Apparatus, radar system and method for detecting target movement

Abstract

The invention relates to a device, a radar system and a method for detecting motion of a target. An apparatus for detecting motion of a target in a field of view of a radar sensor is disclosed, comprising processing circuitry configured to acquire an amplitude of a spectrum of a received signal of the radar sensor. The spectrum includes a first portion and a second portion positioned symmetrically with respect to a center frequency within a frequency bandwidth divided into windows. For at least one window in the first portion, the processing circuitry is configured to determine a window threshold based on an amplitude of the spectrum within one or more windows in the second portion. For at least one window in the second portion, the processing circuitry is configured to determine a window threshold based on an amplitude of the spectrum within one or more windows in the first portion. The processing circuitry is further configured to detect target motion in response to an amplitude of the spectrum exceeding a window threshold in at least one window within the frequency bandwidth.

Description

Technical Field

[0001] The present disclosure relates to radar data processing. Specifically, examples relate to apparatus, radar systems, methods, and programs for detecting target motion in a field of view of a radar sensor. Background Art

[0002] When using radar sensors to detect the motion of a target, various methods have been used to distinguish informative signals from noise. For detection, a threshold can be implemented to determine whether the signal contains a pattern of interest or simply a random pattern. A fundamental issue when using radar sensors is finding an appropriate threshold level that maximizes correct detections and minimizes false detections, thereby saving power. Radar systems should also be able to detect slight motion while preventing false alarms from interference (e.g., fans, curtains, blinds, speaker vibrations, bushes, trees, rain, snow, etc.) or jammers (i.e., other radar systems using the same or adjacent RF frequencies), which can result in increased power consumption. Current solutions using thresholds have proven to be insufficient, especially for detecting the motion of a target.

[0003] Therefore, radar data processing that can achieve appropriate thresholding of the signal spectrum is required. Summary of the Invention

[0004] This requirement is met by the subject matter of the independent claims. Further advantageous embodiments are given in the dependent claims.

[0005] According to a first aspect, the present disclosure relates to an apparatus for detecting target motion in the field of view of a radar sensor. The apparatus includes a processing circuit system configured to obtain the amplitude of the spectrum of a received signal of the radar sensor. The spectrum includes a first part and a second part within a frequency bandwidth divided into bins. The first part and the second part are symmetrically positioned relative to a center frequency. For at least one window in the first part, the processing circuit system is configured to determine a window threshold based on the amplitude of the spectrum within one or more windows in the second part. For at least one window in the second part, the processing circuit system is configured to determine the window threshold based on the amplitude of the spectrum within one or more windows in the first part. In addition, the processing circuit system is configured to detect target motion in response to the amplitude of the spectrum in at least one window within the frequency bandwidth exceeding the window threshold.

[0006] According to a second aspect, the present disclosure relates to a radar system comprising an apparatus as described herein and a radar sensor configured to generate a receive signal.

[0007] According to a third aspect, the present disclosure relates to a method for detecting target motion in the field of view of a radar sensor. The method includes obtaining the amplitude of a spectrum of a received signal of the radar sensor. The spectrum includes a first part and a second part within a frequency bandwidth divided into windows. The first part and the second part are symmetrically positioned relative to a center frequency. The method also includes: for at least one window in the first part, determining a window threshold based on the amplitude of the spectrum within one or more windows in the second part. The method also includes: for at least one window in the second part, determining a window threshold based on the amplitude of the spectrum within one or more windows in the first part. In addition, the method includes detecting target motion in response to the amplitude of the spectrum in at least one window within the frequency bandwidth exceeding the window threshold.

[0008] According to a fourth aspect, the present disclosure relates to a program having a program code for performing a method as described herein when the program is executed on a processor or programmable hardware. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Some examples of apparatus and / or methods will be described below, by way of example only, and with reference to the accompanying drawings, in which:

[0010] Figure 1A schematically illustrates an exemplary apparatus for detecting target motion in a field of view of a radar sensor;

[0011] Figure 1B schematically illustrates an exemplary radar system for detecting target motion in a field of view of a radar sensor;

[0012] Figure 2 depicts an exemplary frequency spectrum including a first portion and a second portion having amplitudes distributed over an exemplary bandwidth and centered about an exemplary center frequency;

[0013] Figure 3 An exemplary spectrum is depicted wherein each of a plurality of windows has a corresponding window threshold;

[0014] Figure 4 depicts an exemplary spectrum having two frequency bins, each frequency bin being depicted with a corresponding bin threshold based on the frequency bin in the relative portion;

[0015] Figure 5 An exemplary spectrum is depicted where a window threshold is exceeded by the amplitude within the corresponding window;

[0016] Figure 6 An exemplary spectrum is depicted in which the window threshold for one frequency bin is depicted based on the amplitude within five other frequency bins in the relative section;

[0017] Figure 7A An exemplary spectrum is depicted in which a window threshold for one frequency bin is depicted as being based on the amplitude within four other frequency bins in relative sections;

[0018] Figure 7B An exemplary spectrum is depicted in which the window threshold for one frequency bin is depicted based on the amplitude within three other frequency bins in the relative portion;

[0019] Figure 8 An exemplary spectrum is depicted in which a plurality of frequency bins are excluded having determined corresponding bin thresholds;

[0020] Figure 9A An exemplary spectrum is depicted with local peak amplitudes within the frequency window;

[0021] Figure 9B An exemplary spectrum is depicted with the correction amplitude within the frequency window of the previous spike amplitude;

[0022] Figure 10A A first time frame and a corresponding spectrum are depicted, wherein the first time frame has a window threshold;

[0023] Figure 10B depicting subsequent time frames and corresponding spectra, wherein the subsequent time frames have window thresholds; and

[0024] Figure 11 A flow chart of an exemplary method for detecting target motion in a field of view of a radar sensor is provided. DETAILED DESCRIPTION

[0025] Some examples are now 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 of features and equivalents and substitutes of features. In addition, the terms used in this article to describe certain examples should not limit other possible examples.

[0026] Throughout the description of the 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 functions. For clarity, the thickness of lines, layers and / or regions in the drawings may also be exaggerated.

[0027] When two elements A and B are combined using "or", this should be understood as discussing all possible combinations, i.e., only A, only B, and A and B, unless expressly stated otherwise in individual cases. As alternative wording for the same combination, "at least one of A and B" or "A and / or B" can be used. The same applies to combinations of more than two elements.

[0028] If singular forms such as "a," "an," and "the" are used and the use of only a single element is not explicitly or implicitly defined as mandatory, other examples may also use several elements to implement the same function. If the function is described below as being implemented using multiple elements, other examples may use a single element or a single processing entity to implement the same function. It is further understood that the terms "include," "including," "comprise," and / or "comprising" when used to describe the presence of specified features, integers, steps, operations, processes, elements, components, and / or groups thereof do not preclude the presence or addition of one or more other features, integers, steps, operations, processes, elements, components, and / or groups thereof.

[0029] Thresholding is commonly used in radar data processing to determine target motion within the field of view of a radar sensor (e.g., a Doppler radar system). Thresholding can be implemented based on the amplitude of the frequency spectrum, specifically within various frequency components (e.g., frequency bins). Each frequency bin can be associated with a Doppler velocity, which is the speed of a moving target as measured by the radar system using the Doppler effect. If such a target is within the field of view of a radar sensor, the motion of the target can cause variations in the reflected wave compared to the original transmitted wave from the radar system, which can affect the amplitude values ​​within each frequency bin according to a structured pattern.

[0030] Target motion can be detected by analyzing the amplitude of the spectrum. In particular, it can be found that there is a difference between the amplitude of the spectrum corresponding to the field of view of any scene with and without target motion. How the thresholds in the spectrum are implemented can determine the accuracy of such detection. Depending on the type of motion the target may exhibit overall, corresponding window thresholds can be implemented for windows in the spectrum. For example, fixed thresholds can be implemented for corresponding windows, and detection can be based on whether the amplitude of the spectrum exceeds the fixed threshold within any window. However, this may result in suboptimal sensitivity in certain situations, which may lead to false positives due to interference or interference in the received signal.

[0031] A common implementation that can better adapt to various situations is the CFAR (Constant False Alarm Rate) algorithm, which aims to maintain a constant false alarm rate. Common CFAR algorithms examine the amplitude within a frequency window near the measured window to find an appropriate threshold. As a result, CFAR algorithms can provide adaptive thresholds for the corresponding frequency window of each newly generated spectrum, which is effective for different noise levels and in various environments. However, they may still be unsuitable for detecting motion caused by specific targets and may not adequately resolve the problem of interfering objects or interfering objects in the target background.

[0032] Certain targets can exhibit certain types of motion, which can result in predictable or structured changes in spectral amplitude. For example, the spectral amplitude of a field of view containing human motion may be generally asymmetric within a specific bandwidth, while a field of view lacking such motion or anything resembling motion may be generally symmetric, even in the presence of interfering or intervening objects. CFAR and other adaptive algorithms do not exploit these characteristics, but instead trigger detection regardless of whether the spectral amplitude is symmetric or asymmetric. A component that exploits these symmetric and asymmetric characteristics for target motion detection is described below.

[0033] Figure 1A A block diagram of the apparatus 100 is schematically illustrated. The apparatus 100 will be considered in the context of a radar system 150, as described below with reference to Figure 1B As explained above, radar system 150 includes radar sensor 140 and apparatus 100. Apparatus 100 is configured to detect motion of target 170 in the field of view (scene) of radar sensor 140. Although apparatus 100 and radar sensor 140 are depicted as separate blocks, in other examples, apparatus 100 may be partially or fully included in radar sensor 140. In other words, apparatus 100 may be external to radar sensor 140 or integrated (e.g., partially or fully) into radar sensor 140. For example, apparatus 100 may be distributed between radar sensor 140 and a location external to radar sensor 140.

[0034] The apparatus 100 includes a processing circuit system 102 and an optional interface circuit system 104. The processing circuit system 102 may be, for example, a single dedicated processor, a single shared processor, or multiple individual processors (some or all of which may be shared), a digital signal processor (DSP) hardware, an application specific integrated circuit (ASIC), a microcontroller, or a field programmable gate array (FPGA). The processing circuit system 102 may optionally be coupled to, for example, a read-only memory (ROM), a random access memory (RAM), and / or non-volatile memory for storing software.

[0035] Where interface circuitry 104 is present, interface circuitry 104 can be communicatively coupled (e.g., via a wired or wireless connection) to processing circuitry 102, e.g., for data exchange between interface circuitry 104 and processing circuitry 102. Interface circuitry 104 can be any device or component for transmitting or exchanging data. Where apparatus 100 includes interface circuitry 104, interface circuitry 104 can be configured to receive data indicative of received signal 130 from radar sensor 140. For example, interface circuitry 104 can be communicatively coupled to radar sensor 140 or a storage device storing data. Interface circuitry 104 can receive data indicative of received signal 130, e.g., via a wired or wireless coupling to radar sensor 140 or a storage device.

