- the object detection apparatus 101 divides a sensor signal output from the sensor 110 into a plurality of frequency band signals and amplifies the signal for each frequency band, and compares the output of the amplification circuit 111 with a predetermined threshold to detect the object. And a determination unit 112 that determines whether or not an object exists. Further, the object detection apparatus 101 includes an illumination control unit 113 that controls the lighting state of the lighting fixture 102 according to the determination result of the determination unit 112.
- the object detection apparatus 101 includes a frequency analysis unit 114 that detects the intensity of each sensor signal output from the sensor 110 for each frequency.
- the object detection apparatus 101 includes a noise removal unit (noise determination unit 115 and switching circuit 116) that reduces the influence of noise of a specific frequency that is constantly generated using the analysis result of the frequency analysis unit 114.
- the frequency analysis unit 114 an FFT (Fast Fourier Transform) analyzer is used.
- the determination unit 112, the illumination control unit 113, and the noise removal unit are included in a control block 117 whose main configuration is a microcomputer.
- the amplifier circuit 111 constitutes a signal processing unit that outputs sensor signals for each predetermined frequency band. Reference 1 describes that the signal processing unit may be configured using an FFT analyzer, a digital filter, or the like.
- the amplifier circuit 111 includes a plurality of amplifiers 118 using operational amplifiers. By adjusting various parameters of the circuits constituting each amplifier 118, it is possible to set a frequency band for amplifying a signal by each amplifier 118. It has become. That is, each amplifier 118 also functions as a band-pass filter that passes a signal in a specific frequency band. Thus, in the amplifier circuit 111, the sensor signal is divided into a plurality of frequency band signals by a plurality of amplifiers 118 connected in parallel, and each frequency band signal is amplified by each amplifier 118 and output individually. .
- the determination unit 112 A / D converts the output of the amplifier 118 into a digital value, and has a comparator 119 for comparing with a predetermined threshold value for each amplifier 118, and determines the presence or absence of the detection target.
- the threshold is individually set for each pass band (that is, for each amplifier 118), and outputs an H level signal when the output of the amplifier 118 is outside the range defined by the threshold.
- Vpp ini is the maximum value of the peak-to-peak Vpp of the output value V of each amplifier 118 measured within a certain time in a state where there is no reflection of electromagnetic waves such as an anechoic chamber.
- Vavg is an average value Vavg of the output value V.
- the determination part 112 has the OR circuit 120 which takes the OR of each comparison result. If there is at least one high level (H level) signal, the logical sum circuit 120 outputs a detection signal indicating a “detection state” in which a detection target exists. On the other hand, if all are at the low level (L level), the OR circuit 120 outputs a detection signal indicating a “non-detection state” in which no detection target exists.
- the value of the detection signal is, for example, “1” in the detection state and “0” in the non-detection state.
- the noise removing unit determines from the output of the frequency analyzing unit 114 whether or not there is a noise having a specific frequency that is constantly generated, and each amplifier 118 for the determining unit 112 according to the determination result of the noise determining unit 115. And a switching circuit 116 for switching the output state.
- the switching circuit 116 includes switches 121 inserted between the amplifiers 118 of the amplifier circuit 111 and the comparators 119 of the determination unit 112, and all these switches 121 are turned on in the initial state. Then, each switch 121 is individually turned on / off by the output from the noise determination unit 115, so that the output of each amplifier 118 to the determination unit 112 is turned on and off individually. That is, in the switching circuit 116, the output of the amplifier 118 can be invalidated by turning off the switch 121 corresponding to the amplifier 118 of an arbitrary pass band by the output from the noise determination unit 115.
- the noise determination unit 115 the signal strength (voltage strength) of the sensor signal for each frequency (frequency component) output from the frequency analysis unit 114 is read and stored in a memory (not shown), and the stored data is used for steady state. The presence or absence of specific frequency noise is determined.
- the switch 121 between the amplifier 118 having the pass band including the noise and the determination unit 112 is turned off.
- the switching circuit 116 is controlled. Thereby, when the noise of a specific frequency has generate
- the ON / OFF state of the switch 121 is updated every time the noise determination unit 115 determines “normal”.
- the part excluding the sensor 110 and the illumination control unit 113 constitutes a signal processing device that performs signal processing on the sensor signal of the sensor 110 that is a millimeter wave sensor. It is done.
- this object detection device 101 for example, when used outdoors, an object other than the detection target may be erroneously detected as the detection target object due to the movement of the object other than the detection target (detection target). There was sex. In addition, it is also required to ensure the detection sensitivity of the detection object.
- the movement of an object other than the detection target includes, for example, rain, movement of a tree branch or leaf, movement of an electric wire, and the like.
- the present invention has been made in view of the above-mentioned reasons, and the object thereof is to reduce false detection caused by the movement of an object other than a detection target while balancing detection sensitivity improvement and false detection reduction. It is to provide a signal processing apparatus.
- the signal processing device of the present invention converts a sensor signal corresponding to the movement of the object output from a sensor that receives a radio signal reflected by the object into a signal in a frequency domain, and outputs the signal for each of a plurality of filter banks having different frequency bands.
- the object is detected by at least one of a frequency analysis unit that extracts the signal, a frequency distribution of a signal based on the signal for each of the plurality of filter banks, and a signal intensity component ratio based on the signal for each of the plurality of filter banks.
- a recognition unit that performs a recognition process, a level setting unit that sets a sensitivity level indicating a level of detection sensitivity of the object in the recognition process, and a parameter adjustment unit that changes a parameter for adjusting the detection sensitivity of the object in the recognition process
- the parameter adjustment unit includes the sensitivity level based on the sensitivity level set by the level setting unit. If high, setting the parameter so that the detection sensitivity of the object is increased, if the sensitivity level is low, wherein the detection sensitivity of the object to set the parameters to be lower.
- the signal processing apparatus has an effect that it is possible to reduce erroneous detection caused by the movement of an object other than the detection target while balancing the improvement in detection sensitivity and the reduction in erroneous detection.
- FIG. 2A to 2C are explanatory diagrams of a normalization unit of the signal processing device according to the embodiment.
- 3A to 3C are explanatory diagrams of a smoothing processing unit used in the signal processing device according to the embodiment.
- 4A to 4C are explanatory diagrams of an example of the background signal removal unit of the signal processing device according to the embodiment. It is explanatory drawing of the other examples of the background signal removal part of the signal processing apparatus in embodiment.
- 6A and 6B are explanatory diagrams of still another example of the background signal removal unit of the signal processing device according to the embodiment.
- FIG. 8A to 8C are explanatory diagrams of recognition processing by principal component analysis of the signal processing device according to the embodiment.
- 9A and 9B are explanatory diagrams of usage patterns of the sensor device according to the embodiment. It is a wave form diagram of a sensor signal from a radio wave sensor of a sensor device in an embodiment. It is explanatory drawing of the output of the normalization part of the signal processing apparatus in embodiment. It is a wave form diagram of the output signal of the signal processing apparatus in an embodiment. It is explanatory drawing of the usage condition of the sensor apparatus provided with the electromagnetic wave sensor and signal processing apparatus in embodiment.
- the signal processing device 2 is a device that performs signal processing on the sensor signal output from the radio wave sensor 1.
- FIG. 1 is a block diagram of a sensor device Se including a radio wave sensor 1 and a signal processing device 2.
- the radio wave sensor 1 transmits a radio wave having a predetermined frequency toward a detection area, receives a radio wave reflected by an object moving in the detection area, and determines a difference between the frequency of the transmitted radio wave and the received radio wave.
- a Doppler sensor that outputs a sensor signal having a corresponding Doppler frequency is used. Therefore, the sensor signal is an analog time axis signal corresponding to the movement of the object.
- the radio wave sensor 1 corresponds to a frequency difference between a transmitter that transmits a radio wave toward a detection area, a receiver that receives a radio wave reflected by an object in the detection area, and the received radio wave. And a mixer for outputting a frequency sensor signal.
- the transmitter includes a transmission antenna.
- the receiver includes a receiving antenna.
- the radio wave transmitted from the transmitter can be, for example, a millimeter wave having a predetermined frequency of 24.15 GHz.
- the radio wave transmitted from the transmitter is not limited to a millimeter wave but may be a microwave.
- the value of the predetermined frequency of the radio wave transmitted by the transmitter is an example, and is not limited to this value.
- the signal processing device 2 includes an amplification unit 3 that amplifies the sensor signal, and an A / D conversion unit 4 that converts the sensor signal amplified by the amplification unit 3 into a digital sensor signal and outputs the digital sensor signal.
- the amplifying unit 3 can be configured by an amplifier using an operational amplifier, for example.
- the signal processing device 2 includes a frequency analysis unit 5.
