Luminaire and corresponding method

Abstract

Some embodiments relate to a motion detector (100) configured to signal process a motion signal to obtain a plurality of motion components, the motion components relating to a direction and a speed of motion in an environment, cancel two of the motion components corresponding to motion having opposite directions, and detect motion in the environment from the non-cancelled motion components.

Description

Technical Field

[0001] This invention relates to lighting fixtures, motion detection methods, and computer-readable media. Background Technology

[0002] Reliable motion detection is important in many fields. For example, motion detection is used in lighting systems to control illumination. Motion detectors can prevent lights from turning on when no one is present. Other applications include burglar alarms and office occupancy detection, for example, for office management.

[0003] Unfortunately, motion sensing presents numerous challenges. One problem with motion sensors is their sensitivity to certain types of narrow-band noise, sometimes referred to as hum or buzz-type noise. In particular, Doppler-based sensors are susceptible to false alarms caused by hum noise.

[0004] Known motion sensors are described in Korean patent application KR20160141503, "Apparatus and Method for Driving a Lamp." This Korean patent application discloses a lighting driving device for driving a lighting device equipped with a motion sensing component. The device automatically controls the lighting based on whether motion is detected.

[0005] The motion detection unit is a microwave (RF) Doppler sensor that detects motion by detecting waves generated by a wave source using the Doppler effect. The motion sensing unit can detect not only the motion of objects but also vibrations occurring in the surrounding environment. Therefore, there is a problem where the light might be turned on even when only vibration occurs without any motion.

[0006] Figure 1 of the cited patent illustrates a known lighting driving device. In addition to the motion sensing unit 12, the known device also includes a vibration sensing unit 11 for sensing vibrations.

[0007] The motion sensing unit 12 is an RF Doppler sensor that uses microwaves (RF) to sense motion using the Doppler effect and outputs a motion sensing signal of corresponding magnitude. The vibration sensing unit 11 is a microelectromechanical system (MEMS) that measures acceleration and senses vibration, and outputs an electrical signal of corresponding magnitude as a vibration sensing signal.

[0008] When the motion detection unit 12 detects motion, the controller illuminates the lighting device 4, but only illuminates it when no vibration is detected. This prevents the lighting device 4 from turning on when vibration is detected.

[0009] US2018 / 263502A1 discloses the use of radar signals to estimate heart rate, heart rate variability, respiratory rate, and / or respiratory rate variability in humans or other animals. Respiratory motion can be estimated from the radar baseband output signal. The estimated respiratory signal can then be subtracted from the radar signal in the time domain and further enhanced using digital signal processing techniques to produce an estimate of heartbeat impulses. Summary of the Invention

[0010] Known systems have several drawbacks. First, they require a separate vibration sensor in addition to the motion sensor. This increases the parts list, system complexity, and cost. Second, motion cannot be detected as long as vibration is detected. A buzzing sound may be intermittent and may only last a few seconds, but the inventors have observed that buzzing-type noise can also last for hours. Such a continuous buzzing sound renders known systems inoperable because no motion is detected during the continuous buzzing, and therefore no lights are turned on. Alternatively, the vibration threshold can be set at a high level, thus the risk of false alarms caused by one or more buzzing noise sources remains. Third, known systems only detect mechanical vibrations. However, the inventors have observed that buzzing noise can also originate from electrical sources.

[0011] To address these and other issues, a luminaire incorporating a motion detector is proposed. The motion detector includes:

[0012] - A motion sensor interface configured to receive motion signals from a motion sensor, the motion signals being correlated with the motion of objects in the motion sensor's environment.

[0013] - Processor system, configured as follows

[0014] -Signal processing is performed on the motion signal to obtain multiple motion components, which are related to the direction and velocity of motion in the environment.

[0015] - Eliminate two motion components that correspond to motions with opposite directions from the motion components.

[0016] - Detects the motion of objects in the environment by detecting motion components that are never eliminated. The luminaire can be connected to the light-emitting element and configured to control the light-emitting element by relying at least on the motion detector.

[0017] The advantage of motion detection is that it eliminates the need for a separate vibration sensor. Instead, humming noise can be removed from the output of the motion sensor. For example, in an embodiment, determination may include determining the energy in the remaining frequency bin. For instance, if the determined energy exceeds a threshold, the environment can be classified as motion. The frequency bin can be implemented as coefficients generated by frequency domain transformations (e.g., FFT, DFT, etc.). The frequency bin is called a bin because it actually corresponds to a narrow range of frequencies; for a Doppler sensor, the frequency bin correspondingly corresponds to a narrow range of velocities in the region surrounding the sensor.

[0018] The inventors' insight is that vibrations in the environment consist of two motions in opposite directions. By removing the motion component with this profile, vibration noise is reduced.

[0019] In this embodiment, the motion signal includes a first channel (I) and a distinct second channel (Q), both of which are correlated with motion in the motion sensor environment. Accessing both channels is one way to determine the direction of motion from the motion sensor.

[0020] For example, by performing a frequency transform, motion components corresponding to frequencies can be obtained, such as both positive and negative frequencies. Typically, motion toward and away from the sensor can be represented by positive and negative frequencies, respectively, or vice versa. Therefore, noise cancellation can include subtracting the motion component corresponding to the positive frequency from the motion component with the corresponding negative frequency. Frequency transforms are typically performed using Fourier transforms (e.g., FFT), but an alternative is to apply wavelet decomposition to obtain the motion components.

[0021] Due to limitations in motion sensors, real motion, such as non-humming noise like a walking person, may contribute to one or more positive frequency motion components, but unintentionally also contribute to the corresponding negative frequencies. Subtracting the motion components can reduce the energy in the positive signal, potentially increasing the chance of false alarms (e.g., the detector fails to detect motion even when it is present). This can be avoided by applying a correction factor to compensate for sensor limitations. For example, in an embodiment, the correction factor can be applied to the motion components before subtracting them. Interestingly, symmetricalizing the application of the correction factor may result in a factor that still eliminates humming noise.

[0022] One aspect of the present invention relates to a motion detection method.

[0023] Embodiments of this method can be implemented on a computer as a computer-implemented method, or in dedicated hardware, or a combination of both. Executable code for embodiments of the method can be stored on a computer program product. Examples of computer program products include memory devices, optical storage devices, integrated circuits, servers, online software, etc. Preferably, the computer program product includes non-transitory program code stored on a computer-readable medium for executing embodiments of the method when the program product is run on a computer.

[0024] In an embodiment, the computer program includes computer program code that, when run on a computer, is adapted to perform all or part of the steps of an embodiment of the method. Preferably, the computer program is embodied on a computer-readable medium. Attached Figure Description

[0025] Further details, aspects, and embodiments of the invention will be described by way of example only with reference to the accompanying drawings. Elements in the drawings are shown for simplicity and clarity and are not necessarily drawn to scale. In the drawings, elements corresponding to those already described may have the same reference numerals. In the drawings,

[0026] Figure 1a An example of an embodiment of a motion detector is illustrated schematically.

[0027] Figure 1b An example of an embodiment of the luminaire is illustrated schematically.

[0028] Figure 1c An example of an embodiment of a lighting system is illustrated schematically.