[0036] Depending on the specific implementation, the device 100 may omit the interface circuit system 104. In some implementations, the device 100 may be configured to receive the received signal 130 of the radar sensor 140 with the aid of the processing circuit system 102, such as Figure 1A As shown, in other implementations, apparatus 100 may be configured to receive receive signal 130 with the aid of interface circuitry 104. For example, processing circuitry 102 may determine data indicative of receive signal 130. Processing circuitry 102 may also be integrated into radar sensor 140. In the case where apparatus 100 is integrated into radar sensor 140, processing circuitry 102 and radar sensor 140 may be jointly integrated (embedded) into a single semiconductor chip or multiple semiconductor chips. In the case where apparatus 100 is only partially included in radar sensor 140, radar system 150 may perform distributed processing to execute corresponding portions of the processing steps.

[0037] Processing circuitry 102 may also partially determine data indicative of received signal 130. For example, processing circuitry 102 may determine a first portion of the data, while at least one external processing circuitry may determine at least a second portion of the data. Processing circuitry 102 and the external processing circuitry may be connected, for example, within a distributed computing environment, for jointly determining data indicative of received signal 130. In this case, processing circuitry 102 may be integrated into radar sensor 140 or external to radar sensor 140. Processing circuitry 102 may receive the second portion of the data, for example, via an interface to the external processing circuitry (such as interface circuitry 104), and further process the first and second portions of the data.

[0038] Processing circuitry 102 may be partially integrated into radar sensor 140 and partially external to radar sensor 140. In this case, interface circuitry 104 is optional. For example, processing circuitry 102 may include a first portion (first processing circuitry) integrated into radar sensor 140 and a second portion (second processing circuitry) external to radar sensor 140. In this case, the determination and / or further processing of data may be performed by the first and second portions of processing circuitry 102 in a distributed manner.

[0039] The radar sensor 140 may be any device that uses radio waves to, for example, detect and locate objects. The radar sensor 140 may be configured to transmit a radio frequency signal 120 (Tx signal) into the field of view of the radar sensor 140 and generate a received signal 130 based on a reflection 122 (echo; Rx signal) of the radio frequency signal 120, such as Figure 1B shown.

[0040] RF signal 120 is depicted as reflecting from target 170. Target 170 is depicted as a person in motion, but may be designated as any object exhibiting similar motion (e.g., a person or animal exhibiting similar motion, etc.). The motion of target 170 may be macroscopic motion or motion on a larger scale. More specifically, macroscopic motion may refer to a significant change in the position of target 170 over a given time scale, which may be caused by, for example, walking or running. Other macroscopic motions may be body motions that result in significant changes in the position of certain body parts. Macroscopic motions may be noticeable and detectable compared to less detectable minor motions that involve less significant changes in position over the same given time scale.

[0041] Received signal 130 may be any type of signal generated in a receiver of radar sensor 140. Received signal 130 may be an intermediate frequency (IF) signal, which may be created, for example, by mixing reflection 122 with a local oscillator signal of a specific frequency. Processing circuitry 102 may determine data indicative of received signal 130 by, for example, sampling received signal 130 and further processing the data. Processing circuitry 102 may optionally modify the sampled received signal in a pre-processing step, for example, for noise reduction, DC removal, etc. For example, apparatus 100 may include a memory configured to store such generated data.

[0042] Radar sensor 140 or an external device coupled to radar sensor 140 can generate data indicative of received signal 130 (e.g., an IF signal) based on received reflections 122 of RF signal 120 by, for example, sampling received reflections 122 with an analog-to-digital converter (ADC). For example, radar sensor 140 can use a mixer to mix received reflections 122 with a replica of transmitted signal 120 to produce IF signal xIF(t) (e.g., a Doppler or beat signal). Radar sensor 140 can include one or more antennas for receiving reflected signals (reflections) 122. Furthermore, radar sensor 140 can include an amplifier for receiving multiple reflected signals from its antennas. IF signal xIF(t) can be filtered using a low-pass filter (LPF) and then sampled by the ADC to generate time-domain data in a discrete form.

[0043] In some embodiments, the ADC may advantageously sample the filtered beat signal xout(t) at a sampling frequency for generating a sampling bandwidth such that it is greater than or equal to the bandwidth of the received signal 130 received by the receive antenna. Thus, in some embodiments, the sampling frequency may be twice the highest frequency (or bandwidth) of the received signal 130 to achieve such a sampling bandwidth. This will comply with the Nyquist-Shannon theorem, which states that the sampling frequency should be at least twice the signal bandwidth to avoid distortion. For example, distortion may occur due to aliasing, where different frequency components in the radar signal become indistinguishable or distorted. The Nyquist-Shannon theorem assumes that the sampled signal is band-limited, with no frequency components exceeding a maximum frequency.

[0044] Radar sensor 140 may be, for example, a Doppler radar sensor. When target 170 moves (moves toward or away from radar sensor 140), a Doppler (frequency) shift may be detected, where the Doppler shift is proportional to the velocity of target 170. More specifically, the Doppler shift of target 170 may be determined by capturing reflections 122 of RF signal 120 using radar sensor 140 and processing the data using processing circuitry 102 of device 100.

[0045] In a specific example of a Doppler radar sensor, the received signal 130 may have a bandwidth of 4 kHz, which may include a range of ±2 kHz around a center frequency (e.g., 60 GHz). In general, the range (i.e., bandwidth) of the Doppler signal of an embodiment using a Doppler radar sensor may be in the range of Hz to kHz. As described above, the mixer may convert the received signal 130 into an IF signal, where xout(t) has a range of ±2 kHz centered about 0 Hz. In other words, the received signal 130 may be mixed from the original center frequency (e.g., 60 GHz) to a center frequency (e.g., baseband) of 0 Hz. Furthermore, the ADC may sample the received signal 130 at a sampling frequency greater than or equal to 4 kHz. Thus, the processing steps may be performed over a bandwidth that includes the full range of ±2 kHz on either side of the center frequency (e.g., 0 Hz). This may result in positive and negative sides around the center frequency, as shown in FIG. Figures 2 to 10B shown.

[0046] The sampling of the received signal 130 described above may result in the acquisition of time domain data, including in-phase data (I component) representing the real part of the received signal 130 and quadrature data (Q component) representing the imaginary (complex) part of the received signal 130. The I and Q components can be obtained by separating the received signal 130 into two orthogonal channels, which can be achieved using a mixer or demodulator that multiplies the received signal 30 by two reference signals or in-phase and quadrature carriers. The processing circuit system 100 can be configured to perform a discrete (fast) Fourier transform (DFT) or a Doppler DFT to obtain a periodic complex spectrum including amplitude and phase. In some cases, only the I component or only the Q component of the received signal 130 may be sufficient, while in other embodiments, both the I and Q components may be applied.

[0047] In embodiments including a Doppler radar sensor, a mixer using both the I and Q components can be specifically used to determine whether target 170 is moving toward or away from radar sensor 140. Generally, a Doppler (frequency) shift can be used to detect the target's velocity, while a phase shift between the I and Q components can be caused by the Doppler shift and can be used to determine its direction (toward or away from radar sensor 140). An increase in the phase shift between the I and Q components can indicate target 170's movement toward radar sensor 140, while a decrease in the phase shift can indicate target 170's movement away from radar sensor 140.

[0048] In some embodiments, the radar sensor may be, for example, an FMCW (Frequency Modulated Continuous Wave) radar sensor. Transmitted RF signal 122 may be in the form of multiple chirps, including portions of received reflected signal 122 associated with corresponding transmitted chirps. A chirp may be an RF signal whose frequency varies over time. The chirp frequency may sweep across a specific frequency range, such as a chirp bandwidth. For example, the chirp may be a linearly modulated signal, i.e., a signal whose frequency increases or decreases linearly over time.

[0049] In the example of an FMCW radar sensor, received signal 130 may also be mixed down to baseband. The Doppler shift is centered around a beat frequency, which depends on the range determined for target 170. Generally, for the example of an FMCW radar sensor, the beat frequency may be in the kHz to MHz range. For an FMCW radar sensor, a Doppler DFT may also be performed in addition to a range DFT.

[0050] Analysis of target motion detected using an FMCW radar sensor may also include generating a two-dimensional (2D) range-Doppler map, which can provide a deeper understanding of the motion of target 170 relative to its surroundings. Generally, a range-Doppler map is a commonly used representation in radar signal processing that is used to visualize the range and Doppler characteristics of a detected target. A range-Doppler map may consist of a range axis representing the distance (or range) of the detected target from the radar system and a Doppler axis representing the radial velocity or motion of the target along the line of sight (i.e., the direction or path that the radar signal travels from the transmitter to the target and back to the receiver). By combining these two dimensions, a 2D map may be formed in which each point represents the range and velocity information of the target. In the case where the radar sensor is an FMCW radar sensor, the processing circuit system 102 may be configured to output a 2D FMCW range-Doppler map.

[0051] In particular, the amplitude of the spectrum can be based on the Doppler shift of the received signal 130 and can be used for further processing to detect the motion of the target 170. The processing circuit system 102 can be configured to obtain the amplitude of the spectrum based on the received signal 130 using the I component. In general, the amplitude of the spectrum can represent a set of amplitudes or absolute values ​​of multiple complex amplitudes in the frequency domain. Here, since the amplitude of the spectrum can be processed without considering phase information, the spectrum obtained by DFT of the received signal 130 is referred to as an amplitude spectrum. The amplitude spectrum can provide information about the intensity or strength corresponding to the frequency component (e.g., frequency bin) without considering phase information.

[0052] Figure 2 An exemplary amplitude spectrum 200 is provided. The amplitude spectrum is acquired within a frequency bandwidth 220 of the received signal 130, which frequency bandwidth will be referred to as bandwidth 220. The amplitude spectrum 200 includes a first portion 200-i and a second portion 200-ii within the bandwidth 220. The first portion 200-i and the second portion 200-ii are positioned symmetrically relative to a center frequency 230 (e.g., 0 Hz from the previous example). Therefore, the first portion 200-i and the second portion 200-ii will also be referred to as relative portions. Positioned symmetrically relative to the center frequency 230, the first portion 200-i and the second portion 200-ii can each include an equivalent frequency range within the bandwidth 220. As shown, this can be an equal number of frequency bins of equal size or width. One or more frequency bins within the bandwidth can be outside the first portion 200-i and the second portion 200-ii; (e.g., window 8 and window 16). The first portion 200-i and the second portion 200-ii, the bandwidth 220, and the center frequency 230 are located in the Figures 2 to 10B The amplitude spectrum of each is shown in .