- the frequency analysis unit 5 converts the time domain sensor signal output from the A / D conversion unit 4 into a frequency domain signal (frequency axis signal), and the filter bank 5a (see FIG. 2A) having a different frequency band. It is extracted as a signal for each filter bank 5a in the group.
- the frequency analysis unit 5 sets a predetermined number (for example, 16) of filter banks 5a as a group of filter banks 5a, but this number is merely an example and is not intended to be limited to this number.
- the signal processing device 2 includes a normalization unit 6.
- the normalization unit 6 is the sum of the intensities of the signals extracted by the frequency analysis unit 5 or the sum of the intensities of the signals that have passed through a predetermined plurality of (for example, four on the low frequency side) filter banks 5a.
- the intensity of the signal that has passed through each is normalized and output as a normalized intensity.
- the signal processing device 2 includes a recognition unit 7 that performs a recognition process for detecting an object based on a frequency distribution determined from the normalized intensity for each filter bank 5a output from the normalization unit 6.
- the frequency analysis unit 5 described above has a function of converting a time domain sensor signal output from the A / D conversion unit 4 into a frequency domain signal by performing discrete cosine transform (DCT). .
- DCT discrete cosine transform
- each of the filter banks 5a has a plurality (five in the illustrated example) of frequency bins 5b.
- the frequency bin 5b of the filter bank 5a using DCT is also called a DCT bin.
- the resolution of each filter bank 5a is determined by the width of the frequency bin 5b ( ⁇ f in FIG. 2A).
- the number of frequency bins 5b in each of the filter banks 5a is an example, and is not limited to this number.
- the number of frequency bins 5b may be plural other than five, or may be one.
- the orthogonal transform for converting the sensor signal output from the A / D conversion unit 4 into a frequency domain signal is not limited to DCT, and may be, for example, fast Fourier transform (FFT).
- FFT fast Fourier transform
- the frequency bin 5b of the filter bank 5a using FFT is also referred to as FFT bin.
- the orthogonal transform for converting the sensor signal output from the A / D converter 4 into a frequency domain signal may be a wavelet transform (WT).
- the signal processing device 2 When each of the filter banks 5a has a plurality of frequency bins 5b, the signal processing device 2 preferably includes a smoothing processing unit 8 between the frequency analysis unit 5 and the normalization unit 6. .
- the smoothing processing unit 8 preferably has at least one of the following two smoothing processing functions.
- the first smoothing function is a function for smoothing the signal strength for each frequency bin 5b for each filter bank 5a in the frequency domain (frequency axis direction).
- the second smoothing processing function is a function of smoothing the signal strength for each frequency bin 5b in the time axis direction for each filter bank 5a.
- the function of smoothing the signal strength of each frequency bin 5b in the frequency domain for each filter bank 5a is defined as a first smoothing function.
- This first smoothing processing function can be realized by, for example, an average value filter, a weighted average filter, a median filter, a weighted median filter, and the like, and this first smoothing processing function is realized by an average value filter.
- FIG. 2A as shown in FIG. 3A, at time t 1, s1 strength of five frequency bins 5b signals in each of the first filter bank 5a counted in ascending order of frequency respectively, s2, s3 , S4, and s5.
- m 11 (s1 + s2 + s3 + s4 + s5) / 5 It becomes.
- the signals of the second filter bank 5a, the third filter bank 5a, the fourth filter bank 5a, and the fifth filter bank 5a are m 21 , m, respectively, as shown in FIGS. 2B and 3B. 31 , m 41 and m 51 .
- the signal of the jth filter bank 5a (j is a natural number) at time t i (i is a natural number) on the time axis is smoothed by the first smoothing function.
- the intensity of the processed signal is represented as m ji .
- the normalization unit 6 normalizes the intensity value of the signal that has passed through each of the filter banks 5a by the sum of the intensities of the signals that have passed through the plurality of predetermined filter banks 5a used in the recognition process in the recognition unit 7.
- the total number of the filter banks 5a in the frequency analysis unit 5 is 16, and the predetermined plurality of filter banks 5a used for the recognition process are the first to fifth five from the lowest frequency. It will be described as being only.
- the normalized strength of the signal strength m 11 passing through the first filter bank 5a at time t 1 is n 11 (see FIG. 2C)
- the normalization unit 6 extracts the intensity of the signal that has passed through each filter bank 5a, and passes through each filter bank 5a as the sum of these intensities. Normalize the strength of the signal.
- a function in which the smoothing processing unit 8 smoothes the intensity of the signal of each frequency bin 5b in the time axis direction for each filter bank 5a is a second smoothing processing function.
- the signals of the second filter bank 5a, the third filter bank 5a, the fourth filter bank 5a, and the fifth filter bank 5a are m 2 , m 3 , m 4, and m 5 , respectively.
- m 2 (m 20 + m 21 + m 22 ) / 3
- m 3 (m 30 + m 31 + m 32 ) / 3
- m 4 (m 40 + m 41 + m 42 ) / 3
- m 5 (m 50 + m 51 + m 52 ) / 3 It becomes.
- the signal of the nth (n is a natural number) filter bank 5a is smoothed by the first smoothing processing function, and further smoothed by the second smoothing processing function.
- the intensity of the processed signal is expressed as mn .
- the signal processing device 2 preferably includes a background signal estimation unit 9 and a background signal removal unit 10.
- the background signal estimation unit 9 estimates a background signal (that is, noise) included in the signal output from each filter bank 5a.
- the background signal removal unit 10 removes the background signal from the signal that has passed through each filter bank 5a.
- the signal processing device 2 has, for example, a first mode for estimating a background signal and a second mode for performing recognition processing as operation modes.
- the first time every predetermined time (for example, 30 seconds) counted by a timer. It is preferable that the mode and the second mode are switched.
- the signal processing apparatus 2 operates the background signal estimation unit 9 during the period of the first mode, removes the background signal with the background signal removal unit 10 during the period of the second mode, and then recognizes with the recognition unit 7. It is preferable to carry out the treatment.
- the time in the first mode and the time in the second mode are not limited to the same time (for example, 30 seconds), and may be different from each other.
- the background signal removing unit 10 may remove the background signal by subtracting the background signal from the signal output from the filter bank 5a.
- the background signal removal unit 10 for example, the background signal estimated by the background signal estimation unit 9 from the intensity of the signals m 1 , m 2 ,... (See FIG. 4B) that have passed through each filter bank 5a. .. (See FIG. 4A) can be constituted by a subtracter that subtracts the intensity b 1 , b 2 ,.
- FIG. 4C shows the intensity of the signal obtained by subtracting the background signal from the signal between the same filter banks 5a.
- L 1 m 1 -b 1 It becomes.
- the signal strengths after subtracting the background signal for the second filter bank 5a, the third filter bank 5a, the fourth filter bank 5a, and the fifth filter bank 5a are L 2 and L 3 , respectively.
- L 4 m 4 -b 4
- L 5 m 5 ⁇ b 5
- the background signal estimation unit 9 may estimate the signal strength obtained for each filter bank 5a as the background signal strength for each filter bank 5a and update it as needed during the first mode period. Further, in the first mode, the background signal estimation unit 9 may estimate the average value of the intensity of the plurality of signals obtained for each filter bank 5a as the intensity of the background signal for each filter bank 5a. That is, the background signal estimation unit 9 may use an average value on the time axis of a plurality of signals for each filter bank 5a obtained in advance as the background signal. Thereby, the background signal estimation unit 9 can improve the estimation accuracy of the background signal.
- the background signal removal unit 10 may use the signal immediately before each filter bank 5a as the background signal.
- the signal processing device 2 may have a function of removing the background signal by subtracting the immediately preceding signal on the time axis before each signal is normalized by the normalization unit 6.
- the background signal removal unit 10 has a function of removing the background signal by subtracting the signal one sample before on the time axis from the signal to be subjected to normalization processing with respect to the signal that has passed through each filter bank 5a. You may do it. In this case, for example, as shown in FIG.
- the signals of the filter bank 5a at the time t 1 to be subjected to the normalization process are expressed as m 1 (t 1 ), m 2 (t 1 ), m 3 (t 1 ), M 4 (t 1 ), and m 5 (t 1 ). Furthermore, the signals at the time t 0 immediately before are m 1 (t 0 ), m 2 (t 0 ), m 3 (t 0 ), m 4 (t 0 ), and m 5 (t 0 ).
- L 1 m 1 (t 1 ) ⁇ m 1 (t 0 )
- L 2 m 2 (t 1 ) ⁇ m 2 (t 0 )
- L 3 m 3 (t 1 ) ⁇ m 3 (t 0 )
- L 4 m 4 (t 1 ) ⁇ m 4 (t 0 )
- L 5 m 5 (t 1 ) ⁇ m 5 (t 0 ) It becomes.
- the frequency bin 5b including a relatively large background signal may be known in advance.