[0029] Figure 2a A graph showing the magnitude of the FFT transform of a single-channel motion sensor signal is displayed.

[0030] Figure 2b A graph showing the magnitude of the FFT transform of the dual-channel motion sensor signal is displayed.

[0031] Figure 2c A graph showing the magnitude of the FFT transform of a single-channel motion sensor signal is displayed.

[0032] Figure 2d A graph showing the magnitude of the FFT transform of the dual-channel motion sensor signal is displayed.

[0033] Figure 3 An example of an embodiment of a dual-channel motion sensor is schematically shown.

[0034] Figure 4a A graph showing the magnitude of the FFT transform of the dual-channel motion sensor signal is displayed.

[0035] Figure 4b A graph showing the magnitude of the FFT transform with noise cancellation is provided.

[0036] Figure 4c A graph showing the magnitude of the FFT transform of the dual-channel motion sensor signal is displayed.

[0037] Figure 4d A graph showing the magnitude of the FFT transform with noise cancellation is provided.

[0038] Figure 5a An example of an embodiment of a motion detector is illustrated schematically.

[0039] Figure 5b An example of an embodiment of a motion detector is illustrated schematically.

[0040] Figure 6 An example of an embodiment of the motion detector method is illustrated schematically.

[0041] Figure 7a A computer-readable medium having a writable portion including a computer program, according to an embodiment, is illustrated schematically.

[0042] Figure 7b A representation of a processor system according to an embodiment is shown schematically.

[0043] Figures 1a-5b List of reference numerals in figures 7a-7b:

[0044] 100, 101, 102 Motion detectors

[0045] 110 motion sensor

[0046] 112 Sensors

[0047] 114 Signal Processing Unit

[0048] 120 signal input terminal

[0049] 130 Frequency Domain Converter

[0050] 140, 141 Noise Cancellation Units

[0051] 150 motion detection units

[0052] 162 Correction Term Estimator

[0053] 164 Correction Item Memory

[0054] 170 Lighting Fixtures

[0055] 171 Lighting System

[0056] 172 Light-emitting element

[0057] 173 Computer Networks

[0058] 175 Lighting Controller

[0059] 210, 220 Spectrum

[0060] 230, 240 Spectrum

[0061] Peaks 211 and 213

[0062] 212 positive frequency

[0063] 214 negative frequency

[0064] 221 Peak

[0065] 223 No peak

[0066] 411, 413 Buzzing noise-related peak values

[0067] 412 Motion-related peak value

[0068] 414 No peak

[0069] 500 Dual-Channel Motion Sensor

[0070] 510 Transmission Signal Generator

[0071] 511 transmitter

[0072] 512 receiver

[0073] 520 phase shifter

[0074] 530 mixer

[0075] 540 mixer

[0076] 550 low-pass filter

[0077] 560 Low-pass Filter

[0078] 551 Q signal

[0079] 561 I signal

[0080] 1000 computer-readable media

[0081] 1010 writable portion

[0082] 1020 Computer Program

[0083] 1100 equipment

[0084] 1110 System Bus

[0085] 1120 processor

[0086] 1130 Memory

[0087] 1140 User Interface

[0088] 1150 Communication Interface

[0089] 1160 storage device

[0090] 1161 Operating System

[0091] Instructions 1162, 1163, and 1164. Detailed Implementation

[0092] While the invention may allow for a variety of different embodiments, one or more specific embodiments are shown in the accompanying drawings and will be described in detail herein. It should be understood that this disclosure is to be regarded as an example of the principles of the invention and is not intended to limit the invention to the specific embodiments shown and described.

[0093] Hereinafter, for the sake of understanding, the elements of the embodiments will be described in operation. However, it will be apparent that the various elements are arranged to perform the functions described as being performed by them.

[0094] Furthermore, the invention is not limited to these embodiments, and the invention lies in each novel feature or combination of features described herein or recited in mutually different dependent claims.

[0095] Figure 1a An example of an embodiment of the motion detector 100 is illustrated schematically.

[0096] Motion detectors can be used in a variety of applications, with lighting being particularly advantageous. For example, Figure 1b An example embodiment of luminaire 170 is schematically illustrated. Luminaire 170 may include a motion detector 100 and an illumination element 172. For example, the illumination element may be configured to radiate light when motion is detected by the motion detector 100. The illumination element may be one or more LEDs. For example, Figure 1cAn example embodiment of a lighting system 171 is illustrated schematically. The lighting system 171 includes luminaires 170 (typically multiple luminaires), motion detectors 100 (typically multiple motion detectors), and a lighting controller 175. The lighting controller 175 is configured to receive motion signals, such as quiet / motion classification, from the motion detectors(s), and determine lighting control signals based on these signals. The lighting control signals are sent to one or more luminaires, which then illuminate according to the control signals. One or more motion detectors may be incorporated into the luminaires, but this is not required. Communication between the motion detectors, the lighting controller, and the luminaires can be via a digital communication network (e.g., a computer network).

[0097] For example, various devices in the lighting system 171 can communicate with each other via a computer network 173. The computer network can be the Internet, an intranet, a LAN, a WLAN, etc. Computer network 173 can be the Internet. The computer network can be wholly or partially wired, and / or wholly or partially wireless. For example, the computer network can include an Ethernet connection. For example, the computer network can include wireless connections such as Wi-Fi, ZigBee, etc. Devices include connection interfaces arranged to communicate with other devices in the lighting system 171 as needed. For example, the connection interface can include connectors, such as wired connectors, such as Ethernet connectors, optical connectors, etc., or wireless connectors, such as antennas, such as Wi-Fi, 4G, or 5G antennas. For example, motion detector 100, lighting controller 175, and luminaire 170 can each include a communication interface. Computer network 173 can include additional components such as routers, hubs, etc.

[0098] The operation of the motion detector 100 can be implemented in processor circuitry, an example of which is shown herein. For example, Figure 1a The diagram illustrates functional units that can be motion detectors and, for example, processor circuitry. Figure 1a It can be used as a blueprint for the possible functional organization of the processor circuitry. The processor circuitry is not related to... Figure 1a The cells are displayed separately. For example, Figure 1a The functional units shown can be implemented, in whole or in part, as computer instructions stored at the motion detector 100, for example, in the electronic memory of the motion detector 100, and can be executed by the microprocessor of the motion detector 100. In a hybrid embodiment, the functional units are implemented in part in hardware, for example as a coprocessor, such as a signal coprocessor, and in part in software stored and executed on the motion detector 100.

[0099] Besides lighting control, motion detectors have other applications. For example, they can be used in burglar alarms. Motion sensors can also be used to detect office occupancy, which can then be used to manage offices, such as suggesting vacant offices for use or reporting office occupancy over time.

[0100] like Figure 1a As shown, motion detector 100 includes motion sensor 110; however, this is not mandatory. Motion detector 100 may use an external motion sensor. Some signal processing may be performed in the external motion sensor or in the motion detector itself. In an embodiment, motion sensor 110 may be a component of motion detector 100. Motion sensor 110 is configured to generate sensor signals for the motion detector.

[0101] There are various options for motion sensors. For example, motion sensor 110 can be a Doppler motion sensor, a microwave sensor, or an ambient light sensor, etc. As an example of excitation, an embodiment for a Doppler sensor will be described below. However, it should be noted that the motion detector can be combined with any motion sensor that has noise problems (especially buzzing noise).

