Patent Description:
One way to improve the distinction is by increasing the signal-to-noise ratio (SNR) between radar reflections from living objects and radar reflections from non-living objects (including noise) by increasing the radiation power of the FMCW radar, which aside from using more electrical power, may raise some health concerns. Another way to increase the SNR is to increase the duty cycle of the FMCW radar and apply Fourier transforms to the radar reflections to distinguish the reflections caused by living objects from the reflections caused by stationary objects or noise. This, however, comes at the expense of significantly increasing the computational load and power consumption of the FMCW radar.

<CIT> discloses a system and method for controlling access to a trunk of a vehicle using a radar sensor. <CIT> discloses a hybrid FMCW-interferometry radar for positioning and monitoring. <CIT> discloses a method for object location with a FMCW radar.

The techniques of this disclosure enable frequency-modulated continuous-wave (FMCW) radar-based detection of living objects. Instead of generating a typical chirp pattern with individual chirps separated by long idle periods, a radar transceiver generates a multiple-chirp pattern with groupings of multiple chirps separated by long idles periods, for each frame. A frame being a duration of time during which the chirp pattern that has a first period of multiple chirps followed by a second period of idle time. From applying a Fourier transform (e.g., a fast Fourier transform, or "FFT") to receiver signals (e.g., digital beat signals including baseband data) for each frame, the radar determines an amplitude of the receiver signals, as a function of range, for each frame. The radar system computes the standard deviation between the amplitudes of two frames and, for each additional frame, the radar incrementally updates the standard deviation between the amplitudes of the two frames to be inclusive of the amplitude contribution of the additional frame. That is, rather than recalculate the standard deviation from scratch in response to each new frame, the radar system "incrementally" adjusts the previous standard deviation by a fraction of the amplitude of the new frame, which is proportionate to the total quantity of frames generated thus far. In response to the adjusted standard deviation satisfying a noise threshold, the radar outputs an indication of a living object. The techniques of this disclosure enable radar-based detection of living objects with an improved signal-to-noise ratio and therefore greater accuracy when compared to conventional FMCW radar systems. Live object detection is improved by the described systems and techniques without increasing radiation power, power consumption, costs, or computational load relative to a conventional FMCW radar system.

According to the invention, a FMCW radar system includes an antenna array, a transceiver configured to generate radar signals via the antenna array, and a processing unit. In one example, the processing unit is configured to direct the transceiver to detect objects by generating, over a plurality of frames, the radar signals having a chirp pattern that has a first period of multiple chirps followed by a second period of idle time, wherein the second period of idle time is longer than the first period of multiple chirps. The processing unit applies a Fourier transform to reflections of the radar signals obtained within each of the plurality of frames to determine a respective amplitude, as a function of range, for each of the plurality of frames, and based on the respective amplitude for each of the plurality of frames, determines a standard deviation in the amplitude as a function of range for the plurality of frames. The processing unit is further configured to, in response to the standard deviation in the amplitude for the plurality of frames satisfying a noise threshold, output an indication of a living object detected during the plurality of frames.

This summary is provided to introduce simplified concepts for FMCW radar detection of living objects, which is further described below in the Detailed Description and Drawings. For ease of description, the disclosure focuses on vehicle-based or automotive-based radar systems for detecting passengers as the living objects, such as children or infants sleeping in car seats. However, the techniques and systems described herein are not limited to vehicle or automotive contexts, but also apply to other environments where radar can be used to detect living objects amongst noise. This summary is not intended to identify essential features of the claimed subject matter, nor is it intended for use in determining the scope of the claimed subject matter.

The details of one or more aspects of FMCW radar-based detection of living objects are described in this document with reference to the following drawings. The same numbers are used throughout the drawings to reference like features and components:.

The details of one or more aspects of radar-based detection of living objects are described below. With long integration times and small duty cycles, conventional FMCW radar systems are particularly suited for identifying subtle variations in radar reflections introduced by mostly stationary living objects from among variations in radar reflections introduced by other, non-living objects. However, thermal noise generated by the radar, as well as noise from other sources, can obscure the radar cross-section (RCS) of a human body, especially the body of a small child, which can make detecting living objects difficult or unreliable.

