Apparatus, radar sensor, electronic device, method, non-transient machine-readable medium, and program for detecting

Abstract

The present disclosure relates to an apparatus, a radar sensor, an electronic device, a method, a non-transitory machine-readable medium, and a program for detecting micro-motion. An apparatus comprising processing circuitry configured to: receive radar data output by a radar sensor for each receive channel, arranged as a frame for each receive channel; for each receive channel, each frame and each range bin of the plurality of range bins of the radar data, each range bin corresponding to a range window associated with the radar sensor, extracting micro-motion information from the radar data considering the range bin and generating a first value from the micro-motion information; determining, for each receive channel, each frame, each distance bin, a second value based on a first value determined by the considered distance bin of the considered frame and a previous first value determined by the considered distance bin of a previous frame; determining, for each distance bin, a third value for the considered distance bin based on the respective second value; a micro-motion occurring in the scene is determined based on the third value.

Description

Technical Field

[0001] This disclosure relates to apparatus, radar sensors, electronic devices, methods, non-transient machine-readable media, and programs for detecting micro-motion. Background Technology

[0002] Micro-motion is used in a variety of applications. For example, it is used to detect motion signatures in a static person to determine whether that person is awake. Typically, large bandwidth or a large number of channels are used to increase the probability of detection. Other methods create virtual frames from multiple real radar frames, which requires storing multiple frames and therefore requires large memory.

[0003] Therefore, it is necessary to improve the detection of micro-motions. Summary of the Invention

[0004] This need can be satisfied by the subject matter of the independent claims. Other embodiments are given by the dependent claims, the drawings, and the following description.

[0005] According to a first aspect, this disclosure provides an apparatus for detecting micro-motion in a scene sensed by a radar sensor having one or more receiving channels. The apparatus includes processing circuitry configured to receive radar data output by the radar sensor for each receiving channel, the radar data being arranged as frames for each receiving channel. The processing circuitry is further configured to extract micro-motion information from the radar data of the considered range bins for each receiving channel, for each frame, and for each range bin of a plurality of range bins of radar data, each range bin corresponding to a range window associated with the radar sensor, and to generate a first value from the micro-motion information. The processing circuitry is further configured to determine a second value for each receiving channel, for each frame, and for each range bin, based on the first value determined for the considered range bin at the considered frame and a previous first value determined for the considered range bin at a previous frame. The processing circuitry is further configured to determine a third value for each considered range bin based on the corresponding second value. The processing circuitry is further configured to determine the occurrence of micro-motion in the scene based on the third value.

[0006] According to a second aspect, this disclosure provides a radar sensor including means for detecting micro-motion according to a first aspect. The radar sensor further includes one or more transmit channels configured to transmit one or more transmit signals into the radar sensor's field of view. The radar sensor also includes one or more receive channels configured to generate radar data based on received reflections of the one or more transmit signals.

[0007] According to a third aspect, this disclosure provides an electronic device including a radar sensor according to a second aspect. The electronic device further includes processing circuitry coupled to the radar sensor and configured to perform a predetermined action if the occurrence of micro-motion in a scene is determined by the radar sensor.

[0008] According to a fourth aspect, this disclosure provides a method for detecting micro-motion in a scene sensed by a radar sensor having one or more receiving channels. The method includes receiving radar data output by the radar sensor for each receiving channel, the radar data being arranged as frames for each receiving channel. The method also includes extracting micro-motion information from the radar data of the considered range bins for each receiving channel, for each frame, and for each of a plurality of range bins of radar data, each range bin corresponding to a range window associated with the radar sensor, and generating a first value based on the micro-motion information. The method further includes determining a second value for each receiving channel, for each frame, and for each range bin, based on the first value determined for the considered range bin at the considered frame and a previous first value determined for the considered range bin at a previous frame. The method also includes determining a third value for each considered range bin based on the corresponding second value. The method further includes determining the occurrence of micro-motion in the scene based on the third value.

[0009] According to a fifth aspect, this disclosure provides a non-transient machine-readable medium having a program stored thereon, the program having program code that, when executed on a processor or programmable hardware, is used to perform the method according to a fourth aspect.

[0010] According to a sixth aspect, this disclosure provides a program having program code that, when executed on a processor or programmable hardware, performs the method according to a fourth aspect. Attached Figure Description

[0011] The following will describe some examples of apparatus and / or methods by way of example and with reference to the accompanying drawings, wherein

[0012] Figure 1 An apparatus for detecting micro-motion according to the present disclosure is described;

[0013] Figure 2 A radar sensor according to this disclosure is described;

[0014] Figure 3 An electronic device according to this disclosure is described;

[0015] Figure 4 A flowchart of a method for detecting micro-motion according to this disclosure is depicted; and

[0016] Figure 5 Different diagrams are depicted representing the outputs at different steps of this disclosure. Detailed Implementation

[0017] Some examples will now be described in more detail with reference to the accompanying drawings. However, other possible examples are not limited to the features of these embodiments described in detail. Other examples may include modifications to the features, as well as equivalents and alternatives to the features. Furthermore, the techniques used herein to describe certain examples should not limit other possible examples.