[0102] In one embodiment, motion sensor 110 may include sensor 112 and processing unit 114. Processing unit 114 may perform preprocessing on the signal before it is further processed by the remainder of motion detector 100. Processing unit 114 is optional.

[0103] For example, in one embodiment, motion sensor 110 may be of the Doppler type. For instance, a Doppler sensor may be configured to detect the motion or velocity of a moving object using the Doppler principle. Sensor 112 may be configured to transmit a signal, such as a microwave signal. For instance, the transmitted signal may have a frequency from 5 to 30 GHz and / or from 30 to 100 GHz, or lower or higher frequencies are also possible. Examples of signal frequencies include 5.8 GHz, 24 GHz, and 60 GHz. For instance, the transmitted signal may have a frequency in the ultra-high frequency band (SHF) or the extremely high frequency band (EHF).

[0104] Sensor 112 can be configured to receive a signal. The shift in frequency signal is related to the velocity of the moving object reflecting the transmitted signal relative to the sensor. For example, one processing method in a Doppler sensor is to calculate the product of the transmitted and received signals and apply a low-pass filter to the multiplied signal. The resulting signal including the frequency shift can be represented by a geometric function. For example, processing unit 114 can be configured to multiply the transmitted and received signals and apply a low-pass filter.

[0105] The resulting signal is provided to the signal input terminal 120 of the motion detector 100. For example, the signal input terminal 120 may be an internal input terminal. The signal input terminal 120 may also be an input port, such as an electronic input port or a digital input port, such as an API. For example, in an embodiment, the sensor signal from the motion sensor 110 received at the signal input terminal 120 may be a signal in which the frequency component corresponds to a Doppler frequency shift and therefore corresponds to the velocity of an object in the area surrounding the motion sensor 110. In an embodiment, this signal is a signal reflected from an object in the surrounding area. In the latter case, further Doppler processing may be performed after the signal is received at the signal input terminal.

[0106] In this embodiment, signal input 120 is configured to receive a motion signal from motion sensor 110. The motion signal is correlated with motion in the motion sensor environment. Specifically, the motion signal is arranged such that the direction of motion in the environment is correlated with the motion signal. The correlation does not need to be perfect. For example, it is sufficient if the correlation is only related to the projection of the direction of motion. For example, the direction of motion can be directed to a line from the moving object toward motion sensor 110. For example, some noise cancellation can be achieved if two equal motions having opposite directions (e.g., relative to each other) can be distinguished from each other in the motion signal. In this embodiment, the motion signal is a Q and I time-domain signal.

[0107] In this embodiment, the motion sensor 110 is a so-called dual-channel sensor; for example, the motion signal comprises two channels, each associated with motion in the environment. Because two channels are available, more information about the direction of motion in the environment can be obtained. For example, in this embodiment, the motion signal includes a first channel (I) and a distinct second channel (Q), both associated with motion in the motion sensor's environment.

[0108] In an embodiment, the first channel and the second channel are obtained by mixing the received reflected signal with a first mixed signal and a second mixed signal, respectively. The first mixed signal and the second mixed signal have a phase difference of at least 30 degrees, preferably at least 70 degrees, and more preferably 90 degrees.

[0109] For example, the motion sensor could be a dual-channel Doppler microwave sensor. The sensor's output may have already been processed into I and Q channels by the signal processing unit 114, but this is not necessary; for example, the motion sensor could derive the raw received signal and perform signal processing in the motion sensor 110.

[0110] Figure 3 An example embodiment of a dual-channel motion sensor 500 is illustrated schematically. For example, the dual-channel motion sensor 500 can be used as a motion sensor. Figure 3Only one architecture for a motion sensor is shown; other options are possible.

[0111] Figure 3 A transmission signal generator 510 is shown, configured to generate a signal, such as a sine wave, for transmission via a transmitter 511. The transmitted signal is reflected by an object in the environment of the dual-channel sensor 500. The reflection is received in a receiver 512. The received signal is mixed with the transmitted signal in a mixer 540 and guided through a low-pass filter 560 to obtain an in-phase signal, such as an I signal 561. The transmitted signal also undergoes a phase shift, typically more than 90 degrees. The received signal is mixed with the phase-shifted transmitted signal in a mixer 530 and guided through a low-pass filter 550 to obtain a quadrature signal, such as a Q signal 551. Typically, the phase shifter 520 is shifted by 90 degrees, but this can vary. In particular, the shift may be slightly more or less due to inaccuracies. For example, the phase shift of the phase shifter 520 can be between 85 and 95 degrees. A 270-degree shift is considered equivalent to a 90-degree shift. Non-ideal components, such as amplifiers and the phase shifter 520, may also introduce slight variations in signal amplitude. Due to these factors, these two channels may deviate slightly from perfect I and Q channels. Assuming the deviation is small enough relative to the frequency bin size of the subsequent frequency transformation, this will still allow for at least some degree of noise cancellation. Inaccuracies in the motion sensor and its signal processing can be corrected. Such corrections will be explained further below and are optional.

[0112] The dual-channel motion sensor 500 may have many variations. For example, mixing and filtering can be done analog and / or digitally. For example, the dual-channel motion sensor 500 may include one or more antennas. Mixing can be implemented as a multiplication between two signals. For example, in one embodiment, the original received signal is mixed with a first signal and a second signal that are out of phase. Some components may be reused, etc.

[0113] Return to Figure 1a The Q signal 551 and the I signal 561 can be received by the motion detector 100 in the signal input terminal 120.

[0114] The motion detector 100 includes a frequency domain converter 130, a noise cancellation unit 140, and a motion detection unit 150. The frequency domain converter 130 converts the received signal from the time domain to the frequency domain. For example, the converter 130 can perform a Fourier transform. For example, the converter 130 can perform a Discrete Fourier Transform (DFT). If necessary, the converter 130 can first perform an analog-to-digital conversion, such as an ADD conversion, before performing the conversion to the frequency domain.

[0115] In an embodiment, the signal processing of the frequency domain converter 130 includes transforming the motion signal from the time domain to the frequency domain to obtain multiple motion components. Each motion component represents motion relative to the sensor at a specific speed and direction. The motion components may further represent motion at a specific distance relative to the sensor. Typically, the motion components are sensitive to a range of speeds. Preferably, motion in the opposite direction relative to the sensor corresponds to different motion components.

[0116] Multiple motion components can be frequency transformation coefficients of a motion signal, such as FFT, DFT, etc. For example, multiple motion components can be the frequency compartment of a frequency domain converter. In an embodiment, a frequency domain transformation is performed on a combination of two channels, such as a combination of I and Q channels. Specifically, the transformation can be a complex transformation; for example, a frequency transformation can be applied to a complex combination (I+jQ), where j represents a complex unit. The result of the frequency transformation can be a complex signal. For example, the complex amplitude of the frequency compartment can be obtained.