In contrast to these conventional FMCW radar systems, this document describes a more-reliable FMCW radar system for use as a living-object detector. In accordance with techniques of this disclosure, a FMCW radar system uses an atypical (multiple) chirp pattern for each frame. This increases the signal-to-noise ratio (SNR) between amplitudes of reflections from objects that are alive, and amplitudes of reflections from non-living objects and noise, including thermal noise from the radar itself. For example, the motion pattern from other objects are generally, not similar to the periodicity and amplitude of a moving chest wall of a child. The SNR is increased without increasing radiation power, which aside from preserving electrical power, may reduce some health concerns. The example FMCW radar system increases the SNR without increasing computational load, power consumption, or cost.

Instead of a typical chirp pattern with individual chirps separated by a long idle period, the radar system generates, for a plurality of frames, a repeating-multiple chirp pattern that has a first period of multiple chirps and a second, lengthier period of idle time for each frame. The period of idle time can be orders of a magnitude longer than the first period of the frame. From applying a Fourier transform to individual or averaged receiver signals (e.g., digital beat signals including baseband data) determined from reflections obtained during the plurality of frames, the FMCW radar system determines a respective amplitude, as a function of range, for each of the plurality of frames. From the respective amplitude for each of the plurality of frames, the FMCW radar system computes a standard deviation of the amplitude for the plurality of frames. The FMCW may incrementally update the standard deviation, as a function of range, as each new frame is generated. That is, rather than recalculate the standard deviation each time a new frame is generated, the FMCW radar system can adjust the standard deviation by an amount proportional to the individual contribution of the amplitude of the new frame relative to the standard deviation of the previous frames.

In response to the standard deviation of the amplitude satisfying a noise threshold, the FMCW radar system outputs an indication of a living object detected during the plurality of frames. The FMCW radar system may rely on a predetermined threshold, set to a predetermined level based on observed characteristics of the FMCW radar system. In other examples, the FMCW radar system uses an adaptive noise threshold that changes according to a dynamic noise response of the radar system, including, compensating for power drift in the amplitude of the receiver signals, particularly during power-up. The techniques of this disclosure enable FMCW radar-based detection of living objects with an improved signal to noise ratio and therefore greater accuracy when compared to other radar-based detection systems.

<FIG> illustrates a vehicle <NUM> in which an example FMCW radar system <NUM> can detect living objects, e.g., human and animal living occupants. Although illustrated as a car, the vehicle <NUM> can represent other types of motorized vehicles (e.g., a motorcycle, a bus, a tractor, a semi-trailer truck, or construction equipment), types of non-motorized vehicles (e.g., a bicycle), types of railed vehicles (e.g., a train or a trolley car), watercraft (e.g., a boat or a ship), aircraft (e.g., an airplane or a helicopter), or spacecraft (e.g., satellite).

The FMCW radar system <NUM> (referred to simply as "the radar system <NUM>") is mounted to, or integrated within, the vehicle <NUM>. The techniques and systems described herein are not limited to vehicles or automotive contexts, but also apply to other mobile and non-mobile environments (e.g., residential or commercial heating and cooling systems, lighting systems, security systems) where live-object-detection may be useful, including machinery, robotic equipment, buildings and other structures.

The radar system <NUM> is capable of detecting one or more objects that are within proximity to the vehicle <NUM>. Specifically, the radar system <NUM> is configured for interior, as opposed to exterior, vehicle sensing. The radar system <NUM> is configured to detect signs of life from objects that are alive and inside the vehicle <NUM>.

In the depicted implementation, the radar system <NUM> is located inside the vehicle <NUM> near the ceiling. In other implementations, the radar system <NUM> can be mounted in other parts of the vehicle <NUM>. The radar system <NUM> transmits radar signals and receives radar reflections in a portion of the vehicle <NUM> that is encompassed by a field-of-view <NUM>. The field-of-view <NUM> includes one or more areas occupied by passengers or other living occupants of the vehicle <NUM>. A living object <NUM>, which may sometimes be referred to as a living target, is seated in a front or rear passenger seat, which is within the field-of-view <NUM>.