[0018] Throughout the description of the accompanying drawings, the same or similar reference numerals refer to the same or similar elements and / or features, which may be implemented in the same or modified form while providing the same or similar function. For clarity, the thickness of lines, layers, and / or regions in the drawings may also be exaggerated.

[0019] When two elements A and B are combined using "or", this should be understood to disclose all possible combinations, i.e., only A, only B, and A and B, unless otherwise expressly specified in individual cases. "At least one of A and B" or "A and / or B" may be used as alternative wording for the same combination. This is equivalent to combinations of more than two elements.

[0020] If the singular forms such as “a,” “an,” and “the” are used, and the use of a single element is not explicitly or implicitly mandatory, other examples may use several elements to achieve the same functionality. If the functionality is described below as being implemented using multiple elements, other examples may use a single element or a single processing entity to achieve the same functionality. It should also be understood that the terms “include,” “including,” “comprise,” and / or “comprising”, when used, describe the presence of a particular feature, integer, step, operation, process, element, component, and / or group thereof, but do not preclude the presence or addition of one or more other features, integers, steps, operations, processes, elements, components, and / or groups thereof.

[0021] Figure 1 A device 1 for detecting micro-motion in a scene (e.g., an object) is depicted. The scene is sensed by a radar sensor having one or more receiving channels, as will be referenced below. Figure 2Further discussion. The apparatus includes a processing circuitry device 2. The processing circuitry device may be a single dedicated processor, a single shared processor, or multiple separate processors, some or all of which may be shared, digital signal processor (DSP) hardware, application-specific integrated circuit (ASIC), neuromorphic processor, or field-programmable gate array (FPGA). The processing circuitry device 2 may optionally be coupled to, for example, read-only memory (ROM), random access memory (RAM), and / or non-volatile memory for storing software.

[0022] exist Figure 1 In the following description, reference numerals may also refer to those that can be executed by the processing circuit device 2. Figure 4 The method.

[0023] Processing circuitry 2 is configured to receive radar data 101 generated by a radar sensor through sensing of a scene. The radar data 101 may, for example, represent multiple samples, where each sample can be a number between 0 and (2N)-1, indicating (representing) the digitized amplitude or voltage of a corresponding measurement signal (such as that obtained through one or more receiving channels), or its normalized value. N may correspond to the resolution of the radar data, which may, for example, be determined by the resolution of the analog-to-digital converter (ADC) of the radar sensor that samples the corresponding antenna received signal or measurement signal.

[0024] In other words, the radar data 101 received by the processing circuit device 2 is output by the radar sensor for each receiving channel. Samples or raw data are arranged into (continuous) frames, each frame representing a time period during which the corresponding sample included in the frame has been acquired (e.g., acquired, received, etc.). Thus, for example, if multiple receiving channels are used, each receiving channel can output raw ADC data as a frame.

[0025] The processing circuitry 2 is also configured to extract micro-motion information 102 from the radar data 101. This extraction is performed for each received channel, for each frame, and for each range bin. A range bin may correspond to a range window, which is associated with the radar sensor. Typically, in radar processing, a range bin can be understood as a container for data corresponding to a range range. This bin can be predefined and / or based on at least one of the radar parameters used and frequency estimation techniques. Each bin can be populated with corresponding radar data from the radar data 101. For example, a range FFT (Fast Fourier Transform) or a fast-time FFT can be performed on the ADC sampled data for each chirp and receiver. The result of the range FFT can correspond to an indication of the energy distribution over the range of each chirp and receiver. Each FFT bin of the range FFT can be scaled to the range and can depend on the available RF bandwidth and propagation speed. Therefore, the FFT bin of the range FFT can also be referred to as a range bin.

[0026] Micromovements can refer to movements performed by a stationary / involuntary (active) object. For example, a person sitting in a chair and not (consciously) moving can still exhibit micromovements, such as due to breathing, blinking eyes, still muscle activity, tremors, etc. Similarly, a sleeping person (or animal) can exhibit micromovements in a similar way. Likewise, for example, micromovements can be caused by (slight) changes in body posture.

[0027] More generally, micromotions can refer to small (fine) movements or vibrations of a target object. These movements can be caused by a variety of factors, such as mechanical vibrations, respiratory movements (in the case of humans and animals), or (tiny) mechanical movements of structural parts. Compared to the target's primary movements (which involve, for example, walking or driving), micromotions are typically much smaller in scale. Similarly, micromotions can be superimposed on primary movements.