[0117] In an embodiment, the motion signal received at signal input 120 is divided into multiple parts, such as multiple parts having a predetermined number of time-domain samples. Frequency conversion can be performed on each part. As a result, a so-called frequency bin is obtained. A frequency bin is the amplitude of a frequency range present in the received signal. For example, a frequency bin may represent a frequency range of 40-42 Hz. The frequency range corresponding to the frequency bin may be, for example, about 2 Hz or more or less, such as in the range from 0.5 to 5 Hz. The size of the frequency bin can be considered as the absolute value of the amplitude. In an embodiment, signal processing can be configured to detect motion components within a time period or time segment. This time period may be one second, half a second, etc. In an embodiment, the time period is less than 30 seconds.

[0118] For example, frequency conversion can be performed after a predetermined number of time-domain samples are obtained each time. For example, frequency conversion can be performed once every 24 time-domain samples. For example, in this embodiment, a 5.8 GHz sensor is combined with 24 time-domain samples for each time segment.

[0119] For example, sampling can be performed at a frequency of 250 Hz, and an FFT of length 128 points can be performed every 24 new samples. In this case, the FFTs overlap. For optical switches, it is best to report motion quickly, for example, within 0.5 seconds. In the example above, some FFT is used to make a decision. For other cases, more time may be needed: for example, when motion is triggered when the light is on, or for occupancy detection.

[0120] Therefore, the frequency bin exhibits evolution over time; an increase in the frequency bin, for example, an increase in the size of a specific frequency range, can correspond to an increase in a specific velocity in the area surrounding the sensor. An increase in the frequency bin can indicate motion in that area. High-pass or low-pass filters, or both, can be applied to the signal or frequency bin to eliminate frequencies that are too high or too low to be usable.

[0121] In embodiments of the frequency domain converter, the motion signal is processed to obtain multiple motion components. For example, the multiple motion components may be coefficients of a frequency transformation of I+jQ. The motion components are related to the direction and velocity of motion in the environment. In particular, two motions with opposite directions contribute to two distinct motion components corresponding to motions with opposite directions.

[0122] Specifically, motions with opposite directions contribute to different motion components, for example, to motion components associated with positive and negative frequencies. In practice, this will be the case even if the motion direction is detected relative to the observation direction of the motion sensor (e.g., the observation direction projected onto the motion sensor). In the embodiment, motions with opposite directions contribute to different motion components among multiple motion components.

[0123] Motion sensors only need to measure the velocity toward or away from the sensor; this can be called projected velocity. Interestingly, the vibrating object hardly changes its position, making the magnitudes of the velocities toward and away from the sensor equal.

[0124] Terms such as opposite directions and equal velocities should be understood as implying that they are within a threshold. The threshold can be implicit. For example, if two motions contribute to opposite Fourier coefficients, they can be considered to be in opposite directions.

[0125] In this embodiment, multiple motion components correspond to a frequency of the frequency transformation. In particular, for dual-channel I and Q sensors, motions in opposite directions contribute to motion components with the same frequency but opposite signs.

[0126] Figure 2a A graph showing the magnitude of the FFT transform of a single-channel motion sensor signal is displayed. Figure 2a The image shows the spectrum obtained when a person walks towards the sensor. Positive frequencies are shown at 212, and negative frequencies at 214. In this example, a single-channel motion sensor is used, where the motion signal does not contain information about the direction of motion. Specifically, Figure 2a This was obtained by performing a real-valued FFT on only the I-channel data. The resulting motion components do not provide directional information. Note that the FFT values ​​are repeated after N / 2 FFT bins.

[0127] Peak 211 in spectrum 210 corresponds to the movement of the pedestrian. However, the peak repeats at 213, indicating a lack of sensitivity to the direction of movement.

[0128] Figure 2b A graph showing the magnitude of the FFT transform of the dual-channel motion sensor signal is presented. Figure 2b The image shows the spectrum obtained as a person approaches the sensor. In this example, a dual-channel motion sensor is used, where the motion signal contains information about the direction of movement. Specifically, Figure 2b This was obtained by performing a complex FFT on the I and Q channel data. The resulting motion components do indeed provide directional information. Note that the FFT values ​​do not repeat after N / 2 FFT bins. Figure 2b The size of the frequency bin is displayed.

[0129] Peak 221 shown in spectrum 220 corresponds to the movement of the pedestrian. The peak does not repeat at the negative frequency 223, indicating a lack of sensitivity to the direction of movement.

[0130] Figure 2c and 2d This further illustrates the sensitivity to the direction of motion. Figure 2c and 2d and Figure 2a and 2b Similar to the previous case, except the person is walking away from the sensor. In the same situation, the spectrum 230 of the single-channel sensor shows repeating peaks. However, the spectrum 240 of the dual-channel sensor shows a single peak. Figure 2c Unlike before, the peak is now located at a negative frequency, indicating that the motion is moving away from the sensor rather than towards it.

[0131] The motion detector 100 includes a noise cancellation unit 140 that utilizes this difference. The noise cancellation unit 140 is configured to eliminate two motion components in the motion components that correspond to motions having opposite directions.

[0132] For example, a motion component corresponding to a specific frequency can be subtracted from motion components with the same frequency but opposite signs to eliminate motion components corresponding to motions with opposite directions. For example, suppose array F + [ i ] indicates a motion component pointing towards the sensor, exponent i Distributed across the motion components. For example, for two motion components F with two different values ​​of the exponent i. + [ i 0] and F + [ i1] This may be related to motion at different speeds, although they are all pointing towards the sensor. Note that the actual motion in the environment does not need to be pointing towards the sensor; for example, the direction component can be represented in the motion component, such as by projecting the actual motion direction onto a line from the moving object to the sensor. Assume a second array F - [ i ] indicates a motion component moving away from the sensor, exponent i Distributed across the motion components. For example, the motion component F + [ i ] and F - [ i [ ] can represent motions with the same velocity but in different directions relative to the sensor. To eliminate vibratory motion, such as so-called humming noise, a new array F[ can be calculated. i ]=F + [ i ]-F - [ i Typical vibrational motion has a very small positional change, and the velocities toward and away from the sensor are equal. Note that any orthogonal components related to the sensor can be ignored. In array F, a non-vibrating moving object, especially a moving object such as a walking person, has a relative position to F. + One or more values ​​in the array contribute, but not to F. - The array contributes nothing, and vice versa. However, a vibrating object will contribute to F. + and F - Both the array and the oscillator contribute, and in fact, they usually do so in the same way. By subtracting these two components, the contribution of the vibrating object to the motion component is eliminated, but not for walking motion.

[0133] There may be many variations. For example, array F + F - F and F can be represented in different ways. In particular, array F + and F - It can be represented in a single array. For example, array values ​​from 0 to N / 2 can represent positive frequencies, while array entries from N / 2 to N can represent negative frequencies. If the amplitude signs at positive and negative frequencies are different, this can be resolved by using magnitude, such as F[ i ]=|F + [ i ]|-|F - [ i ]|, ignoring the imaginary or real part, by removing the sign from the imaginary and real parts, for example, mapping all magnitudes to the same quadrant, etc.

[0134] This method can be improved in several ways. For example, it can correct for phase differences other than 90 degrees, or for amplitude differences between two channels, such as those caused by imperfect components. This will be further elaborated below.