[0053] The bandwidth 220 may be defined by the sampling frequency used to generate discrete time domain data by sampling the received signal 130, as previously described for Figure 1B The amplitude spectrum is shown on the horizontal axis 202 and the vertical axis 204 (each axis also applies to the other spectrum, only Figure 2 ). The horizontal axis 202 may represent the frequency scale (e.g., Hz) in the spectrum. The vertical axis 204 may represent the magnitude (e.g., intensity or amplitude) scale of the magnitude spectrum obtained from the DFT of the time domain data (i.e., the sampled received signal 130). Each depicted magnitude spectrum (i.e., Figures 2 to 10B ) shows that the frequency amplitude values ​​of larger positive and negative frequencies away from the center frequency 230 decrease, which may correspond to the increase of noise at smaller frequencies close to 0 Hz.

[0054] A general principle of digital signal processing is that sampled time-domain signals have a periodic spectrum. Given this periodicity, it is more efficient to consider only one period of the amplitude spectrum in data processing for detecting the motion of target 170. Therefore, the amplitude spectrum used for processing can be limited to a frequency bandwidth 220. For example, bandwidth 220 can include a frequency range from 0 Hz to the sampling frequency, or a frequency range from -0.5 times the sampling frequency to 0.5 times the sampling frequency. The two examples above can be considered to present equivalent data in different forms. For ease of explanation, this article will use the latter version of bandwidth 220, which is between the negative and positive values ​​of half the sampling frequency. Therefore, the amplitude spectrum 200 of received signal 130 within bandwidth 220 can be divided into a negative portion and a positive portion, divided by center frequency 230. The negative and positive portions are also symmetrically positioned relative to center frequency 230. Therefore, the first portion 200-i and the second portion 200-ii, symmetrically positioned relative to center frequency 230 within bandwidth 220, will also be referred to as negative portion 200-i and positive portion 200-ii, respectively.

[0055] The negative portion 200-i and the positive portion 200-ii of the bandwidth 220, which are symmetrically positioned relative to the center frequency 230, can be aligned with the negative and positive Doppler shifts caused by the motion of the target 170. In general, a Doppler shift is a frequency change that can be observed using a radar sensor. As a target moves toward or away from a radar system, the Doppler effect causes a frequency shift in the reflected radar signal. This frequency shift can be proportional to the speed of the target along the line of sight between the radar and the target (i.e., the direction or path that the radar signal travels from the transmitter to the target and back to the receiver). The Doppler shift that occurs within the field of view of the radar sensor may affect specific parts or components of the amplitude spectrum.

[0056] To analyze the magnitude spectrum within bandwidth 220, bandwidth 220 is divided into a plurality of (frequency) bins. Each frequency bin can represent a frequency component having a lower frequency limit and an upper frequency limit on the frequency scale. Magnitude spectrum 200 provides an example of a magnitude spectrum, which can include any number of frequency bins, with multiple frequency bins located on one side of center frequency 230 (e.g., the left side for the first / negative portion) and multiple frequency bins located on the opposite side of center frequency 130 (e.g., the right side for the second / positive portion). Negative portion 200-i and positive portion 200-ii can also be separated by one or more frequency bins.

[0057] 16 windows b1 to b16 of the corresponding spectrum are depicted, wherein the center frequency 230 is located in the middle of the eighth window b8. Figure 2An example of 16 windows is provided, but other examples not shown may include a different number of windows, such as 32, 128, or 1024 windows, or other powers of 2, which may enable more efficient digital processing. In general, the configuration of apparatus 100 described herein may be used to divide bandwidth 220 into any number of windows.

[0058] Each window may be centered at a window frequency, where the window frequency ranges from a lower frequency limit of the window to an upper frequency limit of the window, the value of which may depend on a pre-specified resolution. More specifically, certain windows may be associated with ranges of Doppler shifts caused by specific changes in the velocity of target 170 relative to radar sensor 140. Frequency windows in negative portion 200-i may be associated with negative Doppler velocities, where the Doppler shift is caused by target 170 moving away from radar sensor 140, and frequency windows in positive portion 200-ii may be associated with positive Doppler velocities, where target 170 is moving toward radar sensor 140.

[0059] Each window is represented by a rectangular box with a height proportional to the amplitude in the corresponding window. For the sake of simplicity, the value of the amplitude in the corresponding window will be referred to as its amplitude value. In the example of the spectrum 200 depicted, window 8 corresponds to the highest amplitude value, followed by windows 7 and 9, and generally has windows with amplitude values ​​continuously decreasing as they move away from the center frequency 230, until they reach the edge of the bandwidth 220, windows 1 and 16 (for example, for larger Doppler shift / speed, noise decreases). In the amplitude spectrum 200, the center frequency 230 can be positioned as being associated with zero Doppler shift (i.e., 0 Hz). In the negative part 200-i and the positive part 200-ii, windows closer to the center frequency 230 can be associated with lower Doppler shifts, while in the negative part 200-i and the positive part 200-ii, windows further away from the center frequency 230 can be associated with larger Doppler shifts. These windows can also correspond to frequencies that are proportional to the Doppler velocity.

[0060] By analyzing the amplitude distribution and characteristics (eg, symmetric / asymmetric features) within corresponding windows of amplitude spectrum 200 , the motion of target 170 may be detected. Figure 2 、 Figure 3 、 Figure 4 、 Figure 6 、 Figure 7A 、 Figure 7B and Figure 8 The spectrum corresponds to a roughly symmetrical amplitude spectrum. Actual examples of amplitude spectra are never completely symmetrical (e.g., due to noise), so the depicted symmetrical amplitude spectrum (depicted as completely symmetrical) can be understood as an example of an amplitude spectrum that is generally symmetrical (i.e., sufficiently symmetrical with no significant asymmetry).

[0061] Detection of target 170 motion can specifically exploit the symmetric or asymmetric nature of the frequency spectrum, depending on the type of target 170 and the motion it tends to exhibit. In the case of a human or similarly moving creature or object, motion may affect the amplitude within different frequency bins, but generally only affects the amplitude on one side of the frequency spectrum. For example, most of a person's motion within radar sensor 140's field of view may be in a single direction, toward or away from radar sensor 140. This may be due to walking or movement of a particular body part, for example, which may occur in a single direction (toward or away from radar sensor 140) within the time frame of received signal 130 being analyzed. Therefore, motion of target 170, particularly a human target, generally results in asymmetric changes in the amplitude spectrum.

[0062] On the other hand, common interferences generally within the field of view of target 170 (e.g., vibrations from fans, curtains, blinds, speakers, bushes, trees, rain, snow, etc.) typically affect the frequency windows of both the negative and positive portions of bandwidth 220. For example, vibrations may cause rapid alternating motion toward and away from radar sensor 140. Other examples may involve highly cluttered areas within the field of view, which may cause partial scattering of the transmitted and reflected signals, thereby affecting both sides of amplitude spectrum 200. More specifically, the affected frequency components may generally be located symmetrically with respect to center frequency 230 and be affected by approximately the same amount. Thus, spectral processing may be performed, particularly within bandwidth 220, to detect asymmetrical changes caused by target 170 motion (such as human motion), while ignoring symmetrical changes caused by interference or disturbances.

[0063] This can be achieved by providing corresponding window thresholds for multiple frequency bins within bandwidth 220. Applying such window thresholds to an amplitude spectrum (such as amplitude spectrum 200 shown) can provide a convenient form of detection for specific types of targets 170. Such detection can also be performed in a variety of situations without the need for manual adjustment. Various embodiments of device 100 can be used to detect the movement of humans (or other similarly moving creatures or objects). This is because most human movements result in asymmetric changes in the amplitude spectrum that can be generated using radar system 150.

[0064] Figure 3 、 Figure 4 and Figure 5 Illustrative examples that provide more detailed window thresholds are provided in Figure 6 7 discusses further embodiments in more detail, particularly embodiments related to how to determine the window threshold. Figure 8 9 discusses additional embodiments related to how to exclude certain frequency windows from determining the window threshold and reduce false detection. Figure 10A and Figure 10B The adaptive nature of such processing steps for different portions of the time domain data of the received signal 130 is discussed.

[0065] Similar to Figure 2 , Figure 3 Magnitude spectrum 300 is depicted, wherein a plurality of depicted windows also have corresponding window thresholds. For apparatus 100, processing circuitry 102 is configured to determine a window threshold for at least one window in first (i.e., negative) portion 200-i based on the magnitude of the spectrum within one or more windows in second (i.e., positive) portion 200-ii. Furthermore, processing circuitry 102 is configured to determine a window threshold for at least one window in second portion 200-ii based on the magnitude of the spectrum within one or more windows in first portion 200-i. Processing circuitry 102 is further configured to detect motion of target 170 based on the magnitude of the spectrum in at least one window within bandwidth 220 exceeding the window threshold.

[0066] In some embodiments, processing circuitry 102 is configured to determine, for each of a plurality of windows within first (i.e., negative) portion 200-i, a respective window threshold, each window threshold being based on the amplitude of a spectrum within one or more windows in second (i.e., positive) portion 200-ii. Each respective window threshold in first portion 200-i may correspond to an amplitude within a unique set of windows (i.e., one or more windows) in second portion 200-ii. This may be reversed for respective window thresholds in second portion 200-ii. Processing circuitry 102 may be configured to determine, for each of a plurality of windows in second (i.e., positive) portion 200-ii, a respective window threshold, each window threshold being based on the amplitude of a spectrum within one or more windows in first (i.e., negative) portion 200-i. Each respective window threshold in second portion 200-ii may correspond to an amplitude within a unique set of windows (i.e., one or more windows) in first portion 200-i.

[0067] In order to reliably detect the motion of the target 170, the plurality of windows in each portion 200-i, 200-ii having the determined respective thresholds may be a majority of the total number of windows in the respective portion. Figure 3 , all depicted windows (b1 to b7) of the first (negative) portion 200-i have corresponding window thresholds determined, while all depicted windows (including b9 to b15, but excluding b16) of the second (positive) portion 200-ii have corresponding window thresholds determined. In some embodiments, exclusion of certain windows may be applied (e.g., Figure 8), while maintaining a majority or a large number of windows with corresponding window thresholds for reliable detection. In other embodiments, each window of the entire amplitude spectrum has a determined window threshold. Generally speaking, to maximize detection reliability, corresponding window thresholds can be determined for all windows that can be reliably used to evaluate the symmetric / asymmetric characteristics of the amplitude spectrum.