- a relatively large background signal is included in the signal of the frequency bin 5b including a specific frequency such as a frequency multiplied by a commercial power supply frequency (for example, 60 Hz) (for example, 60 Hz, 120 Hz, etc.).
- a commercial power supply frequency for example, 60 Hz
- 60 Hz for example, 60 Hz, 120 Hz, etc.
- the sensor signal output when the detection target object (detection target) is moving within the detection area has a frequency (Doppler frequency) of the sensor signal that is the distance between the radio wave sensor 1 and the object. Depending on the moving speed of the object, it changes from time to time. In this case, the background signal does not constantly occur at a specific frequency.
- the signal processing device 2 sets the frequency bin 5b in which the background signal is constantly included as the specific frequency bin 5b i .
- the background signal removing unit 10 by complementing with the intensity of the signal and disabling the signal of a particular frequency bin 5b i, estimated from the intensity of the signals of the two frequency bins 5b adjacent to the specific frequency bin 5b i The background signal may be removed.
- the third frequency bin 5b from the left in FIG. 6A is the specific frequency bin 5b i .
- Background signal removing unit 10 invalidates the signal of the specific frequency bin 5b i (signal strength b 3), as shown in FIG. 6B, the signal of two frequency bins 5b adjacent to the specific frequency bin 5b i It is supplemented by components of the intensity b 2, b 4 intensity of the estimated signal component from b3.
- the average value of the signal strengths b 2 and b 4 of the two frequency bins 5b adjacent to the specific frequency bin 5b i that is, (b 2 + b 4 ) / 2 is used as the estimated signal strength. It is set to b 3.
- the signal processing device 2 can reduce the influence of the background signal (noise) of a specific frequency that is constantly generated in a short time. Therefore, the signal processing device 2 can improve the detection accuracy of the detection object.
- the background signal removal unit 10 can also use an adaptive filter that removes the background signal by filtering the background signal in the frequency domain (on the frequency axis).
- the adaptive filter is a filter that self-adapts a transfer function (filter coefficient) according to an adaptive algorithm (optimization algorithm), and can be realized by a digital filter.
- an adaptive filter using DCT Adaptive filter using Discrete Cosine Transform
- an LMS (Least Mean Square) algorithm of DCT may be used as an adaptive algorithm of the adaptive filter.
- the adaptive filter may be an adaptive filter using FFT.
- an FFT LMS algorithm may be used as the adaptive algorithm of the adaptive filter.
- the LMS algorithm has an advantage that the amount of calculation can be reduced as compared with the projection algorithm and the RLS (Recursive Least Square) algorithm.
- the DCT LMS algorithm only requires real arithmetic, and has an advantage that the amount of calculation can be reduced as compared with the FFT LMS algorithm requiring complex arithmetic.
- the adaptive filter has, for example, the configuration shown in FIG.
- This adaptive filter includes a filter 57a, a subtractor 57b, and an adaptive processing unit 57c.
- the filter 57a has a variable filter coefficient.
- the subtractor 57b outputs an error signal between the output signal of the filter 57a and the reference signal.
- the adaptive processing unit 57c generates a correction coefficient for the filter coefficient from the input signal and the error signal according to the adaptive algorithm, and updates the filter coefficient.
- the adaptive filter can remove the background signal by filtering the unnecessary background signal if the input signal of the filter 57a is a background signal composed of thermal noise and the reference signal is a desired white noise value. .
- the background signal removing unit 10 appropriately sets a forgetting factor of the adaptive filter so as to extract a frequency distribution of a signal obtained by filtering a long-time average background signal on the frequency axis. It may be.
- the forgetting factor decreases the influence of past data (filter factor) exponentially as it goes back from the current data (filter factor) to the past, and becomes heavier as it approaches the current data in the calculation of updating the filter factor.
- Is a coefficient for The forgetting factor is a positive value less than 1, and may be appropriately set within a range of, for example, about 0.95 to 0.99.
- the recognition unit 7 performs a recognition process of detecting an object based on the distribution in the frequency domain of each normalized intensity that has passed through each filter bank 5a and is normalized by the normalization unit 6.
- detection is a concept including classification, recognition, and identification.
- the recognition unit 7 detects an object by performing pattern recognition processing by principal component analysis (principal component analysis), for example.
- the recognition unit 7 operates according to a recognition algorithm using principal component analysis.
- the signal processing device 2 previously corresponds to each of the learning sample data when the detection object is not included in the detection area of the radio wave sensor 1 and the different movements of the detection object.
- the signal processing device 2 stores data obtained by performing principal component analysis on the plurality of learning data in the database 11.
- data stored in the database 11 is data used for pattern recognition, and is category data in which an object motion is associated with a projection vector and a discrimination boundary value.
- FIG. 8A shows the distribution in the frequency domain of the normalized intensity corresponding to the learning sample data when the detection object of the radio wave sensor 1 does not include the detection target object. Furthermore, the distribution in the frequency domain of the normalized intensity corresponding to the learning sample data when the detection target is included is shown in FIG. 8B.
- the normalized intensities of signals that have passed through the respective filter banks 5a are assumed to be m 10 , m 20 , m 30 , m 40 and m 50 in order from the low frequency side.
- FIG. 8A the normalized intensities of signals that have passed through the respective filter banks 5a are assumed to be m 10 , m 20 , m 30 , m 40 and m 50 in order from the low frequency side.
- the normalized intensities of the signals that have passed through the respective filter banks 5a are m 11 , m 21 , m 31 , m 41, and m 51 in order from the low frequency side.
- FIG. 8A in any of FIG. 8B, the sum of the normalized intensity of the signal passing through each of the three filterbanks 5a of the low frequency side and variables m 1, was passed through each of the two filter banks 5a of the high-frequency side Let the sum of the normalized strengths of the signal be the variable m 2 .
- FIG. 8C illustrates a two-dimensional scatter diagram, a projection axis, and a recognition boundary in two dimensions when the two variables m 1 and m 2 are orthogonal coordinate axes.
- the coordinate position of each scatter point (“+” in FIG. 8C) in the area surrounded by the broken line is ⁇ 0 (m 2 , m 1 )
- the coordinate position of each scatter point in the area surrounded by the solid line is It is set as ⁇ 1 (m 2 , m 1 ).
- the data group Gr0 corresponding to the learning sample data when the detection area of the radio wave sensor 1 does not include the detection target object and the data corresponding to the learning sample data when the detection area includes the detection target object.
- a group Gr1 is determined in advance.
- the projection axis is determined under the condition that the interval is maximized and the variance is maximized. Thereby, in principal component analysis, a projection vector can be obtained for each learning sample.
- the signal processing device 2 includes an output unit 12 that outputs a detection result by the recognition unit 7.
- the output unit 12 outputs a high level signal (for example, “1”) as an output signal indicating that the detection target is detected.
- the output unit 12 outputs a low-level signal (for example, “0”) as an output signal indicating that the detection target is not detected.
- the signal processing device 2 is realized by executing an appropriate program by a microcomputer other than the amplification unit 3, the A / D conversion unit 4, the output unit 12, and the database 11.
- FIG. 9 is a diagram for explaining a use situation of the sensor device Se including the radio wave sensor 1 and the signal processing device 2, where the detection target Ob is a person and an object other than the detection target is present in the outdoor detection area. It shows that a certain tree Tr exists.
- FIG. 10 shows the radio wave sensor 1 when the object Ob moves by 6.7 m at a moving speed of 1 m / s in front of the tree Tr with the branches and leaves of the tree Tr swaying under this usage condition. An example of the output sensor signal is shown.
- the distance between the radio wave sensor 1 and the tree Tr is about 10 m, and the distance between the radio wave sensor 1 and the object Ob is about 8 m.
- FIG. 10 shows the radio wave sensor 1 when the object Ob moves by 6.7 m at a moving speed of 1 m / s in front of the tree Tr with the branches and leaves of the tree Tr swaying under this usage condition.
- An example of the output sensor signal is shown.
- FIG. 11 is a diagram showing a distribution of normalized strength in the frequency domain and a distribution in the time axis domain.
- FIG. 12 is an output signal of the output unit 12, and it was confirmed that false detection caused by the movement of an object other than the detection target can be reduced.
- the signal component has a frequency distribution from a lower frequency region.
- the object is a person walking in the detection area, it has a mountain-shaped frequency distribution with a center frequency near the frequency corresponding to the walking speed, and there is a clear difference in the frequency distribution. .
- Objects other than the detection target existing in the detection area are mainly movable objects that are not moving objects.
- the object other than the detection target existing in the detection area is not limited to the tree Tr, and includes, for example, an electric wire swayed by the wind.
- FIG. 13 is a diagram for explaining a use situation of the sensor device Se including the radio wave sensor 1 and the signal processing device 2, in which the detection target Ob is a person and it is raining in the outdoor detection area. Is shown.