[0135] Complex numerical calculations are unnecessary, especially after frequency transformation. For example, F can be replaced with their magnitudes. + and F - The magnitude of the amplitude. For example, in the above notation, F[ can be calculated. i ]=|F + [ i ]|-|F - [ i Interestingly, if the buzzing and the movement result in an increase in the frequency of the same chamber, then subtraction can even reduce the buzzing.

[0136] Finally, the motion detection unit 150 can detect motion in the environment. For example, the motion detector can be configured to detect motion in the environment from motion components that have never been eliminated. For example, motion detection can include determining the energy in the uneliminated motion components. If the determined energy exceeds a threshold, the environment can be classified as motion. For example, the motion detection unit 150 can be configured to detect motion from motion components F[ i ]=F + [ i ]-F - [ i Detecting motion in, for example, by analyzing |F[ i ]| 2 Sum.

[0137] Motion detection can be performed on a per-frequency-barrel basis. This has the advantage of being able to use different motion thresholds for different frequencies. Detection can be performed after noise removal, for example, by subtracting all positive frequencies from all negative frequencies. Detection can also be done together. For example, one can decide whether each elevated frequency bar corresponds to motion or a buzzing sound; in the former case, it is referred to as motion. The presence or absence of an elevated frequency bar at the opposite frequency can then be used as a factor in the presence or absence of noise. However, other factors can also be considered. For example, real motion typically results in multiple consecutively elevated frequency bars, while buzzing noise typically only raises one or a few, such as two frequency bars. After each frequency bar is identified, motion detection can be determined based on identifying the frequency bars associated with the motion; for example, by summing the energy in the frequency bars that invoke the motion.

[0138] For example, motion detection may include detecting frequency bins with increased size. For each frequency bin with a higher size, for example, it can be said that motion has been observed in that bin compared to a threshold for that bin. In addition to the hum cancellation features of the signal processing described herein, other signal processing can be performed, and in particular, other algorithms can be applied to detect hum noise and / or real motion. For example, for each run of the motion algorithm, each increased frequency bin can be checked against the hum condition. Only frequency bins that invoke motion and / or are not identified as hum can contribute to motion detection. Note that real motion can trigger motion invocation even if the hum condition is present in one or more frequency bins. In an embodiment, for each time segment, the motion detector may check the increased size and motion of all frequency bins.

[0139] After the conversion from the time domain to the frequency domain, the motion detection unit 150 detects motion from the frequency bin (e.g., from the size of the frequency range).

[0140] For example, the motion detection unit 150 can be configured to identify frequency bins with increasing size. For instance, sizes exceeding a threshold can be detected. The threshold can be predetermined. High values ​​in the frequency bins might correspond to large objects or many objects with corresponding speeds. However, frequency bins with increasing size could also be caused by noise. All frequency bins may have one or more thresholds, or each frequency bin may have one threshold, and so on.

[0141] For example, the motion detection unit 150 can be configured to estimate whether the identified frequency bin corresponds to a motion source or a noise source in the environment.

[0142] Figure 4a The spectrum of the magnitude of the FFT transform of the dual-channel motion sensor signal is shown. Spectrum 4a was created based on a computer simulation of a dual-channel Doppler motion sensor. In the simulation, there is a moving object with two humming noise sources. The complex frequency transform yields an array A(ω), which represents the amplitude of the frequency ω. In this example, the frequency ranges from -600 Hz to +600 Hz. Figure 4a The diagram illustrates the absolute value of the frequency amplitude. Please note that... Figure 4a The diagram shows several peaks caused by the Doppler shift resulting from motion in the environment. The peak at 411, between approximately 0 and 200 Hz, is caused by vibrations in the environment. This vibrational motion also causes peaks at corresponding negative frequencies, which can be seen at 413, for example, between approximately 0 and -200 Hz. Figure 4a The peak at 412 is also shown. This peak is at approximately 300 Hz, corresponding to non-vibrational motion. Note that peak 413 is not mirrored at -300 Hz.

[0143] Figure 4bA graph showing the size of the FFT transform with noise cancellation is provided. Figure 4b From Figure 4a The result was obtained by subtracting the magnitude of the negative frequency from the corresponding positive frequency. As a result, the peak corresponding to the humming noise was completely eliminated, while the 300 Hz peak corresponding to non-vibrating motion remained. Figure 4b Motion can be detected with increased reliability because false alarms from the buzzing sound have been reduced. Please note that... Figure 4b It contains no noise; it is a simulated artifact.

[0144] Figure 4c and 4d This is a graph illustrating the effect of removing real motion from the sensor environment but leaving behind buzzing noise. The peak at 412 has been removed because there is no real motion, although the peak caused by the buzzing noise remains. Figure 4d The generated noise-cancelled map looks like this; no peaks remain. When the motion detection algorithm is applied... Figure 4d Instead Figure 4b At that time, no motion will be detected because there is no remaining energy in the spectrum.

[0145] Please note, Figure 4a and 4c The energy difference between them Figure 4b and 4d The energy difference between them is relatively small, which indicates that... Figure 4b and 4d Set an accurate threshold to detect motion ratio. Figure 4a and 4c It's easier. What's worse, the number of buzzing sources can change over time. The buzzing can last from seconds to hours and come from one or more sources. Figures 2a-2d The ratio of the axis to the 4a-4d axis is set automatically.

[0146] A problem with motion sensors, especially Doppler motion sensors, is a type of noise called hum noise. Humming noise sources cause a rise in signal strength within a specific frequency band, typically intermittently. Humming can be caused by vibrations, such as those from drivers inside the luminaire or from external devices. It can also be caused by mechanical structures in the environment, such as the thin-film optics present in T-LED luminaires. Humming tends to be confined to one or two adjacent frequency bands, for example, with a bandwidth of approximately a few hertz, but it can sometimes span more than two frequency bands.

[0147] Intermittent signals can lead to false motion triggering. For example, a humming noise source, such as an electronic actuator or a thin-film optics device, may cause an increase in a specific frequency range, which could then be interpreted as motion in the area around the sensor, when in reality it is simply due to the humming noise.

[0148] The motion detection unit 150 can be configured to classify the environment as quiet or moving based on the motion component (e.g., frequency bin) that has been noise-cancelled.

[0149] The motion detection unit 150 can be classified in various ways. For example, depending on the application, the motion detector can be configured to detect or not detect small movements. For example, a motion detector used for lighting control in an office can be configured to have a low motion threshold, for example, to detect movements such as typing. For example, a motion detector used for lighting control in a corridor can be configured to have a higher motion threshold, for example, to detect larger movements such as walking. This avoids the situation where, in the first case, the lights turn off when the occupant is relatively still except for small movements such as typing, or in the second case, the lights in the corridor are easily turned on due to false alarms.

[0150] For example, motion detection unit 150 can be configured to determine the energy in a frequency bin (e.g., a frequency bin or portion thereof estimated to correspond to a motion source). If the determined energy exceeds a threshold, the environment can be classified as motion. For example, the energy can be calculated by summing the squares of the frequency bins. For example, the energy can be weighted energy. For example, frequencies corresponding to walking speed might be given higher weights than those not corresponding to walking speed. If the energy or weighted energy in a frequency bin corresponding to motion (e.g., not noise) exceeds the threshold, the area is classified as motion. If not, the area might be classified as quiet. The sensitivity of the motion detector can be adjusted according to the needs of the application by adjusting the threshold and / or weights. This can be done empirically.