[0028] The extraction of micro-motion information 102 can be based on filtering the (raw) radar data 101 in the range bin or on filtering the output of a range FFT or fast-time FFT (e.g., the average of the range FFT outputs in the chirped dimension for each receive channel). The extraction of micro-motion information can additionally or alternatively be performed by first performing a slow-time FFT or Doppler FFT along the chirped dimension for each range bin and receive channel, followed by filtering out zero Doppler components for each range bin and receive channel. The result of the slow-time FFT or Doppler FFT can be an indication of the energy distribution across different Dopplers for each range bin and receive channel. The FFT bin of the Doppler FFT can depend on the RF center frequency, and therefore the frequency bin of the Doppler FFT can also be referred to as the Doppler bin.

[0029] Therefore, radar data 101 for a range cell can be considered for extracting micro-motion information 102. For example, extraction can be performed across multiple chirps. In other words, radar data 101 contained in each range cell having a zero Doppler value / component (e.g., the average of samples in the chirp dimension) can be received / acquired. Micro-motion information 102 can take various forms, such as determining a certain value (e.g., a zero Doppler value) for one or more specific range cells, but this disclosure should not be construed as limiting it in this respect. For example, micro-motion information 102 can be additionally or optionally determined or extracted based on a low-pass filter across the chirp dimension in order to extract low-frequency components.

[0030] Based on the micro-motion information 102, a first value 103 is generated. For example, if a range-Doppler representation (also referred to as a range-Doppler map) is used, a range bin (as the first value or the data associated with the range bin) that is associated with or includes a zero Doppler value can be determined, indicating the first value 103 (i.e., the distance). In other words, chirp information can be extracted by averaging after the range FFT (see also above).

[0031] This determination can be performed over multiple frames, resulting in the determination of multiple first values ​​103 for the range bins under consideration. Based on the first values ​​103, a second value 104 is determined for each received channel, for each frame, and for each range bin. The second value 104 can be determined based on the first value 103 of the current / considered frame and the first value 103 of the (directly) previous frame, such that the second value corresponds to a (Δ) change in the first value 103 between the considered frames. For example, in some examples, if zero Doppler value / bin is used as the first value 103, then a change in zero Doppler value / bin indicates micro-motion (e.g., for that range bin). In the example, a moving target indicator algorithm is applied to determine the second value 104, as will be discussed further below.

[0032] Following this determination, for each range cell, a second value 104 associated with different channels and one or more (or two or more) frames can be used to determine a third value 105 for the range cell under consideration (based on which the occurrence of micro-motions 106 in the scene can be determined). In other words, for each range cell, the third value can be determined based on a combination of corresponding second values ​​for the range cell under consideration. Various ways may exist in which the second values ​​can be combined or used to determine the third value for the range cell under consideration.

[0033] For example, the combination or use of the second value 104 may include the accumulation of the second value 104 across different receiving channels and over a predetermined number of consecutive frames to generate a third value. Consecutive frames may include frames that follow each other directly (in time) or frames that follow each other but are spaced apart by other frames not used for accumulation (e.g., arbitrary selection of frames may be performed for accumulation). Accumulation may include integration (such as incoherent integration) without limiting this disclosure to that aspect. Incoherent integration may refer to the combination of signals from multiple radar pulses in a manner that does not require phase coherence between pulses. Thus, as stated above, integration can be performed across different receiving channels; that is, data obtained for different receiving channels can be combined / accumulated in this manner.

[0034] In the example, accumulation is performed using the absolute values ​​of the second values ​​over one or more receive channels (e.g., and over a certain number of frames), such as the sum of the absolute values ​​of the second values, a weighted sum of the absolute values ​​of the second values, an (incoherent) integral as described above, any combination of the second values, etc. For example, if a change from a previous first value to the current first value would result in a negative second value, then that negative second value would be made positive by taking its absolute value.

[0035] Because phase information can depend on the position of the target in space across different receiving channels, it can be taken as an absolute value. Furthermore, the azimuth and elevation angles of the target on the radar can be directly mapped to phase at the receiver. Coherent summation without taking absolute values ​​(which is possible in some examples) can correspond to beamforming in a certain direction, as this may facilitate specific phase values ​​between antennas. Taking absolute values ​​avoids this problem by ignoring the phase of the receiving channels.

[0036] The number of consecutive frames used can vary depending on the use case. For example, the stability of micro-motion detection might be considered. If the number of frames is low, the reliability of detection may decrease below the desired level. If the number of frames is high, the processing power involved in the implementation of the method may increase above the desired level. As another example, when the number of frames is too high, the time delay or the time used for averaging may increase. Therefore, the number of frames can be chosen to satisfy a desired trade-off between these considerations.

[0037] However, it should be noted that this disclosure is not limited to the accumulation across different receiving channels over a predetermined number of consecutive frames as discussed above. For example, any combination of any magnitude (e.g., channel, frame, time, etc.) of the second value 104 (e.g., linear or nonlinear combination, weighted sum, weighted product, etc.) can be used to determine the third value 105.