[0068] For each of the plurality of windows in the first (negative) portion 200-i (e.g., b1 to b7), each corresponding window threshold (e.g., t1 to t7) is based on the amplitude of the spectrum 200 within one or more windows in the second (positive) portion 200-ii. Furthermore, for each of the plurality of windows in the second (positive) portion 200-ii (e.g., b9 to b15), each corresponding window threshold (e.g., t9 to t15) is based on the amplitude of the spectrum 200 within one or more windows in the first (negative) portion 200-i. The corresponding window thresholds (e.g., t1 to t7 and t9 to t15) are depicted as thick black lines above the rectangular boxes (the rectangular boxes represent the amplitudes within the corresponding windows), designated as t1 to t7 for windows 1 to 7 (window thresholds), and designated as t9 to t5 for windows 9 to 15 (window thresholds).

[0069] In some embodiments, each window used for processing has a corresponding window (counterpart bin) in the opposite portion, which is symmetrically positioned with respect to the center frequency 230. In addition, the number of frequency windows to be used in the processing of the negative portion 200-i and the positive portion 200-ii of the center frequency 230 can be equal. As shown, the seven window thresholds (t1 to t7) of the seven frequency windows (b1 to b7) are located in the negative portion 200-i, while the other seven window thresholds (t9 to t15) of the other seven frequency windows (b9 to b15) are located in the positive portion 200-ii. The eighth window (referred to as window 8 or b8, respectively) includes the center frequency 230 and is not part of the negative portion 200-i or the positive portion 200-ii. Therefore, it has no window threshold. In addition, the sixteenth window (window 16 or b16) has no corresponding window (symmetrically positioned with respect to the center frequency 230) and no window threshold. The amplitude within window 16 can also be ignored because it may correspond to the maximum speed at which the direction of motion cannot be distinguished compared to a lower speed.

[0070] exist Figure 3In the example of , fourteen of the sixteen windows have corresponding windows that are symmetrically positioned relative to the center frequency 230. More specifically, window 1 corresponds to window 15, window 2 corresponds to window 14, window 3 corresponds to window 13, window 4 corresponds to window 12, window 5 corresponds to window 11, window 6 corresponds to window 10, and window 7 corresponds to window 9, and this also applies to each of the examples listed. In some embodiments, each window of the entire bandwidth 220 has a corresponding window, while in other embodiments, one or more windows do not have a corresponding window. The determination of each window threshold can be based on the amplitude value of the amplitude spectrum within the symmetrically positioned windows (i.e., within its corresponding window).

[0071] Various embodiments may include determining each window threshold based exclusively on the corresponding window or based on one or more other frequency windows in addition to the corresponding window. Alternatively, each window threshold may be determined using a group of other frequency windows in a relative portion that does not include the corresponding window. Processing circuitry 102 may also be configured to detect motion of target 170 based on the amplitude of spectrum 200 exceeding the window threshold in at least one window within bandwidth 220.

[0072] Each window threshold value of the negative portion 200-i can be determined by multiplying a value determined using the amplitude of the spectrum 200 within one or more windows of the positive portion 200-ii by a predefined value (factor). In addition, each window threshold value of the positive portion 200-ii can be determined by multiplying a value determined using the amplitude of the spectrum within one or more windows of the negative portion 200-i by a predefined value (factor).

[0073] The predefined value can be selected based on the desired detection sensitivity. For example, a standard predefined value can be selected to correspond to a standard detection sensitivity that may not capture very subtle movements of the target 170, but may capture conventional motion or movement. Furthermore, if it is desired to detect very subtle movements of the target 170, the predefined value can be reduced compared to the standard value. This will provide a lower window threshold, which may result in a lower amplitude value for the window exceeding the corresponding window threshold. If it is desired to detect only significant movements that are more substantial than conventional movements, the predefined value can be increased from the standard value. This will provide a larger window threshold, which may result in a larger window amplitude value being required to exceed the window threshold. The predefined value can be adjusted, such as by user input or an automatic mechanism, to adjust the sensitivity of the detection.

[0074] Furthermore, a plurality of predefined values ​​(factors) may be used depending on the position of the window relative to the center frequency 230. For example, the predefined value may be higher or lower for window thresholds corresponding to windows closer to the center frequency 230 than for windows farther from the center frequency 230, among other possibilities. This may adjust the detection sensitivity of a pre-specified frequency range by different amounts, which may be customized depending on the type of object 170 to be detected or the type of motion of the object 170.

[0075] Detection of target 170 motion is performed in response to the amplitude exceeding a window threshold in at least one window within bandwidth 220. If the window threshold is not exceeded, a new amplitude spectrum can be generated, corresponding to the DFT of time domain data for the next time frame of received signal 130. The corresponding window threshold for the same frequency window can be re-determined based on the new amplitude spectrum. Target motion can then be detected if the amplitude within a window in the new amplitude spectrum exceeds the corresponding window threshold. This process can be repeated as long as device 100 acquires time domain data for new time frames of received signals.

[0076] In a specific example, the window thresholds of corresponding windows can be based only on the corresponding window. In this case, the window threshold of window 1 is determined based only on the amplitude value of window 15, and vice versa. The same applies to windows 2 and 14, windows 3 and 13, windows 4 and 12, windows 5 and 11, windows 6 and 10, and windows 7 and 9. The window threshold of a window can be determined by multiplying the amplitude specified in its corresponding window by a predefined value (factor). Figure 4 and Figure 5 Illustrative examples of such embodiments are provided in .

[0077] Figure 4 Another symmetrical amplitude spectrum 400 is depicted, in which the amplitudes of windows 3 and 13 are highlighted in gray and shown only with the window 3 threshold (t3) and the window 13 threshold (t13). The window 3 threshold (t3) is based on the amplitude within its corresponding window (window 13), while the window 13 threshold (t13) is based on the amplitude within its corresponding window (window 3). Since the corresponding amplitude values ​​of windows 3 and 13 in the depicted spectrum 400 are equal (i.e., the amplitudes are approximately equal within both windows 3 and 13, with no significant asymmetry), the window 3 threshold (t3) and the window 13 threshold (t13) are also (approximately) equal.

[0078] The above-mentioned predefined value (factor) can be, for example, 1.1. In this example, the threshold value of each window can be equivalent to 10% greater than the amplitude value of the corresponding window. If the amplitude value of window 15 is 2.0, the window 3 threshold value (t3) can be 2.2. In this example, considering the symmetry of the amplitude spectrum 400 relative to the frequency center 230, the amplitude value of window 3 can also be 2.0, and then the window 13 threshold value (t13) can also be determined to be 2.2. Examples of corresponding windows 3 and 13 are provided herein for illustrative purposes. The predefined values ​​can also be applied to other corresponding window pairs, in Figure 4 In , each pair of windows also has equal amplitude values. Therefore, Figure 4 Symmetry in the amplitude values ​​can lead to symmetry in the thresholds, e.g. Figure 3 Each pair of corresponding windows is shown in .

[0079] Since for each window, the amplitude in both the corresponding window and its corresponding window is the same, this results in the amplitude in each window not exceeding its corresponding window threshold. Therefore, in the case of a symmetric (ie, sufficiently symmetric) amplitude spectrum, no target motion is detected.

[0080] Figure 5 Another exemplary magnitude spectrum 500 is depicted. Compared to the previous spectra 200, 300, 400, Figure 5 The amplitude spectrum 500 of is clearly asymmetric, with the amplitude changing only within window 13 (highlighted in grey). Figure 2 、 Figure 3 and Figure 4 Due to the change in the amplitude value of window 13 in the image, the threshold value (t3) of window 3 also changes. On the other hand, since the amplitude within window 3 does not change, the threshold value (t13) of window 13 also does not change. The amplitude values ​​and window thresholds of the remaining windows also remain unchanged. As shown in the figure, the amplitude value of window 13 (now including a larger value (e.g., 2.4)) is sufficient to exceed the unchanged threshold value (2.2) of window 13.

[0081] For the case where the corresponding window thresholds are based solely on the corresponding windows, the larger amplitude value of window 13 may cause the value of the window 3 threshold to increase. Continuing with the previous example of multiplying the predefined value by 1.1, multiplying by the amplitude value of window 13 of 2.4 results in a new window 3 threshold (t3) of 2.64. Although the unchanged amplitude value of window 3 of 2.0 is much lower than 2.64, the new amplitude value of window 13 of 2.4 exceeding the unchanged window 13 threshold (t13) of 2.2 may be sufficient to detect the motion of target 170, and for such embodiments, only one amplitude value needs to exceed its corresponding window threshold. In other embodiments, the amplitude may need to exceed the window threshold in two or more corresponding windows for detection, which can further reduce false positive detections. Figure 5In the case of spectrum 500, the increased amplitude within window 13 can be associated with motion of a human or another similar moving object, which corresponds to a Doppler shift in the frequency of window 13. On the positive side of spectrum 500 relative to center frequency 230, the detected motion can correspond to a human moving or making motion toward the radar sensor.

[0082] Although Figure 4 and Figure 5 In the example, each window threshold is determined based only on the amplitude value of the corresponding window, but Figure 6 、 Figure 7A and Figure 7B The example presents an embodiment of determining each window threshold using respective amplitude values ​​of a plurality of windows including a corresponding window.

[0083] Figure 6 An amplitude spectrum 600 is depicted which is also symmetrical. Figure 4 and Figure 5 The window 3 threshold (t3) is based only on its corresponding window 13 compared to Figure 6 The window 3 threshold (t3) in is based on a plurality of corresponding amplitude values ​​corresponding to a plurality of other frequency bins (including the corresponding window) in the relative portion. The following content regarding the window 3 threshold (t3) is provided as an example, which can be applied to each window threshold, such as Figure 3 In general, each window threshold in a portion can be based on the respective amplitude values ​​of a corresponding subset of windows in the opposite portion (e.g., a subset of windows that uniquely corresponds to the window threshold), which subset can include the corresponding window symmetrically positioned with respect to the window for which the window threshold is being determined, and / or one or more windows that are continuously adjacent to the corresponding window, as described below.

[0084] Instead of determining the window threshold value (t3) based solely on the corresponding window (window 13), the amplitude values ​​of other windows (window 12 and window 14) adjacent to the left and / or right of window 13 (directly adjacent) may also be used to determine the window threshold value of window 3, such as by averaging. In another example, multiple windows that are continuously adjacent to the corresponding window (window 13) may also have amplitude values ​​that are used to determine the window threshold value of the corresponding window of window 13 (i.e., the window threshold value t3 of window b3). "Continuously adjacent" herein refers to a window adjacent to the corresponding window, a window adjacent to another window adjacent to the corresponding window, or a window adjacent to any window included in the window group that includes the corresponding window, without any gaps or unincluded windows in between.