[0151] Instead of classifying the environment as moving or quiet, for example in binary classification, motion sensors can report values ​​indicating the likelihood of motion in the environment. For example, energy in the noise cancellation spectrum can be mapped to floating-point values, such as fractions between 0 and 1, for example, using the sigmoid function.

[0152] At the edges of frequency bins, such as in higher and lower bins, some special considerations may be required. The inventors also found that sensors are generally unreliable at the low end of the frequency range. In the embodiments, frequency bins below the frequency floor were estimated to be noise-induced. For example, for a 5.8 GHz sensor, the noise frequency floor might be less than 9.3 Hz. These low frequencies were found to have more spurious signals and are therefore unreliable and inconsistent. For other sensor modes, this value will vary proportionally. For example, this cutoff frequency increases with the sensor frequency of the Doppler sensor.

[0153] Motion detectors with noise filtering, such as motion detector 100, risk ignoring motion signals, for example, mistaking real motion for noise. As noted herein, various parameters discussed can be adjusted to increase or decrease the likelihood of this occurring. The inventors have found that mistaking real motion for noise in lighting equipment (e.g., luminaire 170 or lighting system 171) has a more significant impact if people are actually present. In embodiments, this can be avoided by suppressing noise reduction if someone is present, for example, if the light-emitting element is turned on. Noise reduction can be turned off entirely, or different trade-offs can be configured by changing its parameters.

[0154] If the light is on, it means someone is present within the detection area. If a noise filter detects the motion signal as noise and eliminates it, this may not have an immediate and serious impact because the lights may not turn off immediately; they can be configured to remain on for a period of time after motion is detected. The system continuously searches for motion, and if it sees at least one motion within a configured time interval before turning off, the previous false alarm error will not be observed at the system level because the effect is not visible. However, if no other motion is seen within the configured interval, the light will eventually turn off, resulting in unpleasant behavior.

[0155] Typically, the motion detector 100, luminaire 170, lighting system 171, and lighting controller 175 all include a microprocessor that executes appropriate software stored in these devices; for example, this software may have been downloaded and / or stored in a suitable memory, such as volatile memory like RAM or non-volatile memory like flash memory. Alternatively, the devices may be implemented wholly or partially as programmable logic, such as as a field-programmable gate array (FPGA). The devices may be implemented wholly or partially as so-called application-specific integrated circuits (ASICs), such as integrated circuits (ICs) customized for their specific applications. For example, the circuits may be implemented in CMOS, for example using hardware description languages ​​such as Verilog, VHDL, etc.

[0156] In an embodiment, the motion detector includes one or more electronic circuits. The circuits implement the corresponding units described herein. The circuits may be processor circuits and storage circuits, with the processor circuits executing instructions electronically represented in the storage circuits. The processor circuits may be implemented in a distributed manner, for example, as multiple sub-processor circuits. The storage devices may be distributed across multiple distributed sub-storage devices. Part or all of the memory may be electronic memory, magnetic memory, etc. For example, the memory may have volatile and non-volatile portions. Part of the storage may be read-only.

[0157] One challenge with motion sensors is avoiding false alarms, such as false triggers in the presence of non-motion signals (like humming / vibration), which is quite common. The inventors observed that sometimes during operation of motion sensors used for motion detection, sudden vibrations are seen in the frequency domain, often more concentrated in one or two adjacent frequency bands, for example, with a bandwidth of approximately a few hertz. These vibrations typically persist for at least a few seconds, sometimes even minutes or hours. These vibrations are referred to as humming because they are more localized. In contrast, motion signals have a much wider spectral range; therefore, this property can be used to isolate suddenly initiating humming signals from motion signals.

[0158] As described above, noise sources can cause intermittent spikes in a frequency band. This intermittent nature of the signal can lead to false alarms for motion calls. This problem can be addressed using noise cancellation unit 140, for example, by reducing the amplitude of frequency bands that may be affected by noise, particularly humming-type noise. Removing such frequency bands from motion detection considerations can also serve as a noise filter. The humming detector can be implemented as a filtering enhancement for a motion algorithm that identifies frequency bands experiencing humming conditions and eliminates their contribution to motion calls. Further signal processing can detect and interpret humming sounds or vibrations so they are not classified as motion.

[0159] In a Doppler sensor, the frequency of a moving object can be estimated. Generally, for a frequency of... f For a sensor with a value of 0, the following relationship can be used: Where c is the speed of light. f 0 represents the sensor frequency, Δ f Describe the Doppler frequency. Vibrations differ from human motion in that, for example, the excitation frequency chamber of vibrations is typically narrower, and the vibration... f It typically does not change over time. If the time-domain signal is sampled at 40 Hz, it can be analyzed using a 128-point FFT.

[0160] While the parameters of the hum detector can be carefully adjusted, hum filters always carry the risk of misidentifying motion events as vibrations. This is especially important for small movements, such as those made by a person behind an office desk. To avoid this problem, the hum filter can be turned off when someone is present. One approach to address this is to activate the hum filter when the lights are off and deactivate it when the lights are on.

[0161] Vibrations are typically caused by mechanical structures in the environment, such as the thin-film optical elements present in T-LED lamps. These vibrations often share similar characteristics. For this reason, hum detectors must often handle very similar vibrations. Instead of relying on the transient capabilities of the hum detector to filter these out, the hum detector may also, at a certain point, for example, completely ignore frequencies that have experienced vibration problems if the frequency of the vibration is high enough.

[0162] The hum history can be used to more accurately identify hums. Motion detection algorithms run at a specific rate, for example, iterating every 100 milliseconds, and the motion detector can report motion / no motion. If a motion signal is observed, it is typically not necessary to report it immediately. In an embodiment, multiple iterations are performed before reporting the observed signal, for example, four iterations over 400 ms. This reduces the chance of false motion signals. Although hums begin almost instantly, they change very little after they begin. This means that the hum history also changes very little. Since there are several frames, this time can be used to monitor changes in the hum history. If these changes are below a threshold, then one can more confidently identify the signal as vibration and report no motion. If the history does change above a certain threshold, then motion can be reported.

[0163] Noise detection can be used in any product that utilizes time-varying sensor signals. For example, noise detection has been found to be effective for Doppler motion sensors. Noise detection can also be used for different types of sensors. For example, ambient light sensors are affected by similar noise sources, such as vibration noise, electrical noise, etc.

[0164] Back Figure 1a The noise cancellation described in this article removes or reduces the contribution of humming noise to the motion component. If the motion sensor is not ideal, for example, if the amplification or sensitivity in the I and Q channels differs, the reduction will be degraded. Another problem may arise if the mixers of the motion sensor 110 (e.g., mixers 530 and 540) are not precisely quadrature. If the phase difference is not 90 degrees, then | βA(ω) | 2 A mirror image of energy. Note that energy is typically calculated as the square of the amplitude.

[0165] Furthermore, if the loss in the mixed signal is small and accurate, the reduction is improved because it causes the amplitudes of the two frequencies to be closer to each other. Unfortunately, in the embodiment, the motion sensor may be less than ideal, leading to a divergence between the expected behavior in the spectrum.