[0038] The third value generated by combining the corresponding second values ​​allows for an increase in the robustness of the system to account for the (inevitable) variability of information contained in the radar data and related to micro-motion. Thus, the generation of the third value and its use in micro-motion detection can form a mechanism for solidifying micro-motion information, while allowing the detection function to remain significantly lightweight in terms of the required processing power.

[0039] As indicated above, based on the third value 105, the occurrence of micro-motion 106 in the scene (or on an object in the scene) can be determined.

[0040] For example, in order to determine the occurrence of micro-motion 106 in the scene, the processing circuit device 2 can be configured to apply adaptive thresholding to a third value 105 to determine whether the third value is derived from micro-motion 106.

[0041] Adaptive thresholding can refer to a technique that dynamically adjusts a threshold (i.e., a lower threshold or an upper threshold (or both)) to a third value 105. Adaptive thresholding can be useful when dealing with varying signal conditions because it allows for more accurate and context-sensitive detection. Therefore, in contrast to “constant” thresholding, “adaptive” thresholding can be used to set dynamic thresholds based on radar data 101. For example, adaptive thresholding can take into account local variations in signal strength. Thus, features in regions with different background levels or noise conditions can be distinguished. The threshold can be adjusted based on local statistics such as the mean, median, standard deviation, or any other statistical measure within a defined neighborhood.

[0042] Adaptive thresholding may include subjecting the third value of 105 to constant false alarm rate (CFAR) detection. CFAR detection can be used to ensure a constant false alarm rate regardless of varying noise and clutter. The false alarm rate can refer to the probability of falsely announcing the presence of a target when no target is present. Different types of CFAR algorithms may be available, such as cell-averaged CFAR, CFAR maximum, CFAR minimum, ordinal statistical CFAR, etc. According to this disclosure, only one CFAR algorithm may be used, or multiple CFAR algorithms may be combined.

[0043] In the example, the processing circuitry 2 is optionally configured to filter a third value 105 of one or more predetermined range bins to remove the predetermined range bins from subsequent processing. For example, range masking can be used to filter out detections from the predetermined range bins. In this context, "predetermined" can refer to a point in the processing where it is recognized which range bins might be of interest. Therefore, "predetermined" does not necessarily mean that the range bins of interest are always the same, and dynamic adaptation of the range bins based on any of the method steps is possible. The range bins of interest can, for example, depend on the location of the radar sensor associated with the object. If the radar sensor is provided in a mobile phone and the sensor is used for user activity tracking, the range bins of interest may always be more or less the same, since the distance between the phone and the user may be more or less the same if the user holds the phone. On the other hand, if the radar sensor is provided in a surveillance camera, all the range bins of interest can vary because the surveillance camera may need to cover a large field of view.

[0044] In the example, the processing circuit device 2 is also configured to increment the corresponding counter for different distance bins (or for the corresponding distance bins) in response to determining that the third value 105 is derived from the micro-motion 106.

[0045] A counter can be used to provide more stability to the method. For example, if only one occurrence of a micro-motion for a given distance chamber is determined, it might be due to measurement error. Therefore, if the counter for the distance chamber reaches a predetermined value, the probability of a micro-motion occurring for that particular distance chamber can be fully considered since the determination of the third value 105 has been performed multiple times.

[0046] On the other hand, the processing circuit device 2 can also (additionally or alternatively) be configured to decrement the corresponding counter for each distance bin in response to determining that the third value 105 is not derived from the micro-motion 106. For example, if two distance bins indicate the micro-motion 106 after the first measurement, but one distance bin incorrectly indicates the micro-motion 106, the error can be compensated for by decrementing the counter again in the next determination / measurement, while the counter for the correct distance bin can be incremented again.

[0047] Therefore, measurement stability can be provided based on increasing or decreasing the counter (or both).

[0048] In the example, to determine the occurrence of micro-motion 106 in the scene, the processing circuit device 2 is also configured to determine the occurrence of micro-motion 106 in the corresponding distance bin in response to the counter value for the distance bin meeting a predetermined criterion. For example, a predetermined threshold that the counter may need to reach could be such a predetermined criterion. On the other hand, a time-based system (where the counter increments afterward) could correspond to such a criterion. Furthermore, a differential counter value (where the counter value leads some value of other counters) could be such a predetermined criterion.

[0049] As indicated above, in the example, to determine the second value, processing circuitry 2 is configured to execute a Moving Target Indicator (MTI) algorithm. For example, the second value could be the (direct) output of the MTI algorithm or a further processed output of the MTI algorithm. MTI can rely on the presence of a Doppler shift. By focusing on the Doppler shift, (stationary) clutter can be filtered because it may have little or no Doppler shift, thus highlighting the moving target.

[0050] Therefore, the MTI algorithm can be used to distinguish moving targets from stationary clutter. Thus, the second value 104 (a variation of the first value) can be identified as a static target between frames. However, this disclosure is not limited to the use of MTI. Additionally or alternatively, an infinite impulse response (IIR) filter and / or weighted averaging can be applied.