- FIG. 14 shows an example of a sensor signal output from the radio wave sensor 1 when the object Ob moves by 6.7 m at a moving speed of 1 m / s under this usage condition.
- FIG. 15 is an output signal of the output unit 12 when the background signal removal unit 10 does not remove the background signal.
- FIG. 16 is a diagram illustrating a distribution in the frequency domain of the normalized intensity and a distribution in the time axis domain when the background signal is removed by the background signal removal unit 10.
- FIG. 17 is an output signal of the output unit 12 when the background signal is removed by the background signal removal unit 10 and is caused by the movement of an object other than the detection target (here, raindrops) as compared to FIG. It was confirmed that false detection can be reduced.
- an object other than the detection target existing in the detection area is, for example, a device including a movable body (a blade in the case of a fan) such as a fan. Is mentioned.
- the signal processing device 2 preferably makes the above-described discrimination boundary value variable by setting from the outside. As a result, the signal processing device 2 can adjust the false alarm rate and false alarm rate required according to the intended use. For example, in a use application in which the detection target is a person and the lighting load is controlled on and off based on an output signal from the output unit 12, the person enters the detection area of the radio wave sensor 1. Some misinformation may be tolerated as long as it is misreported.
- the frequency analysis unit 5 converts the sensor signal (time axis signal) output from the A / D conversion unit 4 into a signal in the frequency domain, and in the group of filter banks 5a having different frequency bands. It is extracted as a signal for each filter bank 5a.
- the recognition unit 7 performs a recognition process for detecting an object based on a frequency distribution determined from a signal intensity based on a signal for each filter bank 5a.
- the sensor signal has a unique frequency distribution (statistical distribution in the frequency domain) that is different for each object even in a short time (for example, several tens of ms) in which frequency analysis such as DCT is performed.
- the signal processing apparatus 2 uses the characteristics of the frequency distribution to detect the detection target, the signal processing apparatus 2 can recognize and recognize objects having different frequency distributions.
- the signal processing device 2 can reduce false detection caused by the movement of an object other than the detection target.
- the signal processing device 2 can separate and detect objects having statistically different frequency distributions determined from the signal intensities of the signals that have passed through the plurality of filter banks 5a, thereby reducing false detection. It becomes.
- a process of multiplying a sensor signal by a predetermined window function is performed before the FFT process, and a side lobe outside a desired frequency band (pass band) ( Side-lobe) may need to be suppressed.
- the window function for example, a rectangular window, a Gauss window, a Hann window, a Hamming window, or the like can be used.
- the window function can be eliminated, so that the window function can be realized with a simple digital filter.
- the filter bank 5a using DCT is compared with the filter bank 5a using FFT, whereas FFT is a complex arithmetic processing method (calculating intensity and phase), whereas DCT is a real arithmetic processing method. Therefore, it is possible to reduce the operation scale.
- the DCT when the DCT and the FFT are compared with the same number of processing points, the DCT is a half of the FFT, so the hardware resource (hardware resource) such as the database 11 is used. It becomes possible to reduce the size.
- the width of the FFT bin 5b is 8 Hz
- the width of the DCT bin 5b can be 4 Hz.
- these numerical values are examples and are not intended to be limited to these numerical values.
- the signal processing device 2 removes the normalized strength output from the normalization unit 6 at that time as an offset background signal. By doing so, it becomes possible to improve recognition accuracy.
- the recognition unit 7 may detect an object by pattern recognition processing based on principal component analysis, or may use other pattern recognition processing. For example, the recognition unit 7 may detect an object by pattern recognition processing using KL conversion.
- the signal processing apparatus 2 performs a pattern recognition process by principal component analysis or a pattern recognition process by KL conversion in the recognition unit 7, thereby reducing the amount of calculation in the recognition unit 7 and the capacity of the database 11. It becomes possible.
- the recognition unit 7 may perform a recognition process for detecting an object based on the component ratio of the normalized intensity for each filter bank 5a output from the normalization unit 6.
- Such a recognition unit 7 may detect an object by performing recognition processing by multiple regression analysis, for example.
- the recognition unit 7 operates according to a recognition algorithm using multiple regression analysis.
- the signal processing device 2 acquires learning data corresponding to different movements of the detection target in the detection area of the radio wave sensor 1 in advance.
- the signal processing apparatus 2 stores data obtained by performing multiple regression analysis on the plurality of learning data in the database 11.
- FIG. 18 shows a combined waveform Gs in which the signal component s1, the signal component s2, and the signal component s3 are combined. According to the multiple regression analysis, this synthesized waveform Gs is obtained from the synthesized waveform even if the type of the signal components s1, s2, s3, the number of signal components, and the intensity of each of the signal components s1, s2, s3 are unknown. It is possible to separate and estimate the signal components s1, s2, and s3.
- FIG. 18 shows a combined waveform Gs in which the signal component s1, the signal component s2, and the signal component s3 are combined. According to the multiple regression analysis, this synthesized waveform Gs is obtained from the synthesized waveform even if the type of the signal components
- [S] indicates a matrix having signal components s1, s2, and s3 as matrix elements
- [S] -1 means an inverse matrix of [S]
- I indicates a component ratio of normalized intensity ( Coefficient).
- the data stored in the database 11 is data used for the recognition process, and is data in which the motion of the object is associated with the signal components s1, s2, and s3.
- the horizontal axis represents time
- the vertical axis represents normalized strength
- Data on the time axis (corresponding to the above-described synthesized waveform Gs) is A1.
- FIG. 19A also shows signal components A2 and A3 separated from data A1 by multiple regression analysis.
- the signal component A2 is a signal component resulting from movement of a person
- the signal component A3 is a signal component resulting from shaking of the electric wire.
- 19B shows that the recognition unit 7 recognizes that the detection target exists when A2> A3, and sets the output signal of the output unit 12 to the high level (here, the value “1”). This is an output signal of the output unit 12 when it is recognized that there is no object and the output signal of the output unit 12 is set to a low level (value “0” in this case). From FIG. 19B, it was confirmed that the erroneous detection caused by the movement of the object other than the detection target (here, the electric wire) can be reduced.
- the signal processing device 2 preferably makes the above-described determination condition (A2> A3) variable by setting from the outside.
- the determination condition is A2> ⁇ ⁇ A3, and the coefficient ⁇ is variable by setting from the outside.
- the signal processing device 2 can adjust the false alarm rate and false alarm rate required according to the intended use.
- the recognition unit 7 may detect the detection target based on both the above-described characteristics of the frequency distribution and the component ratio of the normalized intensity.
- the recognizing unit 7 may detect an object by a majority decision based on the result of an odd number of recognition processes on the time axis. For example, according to the majority decision of the result of the recognition process performed three times in the region surrounded by the one-dot chain line in FIG.
- the signal processing device 2 can improve the detection accuracy in the recognition unit 7.
- the signal processing device 2 performs the recognition process by the recognition unit 7 only when the sum of the signal component intensities or the weighted sums of the plurality of predetermined filter banks 5a before normalization by the normalization unit 6 is equal to or greater than the threshold value.
- the recognition result by the recognition unit 7 may be validated.
- 21A and 21B show the case where the signal strength of each filter bank 5a before normalization by the normalization unit 6 is m 1 , m 2 , m 3 , m 4 and m 5 in order from the low frequency side. It is an example.
- FIG. 21A shows a case where the sum of the intensity [m 1 + m 2 + m 3 + m 4 + m 5 ] is equal to or greater than the threshold value E1.
- FIG. 21B shows a case where the total sum [m 1 + m 2 + m 3 + m 4 + m 5 ] of the intensity is less than the threshold value E1.
- the signal processing device 2 can reduce false detection.
- the recognition unit 7 recognizes an object based on a frequency distribution using the normalized signal component intensity.
- the recognition unit 7 is characterized in that there is no detection target within the detection range of the radio wave sensor 1 and the frequency distribution of the signal intensity is within the detection range even when dark noise is input. It is possible to make a false detection by determining that it is similar to. Therefore, the signal processing device 2 suppresses erroneous detection by determining whether or not recognition processing is possible using the signal strength before normalization.
- a plurality of predetermined filter banks 5a before normalization by the normalization unit 6 are set as one filter bank group 50 (see FIG. 22).
- the signal processing apparatus 2 may determine whether or not the sum of the signal component intensities or the weighted sum before normalization is greater than or equal to the threshold E2 in each of the plurality of filter bank groups 50. That is, the signal processing device 2 performs the recognition process by the recognition unit 7 only when the sum of the intensities of the signal components before normalization is equal to or greater than the threshold E2 in any one of the filter banks 50, or by the recognition unit 7. The result of recognition processing is validated.
- the signal processing device 2 performs the recognition processing by the recognition unit 7 only when the intensity summation or weighted sum of the signal components before normalization is greater than or equal to the threshold E2 in all the filter bank groups 50, or the recognition unit The result of the recognition process according to 7 may be valid.