[0085] For example, windows 12 and 14 (directly adjacent to window 13) or windows 11 and 15 (directly adjacent to windows 12 and 14) can be included in a group of windows that are consecutively adjacent to window 13. The depicted subset of windows b11 to b15 (e.g., five consecutively adjacent windows including the corresponding window) can form a (unique) corresponding window subset for determining window threshold t3 for window b3. Other examples of window thresholds that follow the same scheme can be a window threshold t4 (uniquely) corresponding to a subset of windows b10 to b14 and a window threshold t5 (uniquely) corresponding to a subset of windows b9 to b13.

[0086] Other consecutive adjacent windows may also be included if adjacent to them. Continuing with the example of threshold t3 and the subset of windows b11 through b15, windows 9 and 10 may also be included in the group of windows that are consecutively adjacent to window 13 if windows 11 and 12 are also included. In some embodiments, any consecutive group of any number of frequency windows that includes a corresponding window (e.g., window 13) within the negative portion 200-i or the positive portion 200-ii may be used to determine the window threshold (e.g., t3). In some embodiments, the threshold may be determined based on additional criteria (e.g., inaccuracy, exceeding Figure 9A In some embodiments, the corresponding window may be excluded and the window threshold may be determined using the group of windows that are consecutively adjacent to the corresponding window. Combinations of excluding windows from the group of windows that are consecutively adjacent to the corresponding window are also possible for various reasons.

[0087] Consecutive adjacent windows (e.g. Figure 6 The corresponding amplitude values ​​of windows 11 to 15 in FIG. 1 (shown in FIG. 1 ) can be used to determine a window threshold (e.g., t3) by various computational techniques. One example is an averaging process, such as an average or a weighted average. For a weighted average, each amplitude value can be assigned a corresponding weight proportional to its relative importance within the resulting average. For example, a larger weight can be assigned to the corresponding window (window 13) than to consecutive adjacent windows. Optionally, different weights can also be assigned to various consecutive adjacent windows. In another example, a root mean square averaging method can be used, such as the equation described below. The variable σ can represent the average value calculated using N consecutive adjacent windows, i is the index of the corresponding window, and x is the index of the corresponding window. i is the amplitude value of the corresponding window. Once the average result is obtained, it can be multiplied by a predefined value, which can be proportional to the selected detection sensitivity, as mentioned before.

[0088]

[0089] For a larger number of windows, a more detailed computational technique for determining the window threshold (t3) may be preferred. For example, the window threshold may be determined assuming that the corresponding amplitude values ​​follow a Rayleigh distribution. The time domain data may be affected by normally distributed Gaussian white noise, resulting in the amplitude values ​​associated with the corresponding windows being Rayleigh distributed.

[0090] Each window threshold value can also be determined using the maximum likelihood estimation of the corresponding amplitude values ​​of the multiple windows (windows 11 to 15) used to determine the window threshold value (t3), and the assumption of the Rayleigh distribution can be used. The Rayleigh distribution can be defined by a scale parameter σ, which can be optimized in the maximum likelihood estimation. A probability density function PDF can be provided for each amplitude value as described below, where x can represent the amplitude value and σ is the scale parameter to be estimated. This formula can represent the probability of observing the amplitude value given the scale parameter:

[0091]

[0092] For example, for the Rayleigh distribution, Can be each amplitude value x i The Rayleigh probability density function of σ (e.g., the five amplitude values ​​in the window 11 to 15) can be constructed. In addition, a likelihood function L can be constructed that represents the probability of observing the corresponding amplitude value given a specific parameter value σ. The likelihood function can be expressed as the product of the PDFs evaluated for each amplitude value, assuming that these values ​​are independent and identically distributed.

[0093] L(σ;x1,x2,x3,x4,x5)=f(x1;σ)*f(x2;σ)*f(x3;σ)*f(x4;σ)*f(x5;σ)

[0094] The maximum likelihood estimation can also include taking the natural logarithm of the likelihood function ln(L) and determining the parameters that maximize the log likelihood function. For example, this can be achieved by setting the derivative of the log likelihood function with respect to σ to zero and determining the value of σ. This can be achieved by analytical calculation or numerical optimization techniques. The maximum likelihood estimation can determine the parameter value σ that maximizes the likelihood of observing the amplitude value under the assumed Rayleigh distribution (i.e., the best fit amplitude value). Although the example provided depicts one parameter to be adjusted, other examples can provide multiple parameters to be adjusted, which can provide more accurate and / or more precise estimates.

[0095] Once the value of parameter σ is obtained, the corresponding distribution can be applied to determine the window threshold (e.g., t3). For example, this can be achieved by obtaining a new value of the amplitude value within the corresponding window (e.g., window 13) and adjusting the amplitude value to the new value provided by the maximum likelihood estimation. The adjusted value can then be multiplied by a predefined value that can be consistent with the desired detection sensitivity of device 100, as described above. Alternatively, among other possibilities, the new corresponding amplitude values ​​obtained by the maximum likelihood estimation can be averaged.

[0096] Figure 7A and Figure 7B Another symmetrical magnitude spectrum 700A, 700B is provided, respectively. The magnitude spectrum 700A is depicted with a binary 2 threshold (t2), while the magnitude spectrum 700B is depicted with a binary 1 threshold (t1). Figure 7A and Figure 7B For illustration, the corresponding subset of windows used for averaging to determine the corresponding window threshold value may be within a predefined frequency range (or a window range having a predefined number of windows) centered about the symmetrically positioned window and within bandwidth 220. Furthermore, if any frequency bin does not meet each of the above conditions, processing circuitry 102 may be configured to not apply its amplitude value to determine the window threshold value.

[0097] These examples are provided for Figure 6 In contrast to the amplitude spectrum of 600, Figure 6 The amplitude spectrum 600 of has a window threshold determined based on the other five frequency windows. In other cases, for the same predefined frequency range (e.g., Figure 5 The number of windows used to determine the window threshold can be limited by the combination of the predefined frequency window centered on the corresponding window and the bandwidth 220. The same predefined frequency range (5 windows) centered on the corresponding window is applied to Figure 6 For amplitude spectra of the frequency spectrum of the frequency domain, different numbers of windows (e.g., 4 windows and 3 windows, respectively) and therefore different amplitude values ​​may be used in the averaging and / or estimation process. Since the number of frequency bins having greater or lesser frequencies than the corresponding windows used to determine the window threshold may be different, the above-mentioned (averaging / estimation) calculation techniques may be adjusted to obtain appropriate values ​​(e.g., adjusting weights, etc.).

[0098] Figure 6 The window 3 threshold (t3) shown is based on the corresponding window (13), two consecutive adjacent low frequency windows (11 and 12), and two consecutive adjacent high frequency windows (14 and 15), all of which are within the bandwidth 220. However, the predefined range of the five windows may not always fit perfectly within the bandwidth 220. For example, to determine Figure 7AWith the window 2 threshold (t2) in [ 2 ], the same range of five windows can be centered around window 14. Although two consecutively adjacent windows with lower frequencies (windows 12 and 13) are within bandwidth 220, only one consecutively adjacent window with higher frequency (window 15) is within bandwidth 200 and has a corresponding window (located symmetrically with respect to center frequency 230). Figure 6 The amplitude values ​​of the five windows used to determine the window 3 threshold are different, and only the four windows including the corresponding window will be used to determine the window 2 threshold (t2).

[0099] against Figure 7B Continuing with the above example, and determining the window 1 threshold (t1), for the window 1 threshold (t1), although the two consecutive adjacent windows (i.e., windows 13 and 14) of the lower frequency window 15 are within the bandwidth 220, this is not the case for any consecutive adjacent windows of higher frequency (e.g., the assumed amplitude values ​​of windows 16 and 17, not shown). Therefore, when applying the same predefined range of five windows centered around the corresponding window, only three windows will be used to determine the window 1 threshold (t1), rather than the four windows as shown in FIG. Figure 6 The amplitude values ​​of five windows are averaged and Figure 7A As shown, four windows are used for averaging. As described above, using the same predefined frequency range for window selection, other window thresholds that may not be based on five amplitude values ​​include windows 6, 10, 14 (each window threshold will be based on four amplitude values) and windows 7, 9 and 15 (each window threshold will be based on three amplitude values).

[0100] Figure 6 、 Figure 7A and Figure 7B The frequency window selection mechanism for determining the corresponding window threshold provided in FIG. 1 is provided as an example of how a selected window can be within a predefined frequency range and bandwidth 220 centered around a symmetrically positioned window, which can be applied in various forms. For example, the predefined frequency range can be any number of frequency windows and can correspond to any upper and lower frequency limits. Such upper and lower limits can also be asymmetric. In other words, the predefined frequency range does not need to be centered around the corresponding window as long as it includes the corresponding window.

[0101] Furthermore, in some embodiments, such a predefined frequency range for selecting a window for determining a window threshold can vary depending on the window threshold being determined. For example, windows in certain portions of the spectrum (e.g., windows closer to or further from the edge of bandwidth 220) can have a smaller or larger predefined frequency range for averaging. Other related customizations or adjustments not mentioned herein are also possible, depending on the characteristics of a particular target or the optimal processing technique.

[0102] In addition to accurately detecting such target 170 motion, it is also desirable to limit false detections. Figure 8 、 Figure 9A and Figure 9B Examples related thereto are provided in more detail.

[0103] Figure 8 Another exemplary symmetric magnitude spectrum 800 is depicted. Figure 8 In this case, the windows closest to the center frequency 230 are highlighted in gray and marked as windows associated with low Doppler velocities. Windows with low Doppler velocities (i.e., windows closer to the center frequency 230) are generally likely to be affected by interfering objects within the field of view of the radar sensor, while they are less likely to be affected by target motion. Interfering objects including air conditioning units, fans, blinds, bushes, and trees, among other examples, may appear in the background within the field of view of the radar sensor 140 and may affect the amplitude spectrum. Although the amplitude spectrum changes caused by such objects are generally symmetrical and therefore generally irrelevant to detection, asymmetric changes from such objects may still occur. Therefore, if windows with low Doppler velocities are not included in the window threshold calculation, false detections based on interfering objects can be more effectively prevented.

[0104] In many cases, instances of target 170 motion may generally correspond to windows outside of low Doppler velocities (i.e., windows further from center frequency 230). Thus, windows associated with lower Doppler velocities may be excluded from the window threshold calculation while sacrificing little detection accuracy. In some embodiments of apparatus 100, one or more windows within a predefined velocity threshold frequency range that includes center frequency 230 may be excluded from determining the corresponding window threshold.