[0051] Figure 2 A radar sensor 10 is depicted. This disclosure is not limited to any particular type of radar sensor. For example, the radar sensor may be based on Doppler radar, frequency modulated continuous wave (FMCW) radar, etc. The radar sensor 10 includes, as shown in the reference... Figure 1 The device 1 described is for detecting micro-motion.

[0052] The radar sensor 10 also includes one or more transmit channels (not depicted) configured to transmit one or more transmit signals into the radar sensor's field of view, as is generally known. Similarly, the radar sensor 10 includes one or more receive channels configured to generate radar data based on the received reflections (or echoes) of one or more transmit signals, as is generally known.

[0053] In the example, radar sensor 10 also includes a radio frequency integrated circuit (RFIC). The device 1 for detecting micro-motion can be included in the RFIC.

[0054] RFIC can refer to a (highly) integrated circuit operating at the radio frequency, for example, designed to handle and process RF signals in the range of 3 kHz to 300 GHz. RFICs can combine multiple RF functions onto a single semiconductor substrate. The integration of components within an RFIC, such as low-noise amplifiers, mixers, oscillators, power amplifiers, and filters, allows for enhanced signal integrity, reduced power consumption, and miniaturization, making it suitable for radar applications according to this disclosure.

[0055] In the example, the device for micro-motion detection is implemented as a register transfer level (RTL) circuit device.

[0056] RTL circuitry can refer to a digital circuit design methodology that describes the data flow and control signals between hardware registers and gates, as well as the logical operations performed on that data. RTL circuits can form the basis for the synthesis of digital systems and are commonly used to model and implement complex digital functions in hardware description languages. Such circuitry allows for the specification of the behavior of digital systems at a high level of abstraction, focusing on data movement and transformation rather than detailed gate-level implementations. Therefore, the methods disclosed herein can be implemented on an RFIC.

[0057] For example, in the context of this disclosure, an RTL can receive data from a receive channel and perform the corresponding processing discussed herein. An RTL may include multiple registers for (at least temporarily) storing data and gates for performing (logical) operations (such as range FFT, Doppler FFT, MTI, integration, CFAR, range masking, etc.), and thus can be hard-coded on the RTL. The registers can therefore implement motion event counters.

[0058] Figure 3 An electronic device 20 according to this disclosure is depicted. The electronic device can take various forms. For example, it can be a vehicle (such as a car, truck, or motorcycle). In other examples, the electronic device can be, or may be included in, a consumer product (such as a mobile phone, laptop computer, tablet computer, wearable device like a smartwatch, television, etc.). The electronic device according to this disclosure can also be used in other applications such as home appliances (e.g., motion sensors) or (smart) toilets, surveillance cameras, etc. In other words, the electronic device can be a home appliance, a (smart) toilet, a surveillance camera, etc.

[0059] Therefore, electronic device 20 includes, as referenced Figure 2 The radar sensor 10 is under discussion.

[0060] The electronic device 20 also includes a processing circuit 20 coupled to the radar sensor and configured to execute a predefined action if the radar sensor 10 determines that micro-motion has occurred in the scene. Therefore, micro-motion data is provided from the radar sensor to the processing circuit 21, and the processing circuit 21 receives the micro-motion data to determine whether the predefined action should be executed. Thus, the micro-motion data may indicate the absence of micro-motion or may indicate micro-motion. In different examples, the absence of micro-motion data indicates that no micro-motion has been determined.

[0061] The predefined actions may vary depending on the application in which the electronic device is used. Typically, predefined actions may include activating (or deactivating) the functions of the electronic device. For example, if the electronic device is provided in a mobile phone or laptop computer, the predefined action may include activating a sensor used to unlock the phone (or computer). If the electronic device is provided in a camera, the predefined action may include activating the camera and starting recording. If the electronic device is provided in a television set, the predefined action may include changing a channel, starting an application, increasing (or decreasing) the volume of content being played back, or pausing playback. However, this disclosure should not be limited to any particular function.

[0062] Figure 4 Methods for detecting micro-motions in a scene sensed by a radar sensor having one or more receiving channels are described, as discussed in this paper.

[0063] The method includes 31 receiving radar data 101 output by a radar sensor for each receiving channel, the radar data being arranged as frames for each receiving channel, as discussed herein.

[0064] The method further includes: 32, for each range bin of multiple range bins for each received channel, for each frame and for each range bin of radar data, each range bin corresponding to a range window associated with a radar sensor, extracting micro-motion information from the radar data of the range bin under consideration; and 33, generating / determining a first value 103 from the micro-motion information 102, as discussed herein.

[0065] The method also includes 34, for each received channel, for each frame, for each range cell, determining a second value 104 based on a first value 103 determined for the range cell under consideration at the frame under consideration and a previous first value 103 determined for the range cell under consideration at a previous frame, as discussed herein.

[0066] The method also includes 35, for each distance bin, determining a third value 105 for the distance bin under consideration based on the corresponding second value, as discussed in this paper.