- a series of processes including this determination process will be described with reference to the flowchart of FIG.
- the “total sum or weighted sum of signal component intensities before standardization” is simply referred to as “total sum of signal component intensities before standardization”.
- the A / D converter 4 performs an A / D conversion process for converting the sensor signal amplified by the amplifier 3 into a digital sensor signal and outputting it (X1).
- the frequency analysis unit 5 converts the sensor signal output from the A / D conversion unit 4 into a frequency domain signal (frequency axis signal) by DCT processing (X2) and extracts it as a signal for each filter bank 5a.
- Filter bank processing is performed (X3). For example, in the case of 128-point DCT, it is conceivable to bundle five frequency bins 5b from 128 frequency bins 5b and divide them into 25 filter banks 5a.
- the signal processing device 2 standardizes a plurality of filter banks 5a constituting each filter bank group 50 for each of the two filter bank groups 50 on the low frequency side and the high frequency side. Find the sum of the previous signal strengths. Then, the signal processing device 2 performs a threshold determination process for determining for each filter bank group 50 whether or not the sum of the signal intensities is equal to or greater than the threshold E2 (X4).
- the signal processing device 2 determines that the amplitude of the sensor signal output from the radio wave sensor 1 is large and the possibility of background noise is low if the sum of the signal intensities in any of the filter bank groups 50 is equal to or greater than the threshold value E2. Then, normalization processing by the normalization unit 6 is performed (X5). That is, the normalization unit 6 normalizes the intensity of the signal that has passed through each filter bank 5a and outputs the normalized intensity.
- the recognition unit 7 of the signal processing device 2 recognizes the characteristics of the signal intensity distribution for each frequency component of the plurality of filter banks 5a obtained by normalization, and determines whether or not it can be regarded as a detection target. A recognition process is performed to determine (X6). And the output part 12 performs the output process of a detection signal, when the recognition part 7 judges that it is a detection target object (X7).
- the signal processing device 2 determines that there is a high possibility of background noise, the signal processing device 2 does not perform the subsequent processing (X5 to X7) including the normalization processing by the normalization unit 6.
- FIG. 24 shows an example of a sensor signal (dark noise signal pattern) output from the radio wave sensor 1 when there is no object to be detected.
- FIG. 25 shows an example of a sensor signal output from the radio wave sensor 1 when there is an object to be detected.
- the sensor signal of the dark noise shown in FIG. 24 has a smaller amplitude than the sensor signal at the time of object detection shown in FIG. 24 and 25, the horizontal axis represents time, and the vertical axis represents the intensity (voltage) of the sensor signal.
- the output signal of the output unit 12 is shown as in FIG. 26 for the sensor signal (dark noise) in FIG. FIG. 27 shows 25 sensor signals (with detection object). That is, it was confirmed that by appropriately setting the threshold value E2, erroneous detection due to dark noise can be reduced, and when there is a detection target, it can be accurately detected. 26 and 27, the output signal of the output unit 12 is at a high level (here, the value “1”) when the detection target is detected by the recognition unit 7, and the detection target is not detected. At a low level (here, the value “0”).
- the threshold value E2 when the threshold value E2 is set to zero, the output signal of the output unit 12 is shown as in FIG. 28 for the sensor signal (dark noise) in FIG. 24, and the sensor signal in FIG. 25 (with detection object). Is shown in FIG. That is, when the signal processing device 2 does not perform the threshold determination process of step X4 described above, erroneous detection due to background noise frequently occurs, and even when there is a detection target, the value of the output signal of the output unit 12 is It is frequently switched to “1”. Thus, it can be seen that if the signal processing device 2 does not perform the threshold determination process in step X4 described above, there is a possibility that erroneous detection due to background noise may occur.
- the signal processing apparatus 2 includes a parameter adjustment unit 14, and the parameter adjustment unit 14 changes a parameter for adjusting the detection sensitivity of the object in the recognition process of the recognition unit 7.
- Parameters for adjusting the detection sensitivity include the above-described threshold values E1, E2, and the like.
- the signal processing apparatus 2 includes a state machine for performing the above-described processes, and the basic operation of this state machine (operation when the level setting unit 13 is not used) is shown in FIG.
- the above-described threshold value E2 is used as a parameter to be adjusted by the parameter adjustment unit 14.
- the state machine starts operating from the idle state J11. Then, the state machine transits from the idle state J11 to the state I00 (t01).
- the level of background noise in the surrounding environment where the radio wave sensor 1 is installed may change due to factors such as an increase or decrease in factors that change the background noise level. Therefore, even if the threshold value E2 in the threshold value determination process is set once, if the background noise level changes, the current setting value does not perform the expected operation, and a false detection occurs or a detection target exists. Nevertheless, there is a possibility of non-detection.
- the parameter adjustment unit 14 performs an operation of setting the threshold value E2 in the threshold determination process in the startup period, and after setting the threshold value E2, transitions to the state S11 (t02). .
- sensor signal A / D conversion processing, DCT processing, and filter bank processing are performed (steps X1 to X3 in FIG. 23), and the signal strength in each filter bank 5a is measured.
- the parameter adjustment unit 14 calculates a threshold value E2 by multiplying the average value of the signal intensities of all or a plurality of filter banks 5a by a predetermined coefficient, and uses the threshold value E2 as a threshold value in the subsequent threshold value determination processing. To do.
- the range of the threshold value E2 may be limited by a predetermined upper limit value or lower limit value.
- the upper limit value of the threshold value E2 is set in order to ensure the detection accuracy of the detection object, and the lower limit value of the threshold value E2 is set in order to ensure the effect of suppressing erroneous detection due to dark noise.
- the threshold value E2 is a value based on background noise.
- the parameter adjustment unit 14 sets the threshold value E2 used for the threshold value determination process according to the surrounding background noise environment. Specifically, instead of performing the recognition process immediately after activation, first, the ambient dark noise level is measured from the sensor signal, and the parameter adjusting unit 14 multiplies the measured value by a predetermined coefficient to generate the threshold value E2. Is calculated. Therefore, even when the surrounding environment of the radio wave sensor 1 changes and the background noise level also changes, the threshold value E2 can be appropriately changed during the startup period, so that erroneous detection due to background noise can be reduced.
- the state machine transits from the state I00 to the state S11 (t02). If the recognition unit 7 detects the detection target in the state S11 (hereinafter referred to as a detection state), the state machine changes to the state W11. Transition (t03). On the other hand, in the state S11, if the recognition unit 7 does not detect the detection object (hereinafter referred to as a non-detection state), after a predetermined time has elapsed since the transition to the state S11, the state The process proceeds to S16 (t04). And if it is a non-detection state in state S16, it will change to state S11 (t05). That is, when the non-detection state continues from the state S11, a transition reciprocating between the state S11 and the state S16 is indicated.
- state S11 if it becomes a detection state in state S11, S16, it will change to state W11 (t03, t06), and after waiting for the predetermined time in state W11, it will change to state S12 (t07), and it will not change to state S13. Transitions under conditions (t08).
- the state S13 if it is a non-detection state or if the detection state continues for a predetermined time or more, the state transitions to the state S14 (t09). And if it is a detection state in state S14, it will change to state S13 (t10). That is, when the detection state continues from state S13, a transition that reciprocates between state S13 and state S14 is indicated.
- state S15 if it is a non-detection state in state S14, it will change to state S15 (t11). If it is a non-detection state in state S15, it will change to state S11 (t12), and if it is a detection state in state S15, it will change to state W11 (t13).
- the signal processing apparatus 2 performs each of the above-described steps X1 to X7 while changing the states of the state machine.
- the parameter adjustment unit 14 performs an operation of resetting the threshold value E2, assuming that the detection state may be continued. Specifically, in state I11, sensor signal A / D conversion processing, DCT processing, and filter bank processing are performed (steps X1 to X3 in FIG. 23), and the signal strength in each filter bank 5a is measured. Then, the parameter adjustment unit 14 calculates a threshold value E2 by multiplying an average value of signal intensities of all or a plurality of filter banks 5a by a predetermined coefficient, and uses the threshold value E2 in the subsequent threshold value determination processing. Further, the range of the threshold value E2 may be limited by a predetermined upper limit value or lower limit value.
- the parameter adjustment unit 14 resets the threshold E2 newly calculated in the state I11 to the threshold E2 newly calculated in the state I11 instead of the threshold E2 in use only when the threshold E2 newly calculated in the state I11 is larger than the threshold E2 currently in use. Set. Conversely, when the threshold E2 newly calculated in the state I11 is equal to or less than the threshold E2 currently in use, the parameter adjustment unit 14 does not reset the threshold E2 calculated in the state I11 and does not reset the threshold E2 in use. Continue to use E2. And after the process in the state I11 is completed, it changes to state S11 (t15).