[0105] The predefined velocity threshold frequency range can be defined based on the Doppler velocity threshold. For example, the Doppler velocity threshold can be pre-specified as ±0.1 m / s. In this case, the frequency shift corresponding to a positive or negative Doppler velocity of an absolute value of 0.1 m / s can be determined based on various settings or parameters of the radar system 150. A frequency window corresponding to frequencies equal to or lower than the frequency shift can then be selected and excluded from determining the window threshold. For noisier or interfered environments, a higher Doppler velocity threshold, such as ±0.3 m / s, may be appropriate. The Doppler velocity threshold can also be adapted based on the use case, such as through user input or automated mechanisms associated with other sensing components.

[0106] Figure 8An illustrative example is provided that can be extended to any velocity threshold frequency range, including the center frequency 230, and including any number of frequency bins within the bandwidth 220 to be excluded from determining the window threshold. The velocity threshold frequency range can be based on a Doppler velocity threshold that is adjustable. As examples of such multiple windows, windows 5, 6, and 7 in the negative portion and windows 9, 10, and 11 in the positive portion are highlighted in gray, each corresponding to a frequency below the Doppler velocity threshold. Figure 8 , windows 5 to 7 and windows 9 to 11 of magnitude spectrum 800 can be excluded from determining the corresponding window thresholds, while windows 1 to 4 and windows 12 to 15 can have their corresponding window thresholds determined, as shown. In this example, if any particular corresponding amplitude value of windows 1 to 4 or windows 12 to 15 exceeds its corresponding window threshold, target motion can be detected.

[0107] A target may also be within the field of view of radar sensor 140 while exhibiting only minimal motion. For a human target, slight, sporadic movements may occur while sitting or standing. For example, while the majority of the body remains stationary, a hand or finger may move slightly, such as when lightly grasping another body part or using a smartphone. In such cases, even if a window threshold is not determined for a window closer to center frequency 230, further processing may be performed to detect such movement.

[0108] In some embodiments, processing circuitry 102 may be configured to determine an average amplitude based on corresponding amplitude values ​​of lower Doppler velocity windows (e.g., windows within the velocity threshold frequency range) for comparison with a corresponding average amplitude threshold, which may be based on other higher Doppler velocity windows (e.g., remaining windows outside the velocity threshold frequency range in bandwidth 220). For example, in Figure 8 In the case of spectrum 800, the corresponding amplitude values ​​of windows 5 to 7 and windows 9 to 11 can be used to determine the average amplitude, while the corresponding amplitude values ​​of windows 1 to 4 and windows 12 to 15 can be used to determine the average amplitude threshold. Both the average amplitude and the average amplitude threshold can be calculated using various averaging or estimation techniques, such as those described above. The result of averaging or estimating using a higher Doppler frequency window (e.g., outside the velocity threshold frequency range) can be multiplied by a predefined value (factor) to obtain the average amplitude threshold, thereby providing an appropriate average amplitude comparison for detecting small movements of the target.

[0109] Furthermore, processing circuitry 102 may be configured to detect target motion based on whether the average amplitude exceeds an average amplitude threshold. As previously described, this detection mechanism may be used in addition to determining whether the amplitude values ​​of a window exceed its corresponding window threshold. Furthermore, the range (number) of windows used to determine the average amplitude threshold and the average amplitude may be adapted based on the desired sensitivity for detecting fine motion of target 170.

[0110] Figure 9A An exemplary asymmetric spectrum 900A is depicted, specifically, the only difference compared to the previous symmetric spectrum is the localized spike in amplitude within window 4. While the previous figures have illustrated configurations that improve the accuracy of valid data detection, it is possible that certain portions of data may be determined to be invalid, such as when the amplitude spectrum includes a large localized spike within a window. More specifically, if the amplitude value of a window is significantly greater than that of other windows within the window's predefined frequency range, this is unlikely to be caused by motion of target 170 within radar sensor 140's field of view, and therefore, correction processing may be required.

[0111] In general, a local peak (such as the amplitude value of window 4) may correspond to an amplitude value that is much higher than all other amplitude values ​​of any nearby frequency windows. Figure 9A The description, while including only 16 frequency bins, is intended to provide examples of magnitude spectra with an arbitrary number of frequency bins, where large local spikes and which frequency bins are considered nearby can be defined based on various properties of the magnitude spectrum.

[0112] Processing circuitry 102 can be configured to determine a peak threshold for each window or windows within bandwidth 220 (e.g., st4 for window 4). In some cases, the peak threshold may be determined only for windows with a window threshold. The peak threshold for a corresponding window may be based on amplitude values ​​associated with a group of multiple consecutively adjacent windows (as described above) within a predefined frequency range, which also includes the corresponding window (e.g., the surrounding windows of window 4, as shown). Therefore, the predefined frequency range used to determine the peak threshold will be on the same side of center frequency 230 as the corresponding window. In the case of spectrum 900A, window 4 is represented by window 4 peak threshold (st4). For example, processing circuitry 102 can be configured to detect target motion if the amplitude value of window 4 is above window 4 threshold (t4) but below window 4 peak threshold (st4). This can be similarly applied to all windows within bandwidth 220 with a determined window threshold. However, in amplitude spectrum 900A, the amplitude value of window 4 exceeds the window 4 peak threshold.

[0113] In the event that the amplitude value of a window (e.g., b4) is greater than its corresponding peak threshold (e.g., st4), the processing circuit system 102 may also be configured to change the amplitude value (i.e., change the amplitude of the spectrum within the corresponding window). For example, if the window peak threshold is exceeded, the amplitude within the window may be changed to be equal to the average of the amplitude values ​​associated with multiple consecutive adjacent windows. Figure 9A In this case, the new value for the amplitude can be determined by averaging the corresponding amplitude values ​​associated with windows 3 and 5, windows 2, 3, 5, and 6, or windows 1, 2, 3, 5, 6, and 7. The averaged result can then replace the previous (peak) amplitude value for window 4.

[0114] In general, the value can be calculated using the corresponding amplitude values ​​associated with any window group within the predefined frequency range of the window including the local peak. The calculated value can be obtained by averaging and / or using other forms of calculation, such as median amplitude values ​​or maximum likelihood estimates, and other possible values, which can replace the previous (peak) amplitude value. In other embodiments, such peak amplitude values ​​can be ignored.

[0115] Figure 9B An exemplary spectrum 900B is depicted, whose amplitude is corrected at Figure 9A The window 4 corresponding to the amplitude value that previously exceeded its corresponding spike threshold (st4) is shown as having a corrected amplitude, which can be similar to Figure 2 、 Figure 3 、 Figure 4 、 Figure 6 、 Figure 7A 、 Figure 7B and Figure 8 The new amplitude value of window 4 can then be used to determine the window threshold value (t12) of its corresponding window b12. In general, processing circuit system 102 can be configured to perform a spike threshold check on all frequency bins, adjust any associated amplitude values ​​as needed to generate a corrected amplitude spectrum, determine a corresponding window threshold value for each frequency bin based on the corrected amplitude spectrum, and detect target motion if the corrected amplitude within any frequency bin exceeds its corresponding window threshold value.

[0116] During operation of radar system 150 , the determination of the magnitude spectrum and corresponding threshold may be repeated over time in subsequent time frames of received signal 130 . Figure 10A and Figure 10B Depicted are spectra 1000A, 1000X corresponding to respective time frames 1050 - a , 1050 - x of the received signal 130 , and respective window thresholds for each time frame ( t3 - a ; t3 - x ). Figure 10A The amplitude spectrum of 1000A and Figure 10B 10. The amplitude spectrum 1000X of FIG. 10 is different in amplitude within windows 11, 12, and 13. As shown in the figure, first amplitude spectrum 1000A is obtained from the DFT of a first set of time domain data measured at a first time frame 1050-a of received signal 130. Second amplitude spectrum 1000X is obtained from the DFT of another set (e.g., a second set) of time domain data measured at another time frame 1050-x of received signal 130. Second amplitude spectrum 1000X can represent any subsequent amplitude spectrum corresponding to any subsequent time frame 1050-x within a predetermined time span. The predetermined time span can be a measurement time span in which a round of measurements is performed to determine whether the motion of target 170 can be specifically detected within the time span (e.g., 10 seconds).

[0117] These two amplitude spectra are provided to illustrate that each of the window thresholds (e.g., windows 1 to 7 and windows 9 to 15) is adjustable over time (i.e., can be updated) as different portions of the time domain data within corresponding time frames of the received signal 130 are processed. An illustrative example using window 3 is provided. Figure 10A The first window 3 threshold (t3-a) is shown in Figure 10B , a subsequent window 3 threshold (t3-x) is shown in FIG. Furthermore, in both amplitude spectra 1000A and 1000X, five windows on opposite sides of the center frequency 230 are selected, including corresponding window 13 and four consecutively adjacent windows 11, 12, 14, and 15, for determining the window 3 threshold. As previously described, the window 3 threshold can be determined based on an averaging and / or estimation technique. The window selection and averaging and / or estimation technique used to determine the window 3 threshold can then be maintained constant through multiple processing iterations, including processing multiple portions of the time domain data corresponding to the corresponding time frames (e.g., 1050-a; 1050-x).

[0118] There is a significant difference between the amplitude values ​​(height of the rectangular box) of three of the five highlighted windows (windows 11, 12, and 13) between the first amplitude spectrum 1000A and the second amplitude spectrum 1000X. Compared with the amplitude values ​​of the first amplitude spectrum 1000A, the amplitude values ​​of windows 11, 12, and 13 in the second amplitude spectrum 1000X are significantly larger. This may result in different values ​​of the window 3 threshold of the corresponding spectra. In the first amplitude spectrum 1000A, the amplitude values ​​of the corresponding window 13 and the consecutive adjacent windows 11 and 12 are relatively small, resulting in a smaller value of the first window 3 threshold (t3-a). Figure 10B compared to, Figure 10AThere is a large gap between the first amplitude within window 3 and the first window 3 threshold (t3-a). On the other hand, in the second amplitude spectrum 1000X, the amplitude values ​​corresponding to window 13 and the consecutively adjacent windows 11 and 12 are relatively large, resulting in a larger value for the subsequent window 3 threshold (t3-x). This is depicted as a large gap between the second amplitude within window 3 and the subsequent window 3 threshold (t3-x). Windows 14 and 15 are shown as having unchanged values ​​between the two spectra 1000A, 1000X; and therefore, do not affect the change in the window 3 threshold in this example.

[0119] Processing circuitry 102 may be configured to detect motion of target 170 in response to a first amplitude within at least one window (e.g., window 3) of bandwidth 220 exceeding a first corresponding window threshold (e.g., t3-a), or in response to another amplitude within at least one window (e.g., window 3) of bandwidth 230 exceeding a subsequent corresponding window threshold (e.g., t3-x). An example of a window 3 threshold varying between corresponding amplitude spectra of two different portions (i.e., two different time frames) of the time domain data of received signal 130 is provided as an example of a window threshold applied to all window thresholds having corresponding windows that are not excluded, such as Figure 2 The window thresholds t1 to t7 and t9 to t15 shown, or Figure 8 The window thresholds in are t1 to t4 and t12 to t15.