[0067] The method also includes 36, determining the occurrence of micro-motions 106 in the scene based on a third value 105.

[0068] In the example, a non-transient mechanically readable medium is provided on which a program having program code is stored, which is used to perform the methods discussed herein when the program is executed on a processor or programmable hardware.

[0069] In the example, a program with program code is provided that, when executed on a processor or programmable hardware, performs the methods discussed herein.

[0070] Figure 5 Different diagrams are depicted representing the output at different steps of this disclosure.

[0071] In the upper right corner, Figure 61 depicts the signal strength after accumulation / integration but before CFAR is performed. Therefore, Figure 61 depicts the signal strength where the step size is Nvi (in...). Figure 5 In this context, "Nvi" indicates the magnitude (in dB) of the integral over multiple frames (10 in this embodiment) of a certain number of frames. As can be seen from Figure 61, the integral output is noisy, necessitating further processing (e.g., CFAR) and noise suppression.

[0072] In the upper left corner, Figure 62 depicts the CFAR output (before noise suppression) as several distance bins over multiple accumulated frames. As can be seen from Figure 62, the CFAR output is still noisy and contains some outliers.

[0073] In the lower left corner, Figure 63 depicts the CFAR output with subsequent noise suppression based on motion event counters, as discussed herein, as multiple range bins over several accumulated frames. In Figure 63, the motion event counter value is depicted whenever a detection is observed in the corresponding range bin. Compared to Figure 61, Figure 63 represents the count of CFAR detections within a certain time window. As can be seen from Figure 63, the outliers present in Figure 62 are suppressed.

[0074] In the lower right corner, Figure 64 depicts the CFAR output with noise suppression. In Figure 64, ( Figure 3 The low counter values ​​are removed based on thresholding, and thus noise in the detected micro-motions is suppressed. Therefore, Figure 64 illustrates a reliable micro-motion indicator from the object / person after thresholding the motion event counter.

[0075] exist Figure 5In this context, the number of distance bins (N_rb) is 128, the number of frames used for accumulation (Nvi) is 10, the total number of available frames (N) is 3200, and the number of frames with a step size of Nvi (N / Nvi) is 320.

[0076] Based on the principles of this disclosure, a dedicated integrated processor / circuit (ASIP / ASIC) can be used to detect micro-motion markers. Therefore, the requirements for bandwidth adjustment and small formation factor can be maintained (unlike known solutions), and low memory and processing power can also be achieved.

[0077] Combined with the proposed technology or one or more examples described above (e.g., Figures 1 to 5 This will be used to explain further details and aspects of the methods discussed herein. The methods may include one or more additional optional features corresponding to one or more aspects of the proposed technology or one or more examples described above.

[0078] The examples and embodiments described in this article can be summarized as follows:

[0079] An example (e.g., Example 1) relates to an apparatus for detecting micro-motion in a scene sensed by a radar sensor having one or more receiving channels. The apparatus includes processing circuitry configured to receive radar data output by the radar sensor for each receiving channel, the radar data being arranged as frames for each receiving channel. The processing circuitry is further configured to extract micro-motion information from the radar data of the considered range bin for each receiving channel, for each frame, and for each of a plurality of range bins of radar data, each range bin corresponding to a range window associated with the radar sensor, and to generate a first value from said micro-motion information. The processing circuitry is further configured to determine a second value for each receiving channel, for each frame, and for each range bin, based on the first value determined for the considered range bin at the considered frame and a previous first value determined for the considered range bin at a previous frame. The processing circuitry is further configured to determine a third value for each considered range bin based on the corresponding second value. The processing circuitry is further configured to determine the occurrence of micro-motion in the scene based on the third value.

[0080] Another example (e.g., Example 2) relates to a previous example (e.g., Example 1). In this example, in order to determine the occurrence of micro-motion in the scene, the processing circuitry is also configured to apply adaptive thresholding to a third value to determine whether the third value originates from micro-motion.

[0081] Another example (e.g., Example 3) relates to the previous examples (e.g., one of Examples 1 and 2). In this example, adaptive thresholding involves subjecting the third value to a constant false alarm rate.

[0082] Another example (e.g., Example 4) relates to the previous examples (e.g., one of Examples 1 through 3). In this example, in order to determine the occurrence of micro-motion in the scene, the processing circuitry is also configured to filter a third value for one or more predetermined distance bins to remove the predetermined distance bins from subsequent processing.

[0083] Another example (e.g., Example 5) relates to a previous example (e.g., in the case of Example 2 or Example 3, or one of Example 2, Example 3, or Example 4). In this example, in order to determine the occurrence of micro-motion in the scene, the processing circuitry is also configured to increment a corresponding counter for different distance chambers in response to determining that a third value is derived from the micro-motion.