- the parameter adjustment unit 14 performs an operation of resetting the threshold value E2, assuming that the non-detection state may be continued. Specifically, in the state I12, A / D conversion processing, DCT processing, and filter bank processing of the sensor signal are performed (steps X1 to X3 in FIG. 23), and the signal strength in each filter bank 5a is measured. Then, the parameter adjustment unit 14 calculates a threshold value E2 by multiplying an average value of signal intensities of all or a plurality of filter banks 5a by a predetermined coefficient, and uses the threshold value E2 in the subsequent threshold value determination processing. Further, the range of the threshold value E2 may be limited by a predetermined upper limit value or lower limit value.
- the parameter adjustment unit 14 resets the threshold E2 newly calculated in the state I12 to the threshold E2 newly calculated in the state I12 instead of the threshold E2 in use only when the threshold E2 newly calculated in the state I12 is smaller than the threshold E2 currently in use. Set. Conversely, the parameter adjustment unit 14 does not reset the threshold E2 newly calculated in the state I12 to the new threshold E2 calculated in the state I12 when the threshold E2 newly calculated in the state I12 is equal to or greater than the threshold E2 currently used. Continue to use E2. Then, after the processing in the state I12 is completed, the state transitions to the state S11 if it is a non-detection state (t17), and transitions to the state W11 if it is a detection state (t18).
- the current threshold value E2 may be set to an inappropriate value for the current background noise or ambient noise. It is determined that there is, and the threshold value E2 is reset. Therefore, when erroneous detection occurs due to the threshold E2 being too small, the erroneous detection can be suppressed by updating to a larger threshold E2. When the detection target cannot be detected because the threshold value E2 is too large, the detection sensitivity is increased and detection omission can be reduced by updating to a smaller threshold value E2.
- the threshold value E2 used in the threshold value determination process is updated as described above, a detection that becomes a non-detected state due to a large change in the surrounding environment, even if a false detection occurs or a detection target exists. Leakage may occur.
- the signal processing device 2 of the present embodiment includes a level setting unit 13 (see FIG. 1).
- FIG. 13 shows the operation of the state machine using the level setting unit 13.
- the level setting unit 13 sets a sensitivity level indicating the level of detection sensitivity of the detection target in the recognition process of the recognition unit 7. This level setting unit 13 sets the sensitivity level to a low level when it is determined that the erroneous detection by the recognition unit 7 is likely to occur in spite of the updating process of the threshold value E2 in the states I11 and I12. Furthermore, the level setting unit 13 sets the sensitivity level high when it is determined that erroneous detection by the recognition unit 7 is unlikely to occur.
- the parameter adjustment unit 14 Based on the sensitivity level set by the level setting unit 13, the parameter adjustment unit 14 sets parameters so that the object detection sensitivity is high when the sensitivity level is high, and the object detection sensitivity is low when the sensitivity level is low. Set the parameter so that it is lower. That is, when the sensitivity level set by the level setting unit 13 is high, the parameter adjustment range (upper limit, lower limit) by the parameter adjustment unit 14 is set to a range in which an object is relatively easy to detect. Further, when the sensitivity level set by the level setting unit 13 is low, the parameter adjustment range (upper limit, lower limit) by the parameter adjustment unit 14 is set to a range in which an object is relatively difficult to detect.
- FIG. 31 shows a state C11 provided between the state S11 and the state I12 in the state machine of FIG.
- the level setting unit 13 performs a sensitivity level update process. Specifically, the level setting unit 13 occurred because the detection state that caused the transition to the state W11 occurred because the detection target was detected, or because the movement (disturbance) of an object other than the detection target was erroneously detected. Judge whether or not. The determination processing of the level setting unit 13 is performed based on the recognition result of the recognition unit 7 based on the current sensor signal. When the level setting unit 13 determines that the detection state that caused the transition to the state W11 has occurred because the detection target has been detected, the level setting unit 13 is in a situation where the recognition unit 7 is unlikely to generate a false detection (normal time). Judge that there is.
- the level setting unit 13 determines that the detection state that causes the transition to the state W11 has occurred due to erroneous detection of a motion (disturbance) of an object other than the detection target, an erroneous detection by the recognition unit 7 occurs. It is determined that the situation is easy to occur (when a disturbance occurs).
- the level setting unit 13 has a flag setting function indicating the level of detection sensitivity of the detection target in the recognition processing of the recognition unit 7, and updates the flag setting based on the result of the determination processing described above. To do.
- the level setting unit 13 sets the flag to “0” when it is determined that it is normal time, and sets the flag to “1” when it is determined that disturbance is occurring.
- the flag “0” corresponds to the sensitivity level: “high”
- the flag “1” corresponds to the sensitivity level: “low”.
- the flag update process by the level setting unit 13 may be performed when the determination that the disturbance is occurring continues for a predetermined number of times or when the determination that the time is normal continues for a predetermined number of times. preferable.
- the flag update process by the level setting unit 13 when the determination that the disturbance is occurring occurs more than a predetermined number of times within a predetermined period, or the determination that it is normal occurs more than a predetermined number of times within a predetermined period. It is preferable to be performed.
- the level setting unit 13 sets the sensitivity level low when it is determined that the erroneous detection of the recognition unit 7 is likely to occur due to disturbance.
- the level setting unit 13 sets the sensitivity level to a high level (returns the sensitivity level to the original level) when it is determined that the erroneous detection of the recognition unit 7 is unlikely to occur.
- the parameter adjustment unit 14 sets the threshold value E2 so that the detection sensitivity is high if the flag is “0” (setting at the normal time). If the flag is “1”, the parameter adjustment unit 14 sets the threshold value E2 so that the detection sensitivity of the object is low (setting for occurrence of disturbance). That is, if the flag is “0”, the parameter adjustment unit 14 sets the adjustment range of the threshold (E2) to a relatively low range, and if the flag is “1”, the parameter adjustment unit 14 sets the adjustment range of the threshold (E2) to a relatively low range. Set to a higher range.
- the state machine transitions to state C11 without transitioning to state S16 even in the non-detection state (t16A).
- the level setting unit 13 updates the flag setting. Specifically, the level setting unit 13 determines whether the non-detection state that caused the transition to the state C11 has occurred because the detection target does not actually exist, or whether the detection target is actually present. It is judged whether it occurred because it was falsely detected that there was nothing. The determination processing of the level setting unit 13 is performed based on the recognition result of the recognition unit 7 based on the current sensor signal.
- the level setting unit 13 determines that the non-detection state that has caused the transition to the state C11 has occurred because there is no actual detection target, the level setting unit 13 is less likely to cause erroneous detection by the recognition unit 7 ( (Normal time). Further, when the level setting unit 13 determines that the detection state that caused the transition to the state C11 is erroneously detected that there is no detection target even though the detection target is actually present, It is determined that the situation in which erroneous detection by the unit 7 is likely to occur (when a disturbance occurs).
- the level setting unit 13 updates the flag setting based on the result of the determination process described above.
- the level setting unit 13 sets the flag to “0” when it is determined that it is normal time, and sets the flag to “1” when it is determined that disturbance is occurring.
- the sensitivity level setting process by the level setting unit 13 is completed. Transition from the state C11 to the state I12 (t16B).
- the flag update process by the level setting unit 13 may be performed when the determination that the disturbance is occurring continues for a predetermined number of times or when the determination that the time is normal continues for a predetermined number of times. preferable.
- the flag update process by the level setting unit 13 when the determination that the disturbance is occurring occurs more than a predetermined number of times within a predetermined period, or the determination that it is normal occurs more than a predetermined number of times within a predetermined period. It is preferable to be performed.
- the parameter adjustment unit 14 sets the threshold value E2 so as to increase the detection sensitivity if the flag is “0”, and if the flag is “1”, The threshold value E2 is set so that the detection sensitivity is lower. That is, if the flag is “0”, the parameter adjustment unit 14 sets the adjustment range of the threshold E2 to a relatively low range, and if the flag is “1”, the parameter adjustment unit 14 sets the adjustment range of the threshold E2 to a relatively high range. To do.
- the normal determination process is a method based on pattern recognition using the distribution of frequency components of the sensor signal, and based on past fluctuations in the sensor signal. There is a method for detecting the presence or absence of difficult features.
- FIG. 32 and 33 show simulation results using the basic operation of the state machine shown in FIG. 30 (operation when the level setting unit 13 is not used).
- FIG. 32 shows an example of a sensor signal output from the radio wave sensor 1.
- FIG. 33 shows an output signal of the output unit 12.
- the sensor signal of FIG. 32 the sensor signal at the time of occurrence of the disturbance is generated in the period T1, and the sensor signal due to the approaching detection target is generated in the period T2.
- erroneous detection for detecting the detection target frequently occurs in the period T1. That is, in the basic operation of the state machine shown in FIG. 30, erroneous detection due to disturbance frequently occurs.