[0120] In some embodiments, rather than requiring only one amplitude value exceeding its corresponding window threshold to detect target motion, this may be necessary only for a subset of the time domain data, where the amplitude within a window of only one amplitude spectrum among the multiple generated and analyzed spectra exceeds the corresponding window threshold. Alternatively, in order to detect target motion to be triggered, the amplitude within the windows of multiple amplitude spectra (i.e., multiple time frames) may need to exceed their corresponding window thresholds to ensure higher reliability of target detection. Other combinations are also possible, such as requiring the amplitude within two or more windows to exceed the corresponding window threshold for two or more time frames within a certain number of processed time frames, and so on.

[0121] In other words, processing circuitry 102 may be configured to detect motion of target 170 by applying a sliding window to multiple (i.e., two or more) time frames (e.g., 1050-a; 1050-x) of received signal 130. A sliding window may refer to a number of time frames corresponding to the length of an observation time span (i.e., an observation window) that are evaluated for detecting motion of target 170. For example, a sliding window may be a mechanism by which apparatus 100 may be configured to store multiple time frames (e.g., three frames, or other possibilities) in a memory and perform detection processing, as described herein, on each of the (e.g., three) time frames (e.g., 1050-a; 1050-x). The time frames used for processing and detection may be consecutive time frames, including a first time frame (e.g., 1050-a) and one or more immediately subsequent time frames (e.g., 1050-x), without any intervening time frames that are not used for processing and detection (i.e., X frames in a row).

[0122] Alternatively, the time frames 1050-a, 1050-x used for processing and detection can be non-consecutive time frames. For example, a window threshold may be exceeded in a first time frame (e.g., 1050-a), one or more time frames may be processed (analyzed) without exceeding the window threshold, and then the window threshold may be exceeded in a subsequent time frame (e.g., 1050-x). The detection can be based on two instances of exceeding the window threshold, particularly within two separate time frames of a pre-specified number of processed (analyzed) time frames, which can correspond to the above-mentioned observation time span. The pre-specified number of time frames can be adjusted based on the desired detection sensitivity.

[0123] In addition, according to the expected detection sensitivity, the number of required instances exceeding the window threshold in the corresponding time frame in the time frame group can also be increased or decreased. Lower detection sensitivity can correspond to a larger number of required such instances, and vice versa. In order to carry out more precise adjustment, the number of required instances exceeding the window threshold in the time frame group and the number of pre-specified processed (analyzed) time frames (that is, requiring to exceed the window threshold in the X of the last Y frame, and adjusting X and / or Y) can be changed. For example, by applying a sliding window to detect the motion of target 170, further options can be provided for improving the reliability and stability of detection. Therefore, device 100 can also avoid false motion or false interference signal detection, or detection caused by statistical abnormal values, and these abnormal values ​​can be adjusted for each use case.

[0124] A radar system 150 employing one of the embodiments of the apparatus 100 described herein can adapt to such environments or fields of view with such objects by using adaptive thresholds that exploit the symmetric / asymmetric nature of the amplitude spectrum. As previously described, the apparatus 100 provides multiple adaptive thresholds. Given its adaptive nature, the apparatus 100 can be used by the radar system 150 in various environmental conditions and with various interfering or interfering objects within the field of view of the radar sensor 140. For example, the presence of interfering objects, such as vibrating objects or objects without a well-defined surface (e.g., a rotating fan, shrubs, etc.), can generally result in a symmetrical change in the amplitude spectrum compared to an undisturbed spectrum. This symmetrical change can correspond to a Doppler shift in both positive and negative directions. For example, this can be caused by the vibration of the object, causing it to move toward and away from the radar sensor. Positive and negative Doppler shifts can also be caused by a cluttered sensing environment, such as multiple scattering points within a confined area, or multiple parts of an object vibrating in different directions. Furthermore, a generally noisy environment (such as rain or snow) can also result in a symmetrical change in the amplitude spectrum compared to an otherwise undisturbed environment.

[0125] For example, when radar system 150 is used in a rainy environment, each window threshold can be automatically determined to be higher based on the increased noise level. If the amplitude within each window threshold of bandwidth 220 increases, all corresponding windows of the corresponding window (and, if applicable, windows continuously adjacent thereto) will have increased amplitude values. Therefore, all window thresholds will also increase and adapt to the overall increased amplitude. Therefore, no manual adjustment is required. In the absence of rainfall, for less noisy environments, the amplitude will also be reduced. In addition, even in very noisy or interfered environments in which radar system 150 is used, detection of target 170 motion can still be based on sufficient asymmetry in the amplitude spectrum.

[0126] Thus, the radar system 150 of an embodiment of the application device 100 can be considered to utilize dynamic DFT thresholds to adapt to various environments and interfere with objects within the field of view of the radar sensor 140 in a manner not possible in other radar systems. Radar systems that use one or more fixed thresholds cannot provide such automatic adjustment. In addition, other adjustable threshold algorithms (such as CFAR algorithms) do not utilize the symmetric / asymmetric properties of the spectrum (e.g., amplitude spectrum) described herein, and therefore their detection capabilities are limited. On the other hand, the radar system 150 including the device 100 described herein also provides various options for more sophisticated detection forms, such as through various averaging and estimation techniques (e.g., maximum likelihood estimation). Such options can provide more effective detection of the motion of pre-specified targets (including human targets).

[0127] In general, the embodiments of the apparatus 100 provided herein can provide the radar system 150 with more accurate detection of target motion and can detect finer motion while reducing its power consumption. If each detection triggers an alarm mechanism and results in power consumption, power consumption can be reduced by further limiting the number of false detections. The radar system 150 can also be used for more complex applications, such as using multiple radar sensors in closer proximity (e.g., a single room) because interference caused by another radar sensor can be limited. Thus, a variety of advantages are provided, including finer detection, reduction in false detections, and expansion of applications that would otherwise be impossible to achieve or too cumbersome for effective results.

[0128] In combination with the proposed technology or one or more of the above examples, for example, reference Figure 1A and Figure 1B , which explains advantages and further details and aspects of the apparatus 100 and the radar system 150. The apparatus 100 and the radar system 150 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.

[0129] Figure 11 A flowchart illustrating an example (e.g., computer-implemented) method 1100 is shown. Method 1100 may be performed by apparatus 100 as described herein. Method 1100 includes acquiring 1110 the amplitude of a spectrum of a received signal from a radar sensor. The spectrum includes a first portion and a second portion within a frequency bandwidth divided into a window. The first portion and the second portion are symmetrically positioned relative to a center frequency.

[0130] Method 1100 further includes determining 1120A a window threshold for at least one window in the first portion based on the magnitude of the frequency spectrum within one or more windows in the second portion. Method 1100 further includes determining 1120B a window threshold for at least one window in the second portion based on the magnitude of the frequency spectrum within one or more windows in the first portion. Furthermore, method 1100 includes detecting 1130 target motion in response to the magnitude of the frequency spectrum in at least one window within the frequency bandwidth exceeding the window threshold.

[0131] In some embodiments, the method 1100 may include determining, for each of the plurality of windows in the first portion, a corresponding window threshold, each window threshold being based on a magnitude of a frequency spectrum within one or more windows in the second portion. In some embodiments, the method 1100 may further include determining, for each of the plurality of windows in the second portion, a corresponding window threshold, each window threshold being based on a magnitude of a frequency spectrum within one or more windows in the first portion.

[0132] Further details and aspects of the method 1100 are explained in conjunction with the proposed technology or one or more examples described above, for example, with reference to Figure 1A and Figure 1B The method 1100 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.

[0133] Some examples of the proposed technique are given below:

[0134] An example (e.g., Example 1) relates to an apparatus for detecting target motion in a field of view of a radar sensor, the apparatus including a processing circuit system configured to: obtain the amplitude of a spectrum of a received signal of the radar sensor, wherein the spectrum includes a first part and a second part within a frequency bandwidth divided into windows, wherein the first part and the second part are symmetrically positioned relative to a center frequency, for at least one window in the first part, determine a window threshold based on the amplitude of the spectrum within one or more windows in the second part, for at least one window in the second part, determine a window threshold based on the amplitude of the spectrum within one or more windows in the first part, and detect the target motion in response to the amplitude of the spectrum in at least one window within the frequency bandwidth exceeding the window threshold.

[0135] Another example (e.g., Example 2) relates to a previous example (e.g., Example 1 or any other example), further comprising: each window threshold of the first part is determined by multiplying a corresponding value determined using the amplitude of the spectrum within one or more windows of the second part by a predefined factor, and wherein each window threshold of the second part is determined by multiplying a corresponding value determined using the amplitude of the spectrum within one or more windows of the first part by the predefined factor.

[0136] Another example (e.g., Example 3) relates to a previous example (e.g., one of Examples 1 or 2 or any other example), further comprising: each window is associated with an amplitude value corresponding to the amplitude of the spectrum within the corresponding window, and wherein each window threshold is based on one or more amplitude values ​​of a corresponding window subset, the window subset including windows symmetrically positioned relative to the center frequency (230) and / or one or more windows continuously adjacent to the symmetrically positioned windows.

[0137] Another example (eg, Example 4) relates to a previous example (eg, Example 3 or any other example), further comprising: the corresponding window subset is within a predefined frequency range centered about the symmetrically positioned window and within the frequency bandwidth.

[0138] Another example (e.g., Example 5) relates to a previous example (e.g., Example 3, Example 4, or any other example), and further includes: each window threshold is determined by: using the maximum likelihood estimate of the Rayleigh distribution to obtain a corresponding calculated value based on the one or more amplitude values ​​of the corresponding window subset, and multiplying the corresponding calculated value by a predefined factor.

[0139] Another example (e.g., Example 6) relates to a previous example (e.g., one or any other example of Examples 3 to 5), further including: the processing circuit system is configured to determine a spike threshold for each of a plurality of windows, wherein the spike threshold of the window is based on a corresponding amplitude value associated with a group of windows within a predefined frequency range that includes the window, and if the amplitude of the spectrum in the window exceeds its spike threshold, a new amplitude value is determined, and the amplitude of the spectrum in the window is changed to the new amplitude value.

[0140] Another example (e.g., Example 7) relates to a previous example (e.g., one or any other example of Examples 1 to 6), further including: the processing circuit system is configured to determine a speed threshold frequency range that includes the center frequency, wherein a lower limit and an upper limit of the speed threshold frequency range are based on a Doppler speed threshold, and wherein each window within the speed threshold frequency range is excluded from determining the corresponding window threshold.