[0084] Another example (e.g., Example 6) relates to the previous examples (e.g., one of Examples 1 through 5). In this example, in order to determine the occurrence of micro-motion in the scene, the processing circuitry is also configured to decrement the corresponding counter for different distance bins in response to determining that the third value is not derived from the micro-motion.

[0085] Another example (e.g., Example 7) relates to a previous example (e.g., one of Example 5 or Example 6). In this example, in order to determine the occurrence of micro-motion in the scene, the processing circuitry is also configured to determine the occurrence of micro-motion in the corresponding distance chamber in response to the value of a counter for the distance chamber meeting a predefined criterion.

[0086] Another example (e.g., Example 8) relates to a previous example (e.g., one of Examples 1 through 7). In this example, in order to determine the second value, the processing circuitry is also configured to perform a moving target indicator algorithm.

[0087] Another example (e.g., Example 9) relates to the previous examples (e.g., one of Examples 1 through 8). In this example, the third value is determined using the absolute value of the second value.

[0088] Another example (e.g., Example 10) relates to a radar sensor that includes means for detecting micro-motion according to previous examples (e.g., one of Examples 1 to 9). The radar sensor also includes one or more transmit channels configured to transmit one or more transmit signals into the radar sensor's field of view. The radar sensor also includes one or more receive channels configured to generate radar data based on the reflection of the received one or more transmit signals.

[0089] Another example (e.g., Example 11) relates to a previous example (e.g., Example 10). In this example, the radar sensor includes a radio frequency integrated circuit (RFIC), and the means for detecting micro-motions is included in the RFIC.

[0090] Another example (e.g., Example 12) relates to a previous example (e.g., Example 11). In this example, the device for micro-motion detection is implemented as a register transfer stage circuit device.

[0091] Another example (e.g., Example 13) relates to an electronic device that includes a radar sensor according to a previous example (e.g., one of Examples 10 to 12). The electronic device also includes processing circuitry coupled to the radar sensor and configured to perform a predefined action if the radar sensor determines that micro-motion has occurred in the scene.

[0092] Another example (e.g., Example 14) relates to a method for detecting micro-motion in a scene sensed by a radar sensor having one or more receiving channels. The method includes receiving radar data output by the radar sensor for each receiving channel, the radar data being arranged as frames for each receiving channel. The method also includes extracting micro-motion information from the radar data of the considered range bins for each receiving channel, for each frame, and for each of a plurality of range bins of radar data, each range bin corresponding to a range window associated with the radar sensor, and generating a first value from said micro-motion information. The method further includes determining a second value for each receiving channel, for each frame, and for each range bin, based on the first value determined for the considered range bin at the considered frame and a previous first value determined for the considered range bin at a previous frame. The method also includes determining a third value for each considered range bin based on the corresponding second value. The method further includes determining the occurrence of micro-motion in the scene based on the third value.

[0093] Another example (e.g., Example 15) relates to a non-transient machine-readable medium on which a program is stored, the program having program code for executing a method according to a previous example (e.g., Example 14) when the program is executed on a processor or programmable hardware.

[0094] Another example (e.g., Example 16) involves a program with program code that, when executed on a processor or programmable hardware, performs a method according to a previous example (e.g., Example 14).

[0095] Aspects and features described by a particular one in a previous example can also be combined with one or more of the other examples to replace the same or similar features in other examples or additionally introduce features into other examples.

[0096] Examples may also be or relate to (computer) programs that include program code, which, when executed on a computer, processor, or other programmable hardware component, perform one or more of the methods described above. Therefore, the steps, operations, or processes of the different methods described above may also be performed by a programmed computer, processor, or other programmable hardware component. Examples may also cover programmable storage devices, such as digital data storage media, which are machine-readable, processor-readable, or computer-readable and encoded and / or contain machine-executable, processor-executable, or computer-executable programs or instructions. For example, programmable storage devices may include or be digital storage devices, magnetic storage media (such as disks or tapes), hard disk drives, or optically readable digital data storage media. Other examples include computers, processors, control units, (field)programmable logic arrays ((F)PLAs), (field)programmable gate arrays ((F)PGAs), graphics processing units (GPUs), application-specific integrated circuits (ASICs), integrated circuits (ICs), or system-on-a-chip (SoC) systems programmed to perform the steps of the methods described above.

[0097] It should also be understood that the disclosure of steps, processes, operations, or functions in the specification or claims should not be construed as implying that these operations must depend on the described order, unless expressly stated in individual cases or necessary for technical reasons. Therefore, the preceding description does not limit the execution of steps or functions to a particular order. Furthermore, in other examples, a single step, function, process, or operation may include and / or be decomposed into several sub-steps, sub-functions, sub-processes, or sub-operations.

[0098] If aspects of a device or system have already been described, these aspects should also be understood as descriptions of the corresponding method. For example, functional aspects of a block, device, or device or system may correspond to characteristics of the corresponding method (such as method steps). Therefore, aspects of the method description should also be understood as descriptions of the properties or functional characteristics of the corresponding block, element, device, or system.