- FIGS. 34 and 35 show simulation results using the state machine (operation when using the level setting unit 13) shown in FIG.
- FIG. 34 shows the state of the flag set by the level setting unit 13.
- FIG. 35 is an output signal of the output unit 12 with respect to the sensor signal of FIG.
- the output signal of the output unit 12 is in a detection state at the beginning of the period T1.
- the level setting unit 13 detects erroneous detection due to disturbance and switches the flag from “0” to “1”.
- the setting of the threshold value (E2) by the parameter adjustment unit 14 becomes a setting for when a disturbance occurs, and the output signal of the output unit 12 continues to be in a non-detection state. That is, when the flag is switched from “0” to “1”, the parameter adjustment unit 14 sets the threshold value E2 so that the detection sensitivity becomes low, and thereafter false detection due to disturbance is reduced.
- the level setting unit 13 switches the flag from “1” to “0” in the state C11, so that the setting of the threshold value E2 by the parameter adjustment unit 14 becomes the setting for normal time.
- the parameter adjustment unit 14 switches the threshold value E2 setting for normal time and the threshold value E2 setting for occurrence of disturbance.
- the threshold value E2 setting for occurrence of disturbance suppresses false detection compared to the threshold value E2 setting for normal time.
- the flag set by the level setting unit 13 is updated in the state S12 and the state C11.
- the level setting unit 13 switches the flag state and the parameter adjustment unit 14 changes the threshold value E2 while the recognition unit 7 is performing the recognition process, a malfunction may be caused. Therefore, the signal processing device 2 does not perform the recognition target object recognition processing by the recognition unit 7 in the state S12 and the state C11. That is, the level setting unit 13 switches the flag state (sensitivity level) when the recognition unit 7 is not performing recognition processing, and switches the flag state (sensitivity level) when the recognition unit 7 is performing recognition processing. Absent. By separating the processing contents in the state machine, the recognition process of the detection object and the update process of the threshold value E2 are executed separately. Therefore, it is possible to suppress the occurrence of malfunction when the recognition unit 7 performs the recognition process.
- the update process of the flag state in the state S12 and the state C11 is performed using only the sensor signal input within the period of the state S12 and the state C11.
- the update process of the flag state in the state S12 and the state C11 is performed at normal time or when a disturbance occurs when only the sensor signal input during the period in which the state stays in the state S12 or the state C11 is used. It may not be possible to determine whether or not. Therefore, the level setting unit 13 sets the flag status based on the sensor signal input in a longer period, the history of recognition processing using the sensor signal, and the like in addition to the periods of the states S12 and C11. Perform update processing.
- the signal processing device 2 sets the level of the sensor signal and the monitoring unit that monitors the content of the recognition process using the sensor signal regardless of the state of the state machine, apart from the state machine of FIG. Provided in the section 13.
- This monitoring unit does not affect the recognition process of the recognition unit 7 and continues to monitor the monitoring target.
- the signal processing device 2 refers to each piece of information accumulated in the monitoring unit and performs a flag state update process. That is, it is preferable that the level setting unit 13 collects information for determining whether or not the erroneous detection by the recognition unit 7 is likely to occur regardless of the operations of the parameter adjustment unit 14 and the recognition unit 7. .
- the level setting unit 13 sets the sensitivity level according to the occurrence state of the false detection by the recognition unit 7, thereby adjusting the detection sensitivity and reducing the false detection.
- the signal processing device 2 switches the sensitivity level according to the state of the sensor signal during operation, and sets the parameter according to the sensitivity level, so that even if there is a change in the surrounding environment, the detection sensitivity can be improved. It is possible to balance detection reduction.
- the signal processing device 2 can set a parameter that can suppress erroneous detection when a disturbance occurs, in addition to the parameter that is normally used.
- the detection sensitivity tends to decrease. Therefore, it is normal to operate using normal parameters that prioritize detection sensitivity, and when it is determined that a disturbance has occurred, switching to a parameter for generating a disturbance that prioritizes reduction of false detection reduces the error. Suppress detection.
- the detection sensitivity can be returned to the standard state by switching to the normal parameters.
- the signal processing device 2 can reduce the false detection caused by the movement of the object other than the detection target while balancing the detection sensitivity improvement and the false detection reduction.
- the parameters to be changed by the parameter adjustment unit 14 are not limited to the threshold values E1 and E2 used in the above-described threshold determination process.
- the recognition unit 7 performs recognition processing using multiple regression analysis
- the signal components A2 and A3 are obtained by multiple regression analysis from the data A1 on the time axis of the normalized intensity output from the normalization unit 6. Separate (see FIG. 19A).
- the signal component A2 is a signal component resulting from movement of a person
- the signal component A3 is a signal component resulting from disturbance.
- the signal processing device 2 performs the recognition process by the recognition unit 7 only when the magnitude of the fluctuation per unit time of the extracted detected object signal component A2 is less than the threshold E11 in the predetermined filter bank 5a. Or the recognition result by the recognition part 7 is validated. By setting the threshold value E11, the signal processing device 2 can not output a determination result that seems to be erroneous detection due to disturbance.
- the parameter adjustment unit 14 sets the threshold E11 so that the detection sensitivity is high if the flag is “0”, and if the flag is “1”, The threshold value E11 is set so that the object detection sensitivity becomes low. That is, if the flag is “0”, the parameter adjustment unit 14 sets the adjustment range of the threshold E11 to a relatively high range, and if the flag is “1”, the parameter adjustment unit 14 sets the adjustment range of the threshold E11 to a relatively low range. To do. That is, the parameter adjustment unit 14 sets the threshold value E11 as a setting target parameter.
- the signal processing device 2 recognizes the recognition process by the recognition unit 7 only when the magnitude of the fluctuation per unit time of the intensity of the signal that has passed through the predetermined filter bank 5a (the signal before normalization) is less than the threshold value E21. Or the recognition processing result by the recognition unit 7 may be validated. By setting the threshold value E21, the signal processing device 2 can not output a determination result that seems to be erroneous detection due to disturbance.
- the parameter adjustment unit 14 sets the threshold value E21 so that the detection sensitivity becomes high if the flag is “0” based on the flag state (0 or 1), and if the flag is “1”, The threshold value E21 is set so that the object detection sensitivity is lowered. That is, if the flag is “0”, the parameter adjustment unit 14 sets the adjustment range of the threshold E21 to a relatively high range, and if the flag is “1”, the parameter adjustment unit 14 sets the adjustment range of the threshold E21 to a relatively low range. To do. That is, the parameter adjustment unit 14 sets the threshold value E21 as a parameter to be set.
- the parameter adjustment unit 14 may set a plurality of parameter sets as a setting target in addition to setting only one parameter.
- the recognition unit 7 may have a function of detecting an object by performing recognition processing using a neural network as recognition processing. Thereby, the signal processing device 2 can improve the detection accuracy of the recognition unit 7.
- the signal processing apparatus 2 described above includes a frequency analysis unit 5, a recognition unit 7, a level setting unit 13, and a parameter adjustment unit 14.
- the frequency analysis unit 5 converts a sensor signal corresponding to the movement of the object output from the radio wave sensor 1 (sensor) that receives the radio signal reflected by the object into a signal in the frequency domain, and a plurality of filter banks having different frequency bands It is extracted as a signal every 5a.
- the recognition unit 7 performs a recognition process of detecting an object based on at least one of a frequency distribution of a signal based on the signal for each of the plurality of filter banks 5a and a signal intensity component ratio based on the signal for each of the plurality of filter banks 5a.
- the level setting unit 13 sets a sensitivity level indicating the level of object detection sensitivity in the recognition process.
- the parameter adjustment unit 14 changes a parameter for adjusting the object detection sensitivity in the recognition process. Based on the sensitivity level set by the level setting unit 13, the parameter adjustment unit 14 sets parameters so that the object detection sensitivity is high when the sensitivity level is high, and the object detection sensitivity is low when the sensitivity level is low. Set the parameter so that it is lower.
- the signal processing device 2 adjusts the detection sensitivity improvement and the false detection reduction by the level setting unit 13 setting the sensitivity level according to the occurrence state of the false detection by the recognition unit 7.
- the signal processing device 2 switches the sensitivity level according to the state of the sensor signal, and sets the parameter according to the sensitivity level, thereby improving detection sensitivity and reducing false detection even when the surrounding environment varies. Balance can be taken. Therefore, the signal processing device 2 has an effect of reducing the false detection caused by the movement of the object other than the detection target while balancing the detection sensitivity improvement and the false detection reduction.
- the level setting unit 13 determines that the erroneous detection by the recognition unit 7 is likely to occur, the level setting unit 13 sets the sensitivity level to be low and determines that the erroneous detection by the recognition unit 7 is unlikely to occur. In this case, it is preferable to set the sensitivity level high.