[0141] Another example (e.g., Example 8) relates to a previous example (e.g., one or any other example of Examples 1 to 7), further including: each window is associated with an amplitude value corresponding to the amplitude of the spectrum within the corresponding window, and wherein the processing circuit system is configured to determine an average amplitude of the corresponding amplitude values ​​associated with the one or more windows within the speed threshold frequency range, determine an average amplitude threshold based on the corresponding amplitude values ​​associated with the windows outside the speed threshold frequency range and within the frequency bandwidth, and detect the target motion if the average amplitude exceeds the average amplitude threshold.

[0142] Another example (e.g., Example 9) relates to a previous example (e.g., one or any other example of Examples 1 to 8), further including: the amplitude of the spectrum corresponds to the Fourier transform of the received signal within a first time interval, and wherein each window threshold is a first window threshold based on the received signal within the first time interval, and wherein the processing circuit system is further configured to obtain multiple amplitudes of the spectrum within the frequency bandwidth, each amplitude corresponding to the Fourier transform of the received signal within a corresponding time frame; for each amplitude, updating each window threshold based on the corresponding amplitude, storing each amplitude and each window threshold of the corresponding amplitude in a memory, and detecting the target motion in response to at least two of the amplitudes of the spectrum each exceeding at least one of the window thresholds in the corresponding window within the frequency bandwidth.

[0143] Another example (eg, Example 10) relates to a previous example (eg, one or any other example of Examples 1-9), further including: the frequency bandwidth being defined by a sampling frequency used to generate the received signal.

[0144] Another example (e.g., Example 11) relates to a previous example (e.g., one or any other example of Examples 1 to 10), further including: the radar sensor is a Doppler radar sensor, and wherein each window is associated with a corresponding Doppler velocity of the target measured using the Doppler effect.

[0145] Another example (e.g., Example 12) relates to a previous example (e.g., one or any other example of Examples 1 to 11), further including: the radar sensor is a frequency modulated continuous wave (FMCW) sensor, and wherein the processing circuit system is configured to output a two-dimensional (2D) FMCW range Doppler map based on the detection of the target motion.

[0146] One example (e.g., Example 13) relates to a radar system comprising an apparatus according to a previous example (e.g., any one of Examples 1 to 12) or any other example, and a radar sensor configured to generate the received signal.

[0147] One example (e.g., Example 14) relates to a method for detecting target motion in a field of view of a radar sensor, the method comprising acquiring the amplitude of a spectrum of a received signal of the radar sensor, wherein the spectrum includes a first part and a second part within a frequency bandwidth divided into windows, wherein the first part and the second part are positioned symmetrically with respect to a center frequency, determining a window threshold for at least one window in the first part based on the amplitude of the spectrum within one or more windows in the second part, determining a window threshold for at least one window in the second part based on the amplitude of the spectrum within one or more windows in the first part, and detecting the target motion in response to the amplitude of the spectrum in at least one window within the frequency bandwidth exceeding the window threshold.

[0148] One example (eg, Example 15) relates to a program having a program code for performing the method according to the previous example (eg, Example 14) when the program is executed on a processor or programmable hardware.

[0149] Aspects and features described with respect to a particular example among the foregoing examples may also be combined with one or more other examples to replace the same or similar features of the other examples, or to otherwise introduce these features into another example.

[0150] The example may also be or relate to a (computer) program, which includes a program code that, when executed on a computer, processor, or other programmable hardware component, performs 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. The example may also encompass program storage devices, such as digital data storage media, which are readable by a machine, processor, or computer and encode and / or contain machine-executable, processor-executable, or computer-executable programs and instructions. For example, the program storage device may include or be a digital storage device, a magnetic storage medium such as a disk and tape, a hard drive, or an optically readable digital data storage medium. Other examples may also include a computer, processor, control unit, (field) programmable logic array ((F)PLA), (field) programmable gate array ((F)PGA), graphics processor unit (GPU), application specific integrated circuit (ASIC), integrated circuit (IC), or system on chip (SoC) system that is programmed to perform the steps of the above method.

[0151] It is further understood that the disclosure of several steps, processes, operations, or functions disclosed in the specification or claims should not be interpreted as implying that these operations necessarily depend on the order described, unless explicitly stated in individual cases or necessary for technical reasons. Therefore, the above description does not limit the performance of several steps or functions to a certain order. In addition, 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.

[0152] If aspects have been described in conjunction with an apparatus or system, these aspects should also be understood as descriptions of corresponding methods. For example, a block, component, or functional aspect of an apparatus or system may correspond to a feature of a corresponding method, such as a method step. Thus, aspects described in conjunction with a method should also be understood as descriptions of the corresponding block, component, attribute, or functional feature of the corresponding apparatus or system.

[0153] The following claims are hereby incorporated into the Detailed Description, where each claim can stand on its own as a separate example. It should also be noted that although dependent claims may be referred to in the claims as specific combinations with one or more other claims, other examples may include combinations of dependent claims with the subject matter of any other dependent or independent claims. Such combinations are hereby expressly set forth unless it is stated in individual instances that a specific combination is not intended. Furthermore, features of one 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 (100) for detecting motion of a target (170) in a field of view of a radar sensor (140), comprising a processing circuit system (102), the processing circuit system being configured to: acquiring the amplitude of the spectrum of the received signal (130) of the radar sensor (140), wherein the spectrum includes a first part (200-i) and a second part (200-ii) within a frequency bandwidth (220) divided into windows, wherein the first part (200-i) and the second part (200-ii) are symmetrically located with respect to a center frequency (230), determining, for at least one window in the first portion (200-i), a window threshold based on the amplitude of the spectrum within one or more windows in the second portion (200-ii), determining, for at least one window in the second portion (200-ii), a window threshold based on the amplitude of the spectrum within one or more windows in the first portion (200-i), and In response to the amplitude of the frequency spectrum in at least one window within the frequency bandwidth (220) exceeding the window threshold, motion of the target (170) is detected.

2. An apparatus (100) according to claim 1, wherein each window threshold of the first part (200-i) is determined by multiplying a corresponding value determined using the amplitude of the spectrum within one or more windows of the second part (200-ii) by a predefined factor; and wherein each window threshold of the second part (200-ii) is determined by multiplying a corresponding value determined using the amplitude of the spectrum within one or more windows of the first part (200-i) by the predefined factor.

3. The apparatus (100) according to claim 1 or 2, wherein each window is associated with an amplitude value corresponding to the amplitude of the spectrum within the respective window, and Each window threshold is based on one or more amplitude values ​​of a corresponding window subset, wherein the corresponding window subset includes windows symmetrically positioned relative to the center frequency (230) and / or one or more windows continuously adjacent to the symmetrically positioned windows.

4. The apparatus (100) of claim 3, wherein the corresponding subset of windows is within a predefined frequency range and within the frequency bandwidth (220), the predefined frequency range being centered about the symmetrically positioned windows.

5. The device (100) according to claim 3 or 4, wherein each window threshold is determined by: using maximum likelihood estimation of Rayleigh distribution, obtaining a corresponding calculated value based on the one or more amplitude values ​​of the corresponding window subset, and multiplying the corresponding calculated value by a predefined factor.

6. The apparatus (100) of any one of claims 3 to 5, wherein the processing circuit system (102) is configured to: for each window in the plurality of windows, determining a spike threshold, wherein the spike threshold for a window is based on respective amplitude values ​​associated with a set of windows within a predefined frequency range that includes the window; and If the amplitude of the spectrum in a window exceeds its peak threshold, a new amplitude value is determined, and the amplitude of the spectrum in the window is changed to the new amplitude value.

7. An apparatus (100) according to any of the preceding claims, wherein the processing circuit system (102) is configured to determine a speed threshold frequency range that includes the center frequency (230), wherein a lower limit and an upper limit of the speed threshold frequency range are based on a Doppler speed threshold, and wherein each window within the speed threshold frequency range is excluded from determining a corresponding window threshold.

8. The apparatus (100) of claim 7, wherein each window is associated with an amplitude value corresponding to the amplitude of the frequency spectrum within the respective window, and wherein the processing circuitry (102) is configured to: determining an average amplitude of the corresponding amplitude values ​​associated with the one or more windows within the speed threshold frequency range, determining an average amplitude threshold based on the corresponding amplitude values ​​associated with the window outside the speed threshold frequency range and within the frequency bandwidth (220), and If the average amplitude exceeds the average amplitude threshold, motion of the target (170) is detected.

9. The apparatus (100) of any preceding claim, wherein the amplitude of the spectrum corresponds to a Fourier transform of the received signal (130) within a first time interval (1050-a), and wherein each window threshold is based on a first window threshold of the received signal (130) within the first time interval (1050-a), and wherein the processing circuitry (102) is further configured to: acquiring a plurality of amplitudes of the spectrum within the frequency bandwidth (220), each amplitude corresponding to a Fourier transform of the received signal (130) within a corresponding time frame (1050-x), For each amplitude, each window threshold is updated based on the corresponding amplitude, storing each amplitude and each window threshold of the corresponding amplitude in a memory, and In response to each of at least two of the amplitudes of the frequency spectrum exceeding at least one of its window thresholds in the corresponding window within the frequency bandwidth (220), the target (170) motion is detected.

10. The apparatus (100) according to any one of the preceding claims, wherein the frequency bandwidth (220) is defined by a sampling frequency used to generate the received signal (130).

11. The device (100) according to any one of the preceding claims, wherein the radar sensor (140) is a Doppler radar sensor, and wherein each window is associated with a corresponding Doppler velocity of the target (170) measured using the Doppler effect.

12. The apparatus (100) of any preceding claim, wherein the radar sensor (140) is a frequency modulated continuous wave (FMCW) sensor, and wherein the processing circuitry (102) is configured to output a two-dimensional (2D) FMCW range Doppler map based on the detection of motion of the target (170).

13. A radar system (150), comprising: The device (100) according to any one of claims 1 to 12; as well as The radar sensor (140) is configured to generate the received signal (130).

14. A method (1100) for detecting target motion in a field of view of a radar sensor, comprising: acquiring (1110) an amplitude of a frequency spectrum of a received signal of the radar sensor, wherein the frequency spectrum includes a first portion and a second portion within a frequency bandwidth divided into windows, wherein the first portion and the second portion are located symmetrically with respect to a center frequency, determining (1120A) a window threshold based on the amplitude of the spectrum within one or more windows in the second portion for at least one window in the first portion, determining (1120B) a window threshold based on the amplitude of the spectrum within one or more windows in the first portion for at least one window in the second portion, and In response to the amplitude of the frequency spectrum in at least one window within the frequency bandwidth exceeding the window threshold, the target motion is detected (1130).

15. A program having a program code for carrying out the method (1100) according to claim 14 when the program is executed on a processor or programmable hardware.

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