[0099] The following claims are thus incorporated into the detailed description, wherein each claim may be considered an independent example. It should also be noted that, although in the claims, a dependent claim refers to a specific combination with one or more other claims, other examples may also include combinations of dependent claims with the subject matter of any other dependent or independent claim. Such combinations are explicitly stated herein unless, in individual cases, it is stated that a particular combination is not expected. Furthermore, the features of a claim should also be included in any other independent claim, even if that claim is not directly defined as dependent on that other independent claim.

Claims

1. An apparatus (1) for detecting micro-motions in a scene sensed by a radar sensor (10) having one or more receiving channels, the apparatus comprising a processing circuit (2) configured to: Receive radar data output by the radar sensor (10) for each receiving channel, the radar data being arranged as frames for each receiving channel; For each received channel, for each frame, and for each of the multiple range bins of the radar data, each range bin corresponds to a range window associated with the radar sensor (10), micro-motion information is extracted from the radar data of the considered range bins and a first value is generated based on the micro-motion information; For each received channel, for each frame, for each range cell, a second value is determined based on the first value determined for the range cell at the considered frame and the previous first value determined for the range cell at the previous frame. For each distance bin, a third value for the considered distance bin is determined based on the corresponding second value; and The occurrence of the micro-motion in the scene is determined based on the third value.

2. The apparatus (1) according to claim 1, wherein, In order to determine the occurrence of the micro-motion in the scene, the processing circuit device (2) is further configured to: Adaptive thresholding is applied to the third value to determine whether the third value is derived from the micro-motion.

3. The apparatus (1) according to claim 2, wherein the adaptive thresholding includes subjecting the third value to constant false alarm rate detection.

4. The apparatus (1) according to any one of claims 1 to 3, wherein, In order to determine the occurrence of the micro-motion in the scene, the processing circuit device (2) is further configured to: The third value of one or more predetermined distance bins is filtered to remove the predetermined distance bins from subsequent processing.

5. The apparatus (1) according to any one of claims 2 to 4, wherein, when subordinate to 2 or 3, In order to determine the occurrence of the micro-motion in the scene, the processing circuit device (2) is further configured to: In response to determining that the third value is derived from the micro-motion, the corresponding counter is incremented for different distance bins.

6. The apparatus (1) according to any one of claims 1 to 5, wherein, In order to determine the occurrence of the micro-motion in the scene, the processing circuit device (2) is further configured to: In response to determining that the third value is not derived from the micro-motion, the corresponding counter is decremented for the different distance bins.

7. The apparatus (1) according to claim 5 or 6, wherein, In order to determine the occurrence of the micro-motion in the scene, the processing circuit device (2) is further configured to: In response to the value of the counter for the distance chamber meeting a predetermined criterion, the occurrence of the micro-motion in the corresponding distance chamber is determined.

8. The apparatus (1) according to any one of claims 1 to 7, wherein, in order to determine the second value, the processing circuit apparatus (2) is configured to execute a moving target indicator algorithm.

9. The apparatus (1) according to any one of claims 1 to 8, wherein the third value is determined using the absolute value of the second value.

10. A radar sensor (10), comprising: The device for detecting micro-motion according to any one of claims 1 to 9 (1); One or more transmission channels are configured to transmit one or more transmission signals into the field of view of the radar sensor (10); as well as One or more receiving channels are configured to generate the radar data based on the reflection of the received one or more transmitted signals.

11. The radar sensor (10) according to claim 10, wherein the radar sensor comprises a radio frequency integrated circuit (RFIC), and wherein the device (1) for detecting micro-motion is included in the RFIC.

12. The radar sensor (10) according to claim 11, wherein the device (1) for micro-motion detection is implemented as a register transfer stage circuit device.

13. An electronic device (20), comprising: The radar sensor (10) according to any one of claims 10 to 12; as well as The processing circuit device (21) is coupled to the radar sensor (10) and configured to perform a predetermined action if the occurrence of micro-motion in the scene is determined by the radar sensor (10).

14. A method for detecting micro-motion in a scene sensed by a radar sensor (10) having one or more receiving channels, the method comprising: Receive (31) radar data output by the radar sensor (10) for each receiving channel, the radar data being arranged as frames for each receiving channel; For each receiving channel, for each frame, and for each of the multiple range bins of the radar data, each range bin corresponds to a range window associated with the radar sensor (10), micro-motion information is extracted (32) from the radar data of the range bin under consideration and a first value is generated (33) based on the micro-motion information; For each received channel, for each frame, for each range cell, a second value is determined based on the first value determined for the range cell at the considered frame and the previous first value determined for the range cell at the previous frame. For each distance bin, a third value for the distance bin under consideration is determined based on the corresponding second value; and The occurrence of the micro-motion in the scene is determined based on the third value (36).

15. A non-transitory machine-readable medium having a program stored thereon, the program having program code for executing the method of claim 14 when the program is executed on a processor or programmable hardware.

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