[0166] The noise cancellation unit 140 can be configured to correct defects in the motion sensor 110.

[0167] Figure 5a An example embodiment of motion detector 101 is illustrated schematically. Motion detector 101 can be identical to motion detector 100, except for the addition of a correction term memory 164 and a modified noise cancellation unit 141. For example, the correction term memory 164 can store a correction factor β. The noise cancellation unit 141 can be configured to multiply one of the two motion components by the correction factor β before subtracting the two motion components. The correction factor β can be a real number, such as a magnitude. If the correction is applied to a complex value (e.g., amplitude), the correction factor β can be a complex number.

[0168] A particularly advantageous method for calculating the differences between motion components is to use the following formula: , among which | A ( ω | indicates frequency ω The magnitude of the motion components.

[0169] For example, suppose the signal construction is chosen such that positive frequencies correspond to motion toward the sensor, while negative frequencies correspond to motion away from the sensor. If the signal amplification between I and Q is slightly different, then motion toward the sensor will not only have a non-zero FFT amplitude at a certain positive frequency, but also a smaller non-zero FFT amplitude at the corresponding negative frequency; "smaller" here refers to the norm, since the amplitude is complex. As an example, suppose the frequency transition is obtained at ω=12, and the values ​​of A(12) and A(-12) are different, even though they are known to correspond to the same motion; therefore, one of them should be zero. A correction factor can then be used to correct for this. For example, suppose A(12) = 5+5 i And A(-12) = 1-1 i In this case, β can be chosen as |1-1|. i | / |5+5 i |=1 / 5.

[0170] For ω=12, the above expression can now be calculated and read as:

[0171]

[0172] Note that the expression above is nonzero as expected, because it represents motion. Note that the reduction in the magnitude of the motion component is much smaller than that in the expression. The amount of reduction. In the former case, the value is |5+5 i |use Reduce instead of using |1-1 as in the latter case i|reduced. Note that the latter term is much larger. Therefore, in the case of a less than ideal sensor, the above formula reduces the unintentional cancellation of real motion. However, interestingly, in the case of vibration, |A(12)| = |A(-12)|, one still finds that the expression in the claim equals 0. Generally, in the case of vibration, it is indeed approximately |A( ω )|=|A(- ω In the case of )|, because the unintentional contribution of stimulating A(-ω) instead of A(ω) is roughly the same as the unintentional contribution of stimulating A(ω) instead of A(-ω).

[0173] The correction factor does not need to be linear or quasi-linear; for example, a function G can be defined, such as a nonlinear mapping. The function G can act directly on complex values, for example, as follows:

[0174]

[0175] Instead of acting on complex values, the function G can act on magnitudes.

[0176] Figure 5b An example embodiment of motion detector 102 is illustrated schematically. Motion detector 102 can be identical to motion detector 101, except for the addition of a correction term estimator 162. A correction factor or function can be estimated and stored in motion detector 101. For example, the correction factor can be estimated under laboratory conditions. Another approach is to estimate the correction factor during sensor use. For example, correction term estimator 162 can be configured to estimate the correction factor during use of the motion sensor.

[0177] For example, the correction term estimator 162 may include an algorithm to determine that a motion component is likely caused by non-vibrational motion. For example, the algorithm may include comparing the amplitude of the motion component to a threshold under the assumption that real motion typically gives large motion components. For example, the algorithm may verify that adjacent motion components are also boosted because real motion is typically distributed across multiple motion components; for example, a series of ±k consecutive motion components before and after a particular motion component should exceed another threshold to conclude that the particular motion component corresponds to motion. For example, k could be 2 or 3, or more, etc. If the signal is considered motion, for example, determined by the algorithm, a correction factor can be estimated. For example, when using the above formula, assuming the real motion is at ω, β = |A(- ω )| / |A( ω )|, for example, if |A( ω )|greater than|A(- ω )|.

[0178] The estimated correction factor carries the risk that motion signals may be mixed with low-amplitude vibrations. To eliminate this effect, a moving average can be used, which averages β over the last n observations.

[0179] Figure 6 An example of an embodiment of the motion detection method 700 is illustrated schematically. The motion detection method (700) includes:

[0180] - Receive a motion signal (710) from a motion sensor, the motion signal being correlated with motion in the motion sensor environment.

[0181] - The motion signal is processed (720) to obtain multiple motion components, which are related to the direction and velocity of motion in the environment.

[0182] - Eliminate (730) in the motion components, which correspond to two motion components with opposite directions.

[0183] - Detect motion components in an environment that have never been eliminated (740)

[0184] Many different ways of performing this method are possible, as will be apparent to those skilled in the art. For example, the steps can be performed in the order shown, but the order of the steps can also be changed, or some steps can be performed in parallel. Furthermore, other method steps can be inserted between the steps. The inserted steps may represent an improvement to the method described herein, or they may be independent of the method. For example, steps 730 and 740 can be performed at least partially in parallel. Moreover, a given step may not be fully completed before proceeding to the next step.

[0185] Embodiments of this method can be executed using software that includes instructions for causing a processor system to perform method 700. The software may include only those steps taken by a specific sub-entity of the system. The software may be stored on a suitable storage medium, such as a hard disk, floppy disk, memory, optical disk, etc. The software may be transmitted as a signal along a wired or wireless route, or using a data network (e.g., the Internet). The software may be downloaded to a server and / or used remotely. Embodiments of the method may be executed using a bitstream arranged to configure programmable logic (e.g., a field-programmable gate array (FPGA)) to perform the method.

[0186] It should be understood that the present invention also extends to computer programs, particularly computer programs on or within a carrier suitable for putting the present invention into practice. The program may be in the form of source code, object code, intermediate source code, and object code, such as in a partially compiled form, or any other form suitable for implementing embodiments of the method. Embodiments relating to computer program products include computer-executable instructions corresponding to each processing step of at least one of the methods. These instructions may be subdivided into subroutines and / or stored in one or more files that may be statically or dynamically linked. Another embodiment relating to computer program products includes computer-executable instructions corresponding to each device of at least one of the illustrated systems and / or products.

[0187] Figure 7a A computer-readable medium 1000 with a writable portion 1010 according to an embodiment is shown. The writable portion 1010 includes a computer program 1020, which includes instructions for causing a processor system to perform a motion detection method. The computer program 1020 may be embodied on the computer-readable medium 1000 as a physical marker or by magnetization of the computer-readable medium 1000. However, any other suitable embodiments are conceivable. Furthermore, it should be understood that although the computer-readable medium 1000 is shown herein as an optical disc, the computer-readable medium 1000 can be any suitable computer-readable medium, such as a hard disk, solid-state storage, flash memory, etc., and may be non-recordable or recordable. The computer program 1020 includes instructions for causing a processor system to perform the motion detection method.

[0188] Figure 7b An exemplary hardware diagram for implementing device 1100 according to an embodiment is illustrated. As shown, device 1100 includes a processor 1120, a memory 1130, a user interface 1140, a communication interface 1150, and a storage device 1160 interconnected via one or more system buses 1110. It should be understood that this diagram is abstract in some respects and the actual organization of the components of device 1100 may be more complex than illustrated.