- the signal processing device 2 can set the sensitivity level according to the situation where the erroneous detection occurs.
- the level setting unit 13 can collect information for determining whether or not the erroneous detection by the recognition unit 7 is likely to occur regardless of the operations of the parameter adjustment unit 14 and the recognition unit 7. preferable.
- the signal processing device 2 can determine whether or not the erroneous detection is likely to occur regardless of the operations of the parameter adjustment unit 14 and the recognition unit 7.
- the level setting unit 13 switches the sensitivity level when the recognition unit 7 is not performing the recognition process, and does not switch the sensitivity level when the recognition unit 7 is performing the recognition process.
- the signal processing device 2 can suppress the occurrence of malfunction when the recognition unit 7 is performing the recognition process.
- the recognizing unit 7 performs the recognizing process or validates the result of the recognizing process when the sum of the signal intensities of the plurality of filter banks 5a is equal to or larger than the first threshold, and the parameter adjusting unit 14 It is preferable to change the first threshold value.
- the signal processing device 2 can improve the detection accuracy of the recognition unit 7.
- the recognizing unit 7 extracts a signal component caused by the motion of the object from the signal intensity for each of the plurality of filter banks 5a.
- the recognition unit 7 performs a recognition process when the magnitude of fluctuation of the extracted signal component per unit time is less than the second threshold in at least one filter bank 5a among the plurality of filter banks 5a, or It is preferable to validate the result of the recognition process.
- the parameter adjustment unit 14 preferably changes the second threshold value as a parameter.
- the signal processing device 2 can improve the detection accuracy of the recognition unit 7.
- the recognition unit 7 performs a recognition process or recognizes when the magnitude of fluctuation per unit time of the signal strength of at least one filter bank 5a among the plurality of filter banks 5a is less than the third threshold. It is preferable to validate the processing result.
- the parameter adjusting unit 14 preferably changes the third threshold value as a parameter.
- the signal processing device 2 can improve the detection accuracy of the recognition unit 7.
- the signal processing device 2 includes a normalization unit 6.
- the normalization unit 6 includes a total sum of signal strengths extracted by the frequency analysis unit 5 or a total sum of signal strengths that have passed through a predetermined number of filter banks 5a among the plurality of filter banks 5a.
- the intensity of the signal that passed through is normalized and output as a normalized intensity.
- the recognizing unit 7 performs a recognition process of detecting an object based on at least one of a frequency distribution determined from the normalized intensity for each of the plurality of filter banks 5a output from the normalizing unit 6 and a component ratio of the normalized intensity.
- the signal processing device 2 can reduce false detection caused by the movement of an object other than the detection target.
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Abstract
Description
m11=(s1+s2+s3+s4+s5)/5
となる。
n11=m11/(m11+m21+m31+m41+m51)
の演算により求められる。
m1=(m10+m11+m12)/3
となる。
m2=(m20+m21+m22)/3
m3=(m30+m31+m32)/3
m4=(m40+m41+m42)/3
m5=(m50+m51+m52)/3
となる。
L1=m1-b1
となる。
L2=m2-b2
L3=m3-b3
L4=m4-b4
L5=m5-b5となる。
L1=m1(t1)-m1(t0)
L2=m2(t1)-m2(t0)
L3=m3(t1)-m3(t0)
L4=m4(t1)-m4(t0)
L5=m5(t1)-m5(t0)
となる。
bi=(bi-1+bi+1)/2
からなる推定式により求めた値としている。
m1=m10+m20+m30
m2=m40+m50
となる。また、図8Bでは、
m1=m11+m21+m31
m2=m41+m51
となる。
上述の信号処理装置2は、周波数分析部5と認識部7とレベル設定部13とパラメータ調整部14とを備える。周波数分析部5は、物体で反射した無線信号を受信する電波センサ1(センサ)から出力される物体の動きに応じたセンサ信号を周波数領域の信号に変換し、周波数帯域の異なる複数のフィルタバンク5a毎の信号として抽出する。認識部7は、複数のフィルタバンク5a毎の信号に基づく信号の周波数分布と、複数のフィルタバンク5a毎の信号に基づく信号強度の成分比との少なくとも一方により物体を検出する認識処理を行う。レベル設定部13は、認識処理における物体の検出感度の高低を示す感度レベルを設定する。パラメータ調整部14は、認識処理における物体の検出感度を調整するパラメータを変化させる。パラメータ調整部14は、レベル設定部13が設定した感度レベルに基づいて、感度レベルが高い場合、物体の検出感度が高くなるようにパラメータを設定し、感度レベルが低い場合、物体の検出感度が低くなるようにパラメータを設定する。
Claims (8)
- 物体で反射した無線信号を受信するセンサから出力される前記物体の動きに応じたセンサ信号を周波数領域の信号に変換し、周波数帯域の異なる複数のフィルタバンク毎の信号として抽出する周波数分析部と、
前記複数のフィルタバンク毎の信号に基づく信号の周波数分布と、前記複数のフィルタバンク毎の信号に基づく信号強度の成分比との少なくとも一方により前記物体を検出する認識処理を行う認識部と、
前記認識処理における前記物体の検出感度の高低を示す感度レベルを設定するレベル設定部と、
前記認識処理における前記物体の検出感度を調整するパラメータを変化させるパラメータ調整部とを備え、
前記パラメータ調整部は、前記レベル設定部が設定した前記感度レベルに基づいて、前記感度レベルが高い場合、前記物体の検出感度が高くなるように前記パラメータを設定し、前記感度レベルが低い場合、前記物体の検出感度が低くなるように前記パラメータを設定する
ことを特徴とする信号処理装置。 - 前記レベル設定部は、前記認識部による誤検出が発生しやすい状況であると判断した場合に、前記感度レベルを低く設定し、前記認識部による誤検出が発生しにくい状況であると判断した場合に、前記感度レベルを高く設定することを特徴とする請求項1記載の信号処理装置。
- 前記レベル設定部は、前記認識部による誤検出が発生しやすい状況であるか否かを判断するための情報を、前記パラメータ調整部および前記認識部の動作に関わらず収集することを特徴とする請求項2記載の信号処理装置。
- 前記レベル設定部は、前記認識部が前記認識処理を行っていないときに前記感度レベルを切り替え、前記認識部が前記認識処理を行っているときには前記感度レベルを切り替えないことを特徴とする請求項1乃至3いずれか記載の信号処理装置。
- 前記認識部は、前記複数のフィルタバンクの各信号強度の総和が第1の閾値以上である場合、前記認識処理を行う、もしくは前記認識処理の結果を有効とし、
前記パラメータ調整部は、前記パラメータとして前記第1の閾値を変化させる
ことを特徴とする請求項1乃至4いずれか記載の信号処理装置。 - 前記認識部は、前記複数のフィルタバンク毎の信号強度から前記物体の動きに起因した信号成分を抽出し、抽出された前記信号成分の単位時間当たりの変動の大きさが、前記複数のフィルタバンクのうち少なくとも1つのフィルタバンクにおいて第2の閾値未満である場合、前記認識処理を行う、もしくは前記認識処理の結果を有効とし、
前記パラメータ調整部は、前記パラメータとして前記第2の閾値を変化させる
ことを特徴とする請求項1乃至4いずれか記載の信号処理装置。 - 前記認識部は、前記複数のフィルタバンクのうち少なくとも1つのフィルタバンクの信号強度の単位時間当たりの変動の大きさが第3の閾値未満である場合、前記認識処理を行う、もしくは前記認識処理の結果を有効とし、
前記パラメータ調整部は、前記パラメータとして前記第3の閾値を変化させる
ことを特徴とする請求項1乃至4いずれか記載の信号処理装置。 - 前記周波数分析部により抽出された信号の強度の総和もしくは前記複数のフィルタバンクのうち所定数のフィルタバンクを通過した信号の強度の総和で、前記複数のフィルタバンクそれぞれを通過した信号の強度を規格化し規格化強度として出力する規格化部を備え、
前記認識部は、前記規格化部から出力される前記複数のフィルタバンク毎の規格化強度から決まる周波数分布と前記規格化強度の成分比との少なくとも一方により前記物体を検出する認識処理を行う
ことを特徴とする請求項1乃至7いずれか記載の信号処理装置。
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JP2020193904A (ja) * | 2019-05-29 | 2020-12-03 | 日本電気株式会社 | 目標信号分離装置、パッシブレーダー装置および目標信号分離方法 |
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DE102020130881A1 (de) * | 2020-11-23 | 2022-05-25 | Valeo Schalter Und Sensoren Gmbh | Empfangssignal-Verarbeitungseinrichtung einer Detektionsvorrichtung zur Überwachung wenigstens eines Überwachungsbereichs, Detektionsvorrichtung und Verfahren zum Betreiben einer Detektionsvorrichtung |
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