[0189] Processor 1120 can be any hardware device capable of executing instructions stored in memory 1130 or storage device 1160 or otherwise processing data. Therefore, the processor can include a microprocessor, a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), or other similar device. For example, the processor can be an Intel Core i7 processor, an ARM Cortex-R8, etc. In this embodiment, the processor can be an ARM Cortex M0.

[0190] Memory 1130 may include various types of memory, such as, for example, L1, L2, or L3 cache or system memory. Therefore, memory 1130 may include static random access memory (SRAM), dynamic RAM (DRAM), flash memory, read-only memory (ROM), or other similar storage devices. It is apparent that in embodiments where the processor includes one or more ASICs (or other processing devices), these ASICs implement one or more of the functions described herein in hardware, and the software described in other embodiments corresponding to such functions may be omitted.

[0191] User interface 1140 may include one or more devices capable of communicating with users such as administrators. For example, user interface 1140 may include a display, mouse, and keyboard for receiving user commands. In some embodiments, user interface 1140 may include a command-line interface or graphical user interface that can be presented to a remote terminal via communication interface 1150.

[0192] Communication interface 1150 may include one or more devices for enabling communication with other hardware devices. For example, communication interface 1150 may include a network interface card (NIC) configured to communicate according to the Ethernet protocol. For example, communication interface 1150 may include an antenna, a connector, or both. Furthermore, communication interface 1150 may implement a TCP / IP stack for communication according to the TCP / IP protocol. Various alternative or additional hardware or configurations for communication interface 1150 will be readily apparent.

[0193] Storage device 1160 may include one or more machine-readable storage media, such as read-only memory (ROM), random access memory (RAM), disk storage media, optical storage media, flash memory devices, or similar storage media. In various embodiments, storage device 1160 may store instructions for execution by processor 1120 or data that can be operated by processor 1120. For example, storage device 1160 may store a basic operating system 1161 for controlling various basic operations of device 1100. For example, the memory may store instructions 1162 for signal processing of motion signals to obtain multiple motion components (e.g., converting sensor signals to the frequency domain to obtain multiple frequency bins), instructions 1163 for eliminating two motion components corresponding to motions having opposite directions (e.g., reducing the magnitude of a first motion component associated with a first motion in response to a second motion component associated with a second motion opposite to a first motion), and instructions 1164 for detecting motion in the environment of motion components that have not been eliminated.

[0194] Obviously, the various information described as being stored in storage device 1160 may be additionally or alternatively stored in memory 1130. In this respect, memory 1130 may also be considered as constituting a "storage device" and storage device 1160 may be considered as a "memory". Various other arrangements will be apparent. Furthermore, both memory 1130 and storage device 1160 may be considered as "non-transitory machine-readable media". As used herein, the term "non-transitory" will be understood to exclude transient signals but include all forms of storage, including both volatile and non-volatile memory.

[0195] While device 1100 is shown as including one of each of the described components, various components may be replicated in various embodiments. For example, processor 1120 may include multiple microprocessors configured to independently execute the methods described herein or configured to execute steps or subroutines of the methods described herein, such that multiple processors cooperate to achieve the functionality described herein. Furthermore, in the case where device 1100 is implemented in a cloud computing system, various hardware components may belong to separate physical systems. For example, processor 1120 may include a first processor in a first server and a second processor in a second server.

[0196] It should be noted that the above embodiments are illustrative of the present invention and not limiting, and those skilled in the art can design many alternative embodiments.

[0197] In the claims, any reference numerals placed between parentheses should not be construed as limiting the claims. The use of the verb "comprising" and its variations does not exclude the presence of elements or steps other than those described in the claims. The article "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. Expressions such as "at least one of" preceding a list of elements indicate the selection of all elements from the list or any subset of elements. For example, the expression "at least one of A, B, and C" should be understood to include only A, only B, only C, both A and B, both A and C, both B and C, or all of A, B, and C.

[0198] In the claims, the reference numerals enclosed in parentheses refer to reference numerals in the drawings of exemplary embodiments or formulas of embodiments, thereby increasing the comprehensibility of the claims. These reference numerals should not be construed as limiting the claims.

Claims

1. A lighting fixture (170) comprising a motion detector (100), the motion detector (100) comprising: - A motion sensor interface (120) configured to receive motion signals from a motion sensor, the motion signals being related to the motion of objects in the motion sensor environment. - Processor system, which is configured as follows: -Signal processing is performed on the motion signal to obtain multiple motion components, which are related to the direction and velocity of motion in the environment. - Eliminate two motion components that correspond to motions with opposite directions from the motion components. - Detects motion components that are never eliminated, thus detecting the motion of objects in the environment. -The luminaire can be connected to the light-emitting element (172) and is configured to control the light-emitting element in dependence on the motion detector.

2. The luminaire (170) according to claim 1, wherein the motion signal received by the motion sensor interface (120) includes a first channel (I) and different second channels (Q), the first channel and the second channel being related to motion in the motion sensor environment.

3. The luminaire (170) according to claim 2, wherein the signal processing includes obtaining a complex signal (I+jQ) from the first channel and the second channel by frequency variation.

4. The luminaire (170) according to claim 2 or 3, wherein the sensor is a dual-channel Doppler microwave sensor.

5. The luminaire (170) according to any one of claims 1-3, wherein the signal processing includes transforming the motion signal from the time domain to the frequency domain to obtain the plurality of motion components.

6. The luminaire (170) according to claim 5, wherein the motions having opposite directions contribute to different motion components among the plurality of motion components.

7. The luminaire (170) according to claim 6, wherein the plurality of motion components correspond to a frequency, and motions having opposite directions contribute to motion components having the same frequency but opposite signs.

8. The luminaire (170) according to claim 1, wherein the motion component corresponding to the frequency is subtracted from the motion components having the same frequency but opposite signs to eliminate the motion component corresponding to the motion having opposite directions.

9. The luminaire (170) according to claim 1, wherein eliminating the two motion components comprises, before subtracting the two motion components, dividing one of the two motion components by a correction factor ( ). β Multiply by 1.

10. The luminaire (170) according to claim 1, wherein eliminating the two motion components includes calculating... Among them | A ( ω | represents the magnitude of the motion component at frequency ω. β This represents the correction factor.

11. The luminaire (170) according to claim 9 or 10, wherein the processor system is configured to estimate the correction factor during use of the motion sensor.

12. The luminaire (170) according to claim 11, wherein the processor system is configured to: - Determine whether the motion signal corresponds to non-vibrational motion. - Estimate the correction factor from the motion signal.

13. The luminaire (170) according to claim 1, wherein the luminaire further comprises at least one light-emitting element.

14. A motion detection method (700), comprising: - Receive (710) motion signals from a luminaire (170) including a motion sensor, the motion signals being related to the motion of an object in the motion sensor environment, wherein the luminaire may be connected to a light-emitting element (172). - The motion signal is processed (720) to obtain multiple motion components, which are related to the direction and velocity of motion in the environment. - Eliminate (730) in the motion components, which correspond to two motion components with opposite directions. - Detection of motion components that have never been eliminated (740) of objects in the environment. - It relies on motion sensors to control the light-emitting elements.

15. A temporary or non-temporary computer-readable medium (1000) comprising data (1020) representing instructions for causing a processor system to perform the method according to claim 14.

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