The radar system <NUM> is shown having three different parts positioned at different locations of the vehicle <NUM>. The radar system <NUM> can include additional or fewer parts in some implementations. Sometimes referred to as modules or radar systems themselves, the parts of the radar system <NUM> can be designed and positioned to provide a particular field of view <NUM> that encompasses a specific region of interest. Example fields of view <NUM> include a <NUM>-degree field of view, one or more <NUM>-degree fields of view, one or more <NUM>-degree fields of view, and so forth, which can overlap (e.g., for creating a particular size field of view). The living object <NUM> is an infant in a car seat. The living object <NUM> can be any other human or animal occupant that reflects radar signals. The radar system <NUM> and the vehicle <NUM> are further described with respect to <FIG>.

In general, the radar system <NUM> is configured to detect the living object <NUM> by generating, over a plurality of frames, a chirp pattern that has a first period of multiple chirps followed by a second period of idle time for each frame. For example, a radar signal <NUM> is shown in <FIG> which includes the chirp pattern described, where in each frame, the radar signal <NUM> includes a repeating pattern of two or more chirps followed by an idle period where the radar signal <NUM> remains silent until the next frame. The period of idle time is longer than the period of multiple chirps. For example, the first period of each frame with the multiple chirps is approximately two or more microseconds and the second period is less than approximately <NUM> milliseconds.

The radar system <NUM> is configured to apply a Fourier transform to the reflected signals corresponding to the pattern of multiple chirps within each of the plurality of frames of the radar signal <NUM>. Using results obtained from application of the transformation, the radar system <NUM> is configured to determine a respective amplitude, as a function of range, for each of the plurality of frames. From the respective amplitudes, the radar system <NUM> is configured to determine a standard deviation in the amplitude, as a function of range, for the frames of the radar signal <NUM>.

The radar system <NUM> may incrementally update the standard deviation in the amplitude, as each frame is generated. For example, rather than recalculate the standard deviation each time a new frame is generated, the radar system <NUM> is configured to adjust the standard deviation by a fraction of the amplitude for the new frame. The fraction of the amplitude is proportional to the individual contribution of the new frame relative to the contribution of the previous frames.

The radar system <NUM> operates according to a noise threshold. In some examples, the noise threshold is an adaptive threshold that adjusts over time. By adjusting the noise threshold based on changes to a dynamic noise response of the radar system <NUM>, including by compensating for power drift in the amplitude of the radar signal <NUM>, particularly during power-up, the radar system <NUM> can more accurately detect living objects.

In response to the standard deviation satisfying the noise threshold, the radar system <NUM> is configured to output an alert or other indication of the living object <NUM> detected during the plurality of frames of the radar signal <NUM>. For example, the field-of-view <NUM> includes one or more areas occupied by passengers of the vehicle <NUM> and the radar system outputs an indication of living object <NUM> detected in the vehicle <NUM>. A processing unit of the radar system <NUM> outputs the indication of the living object <NUM> to an alert system, which in response, outputs an audible, visual, or haptic feedback to a human or machine about an occupant inside an unattended vehicle. The alert system may provide an alarm monitoring service which notifies the owner(s) of the vehicle <NUM> via telephone and if unsuccessful in contacting the owner, contacts help (e.g., local police, fire, or ambulance services). In response to the indication of the living object <NUM>, the alert system may take action, for example, by directing the vehicle <NUM> to heat, cool, or ventilate the interior of the vehicle <NUM> in response to receiving an indication of the living object <NUM>.

The atypical chirp pattern of the radar signal includes a chirp pattern having multiple chirps, instead of a chirp pattern that includes a single chirp which proceeds each idle period of the chirp pattern generated by the radar system <NUM>. The atypical chirp pattern of the radar signal increases the SNR between radar reflections detected from living objects and other radar reflections detected from stationary objects and noise. The SNR is increased without increasing radiation power of the radar system <NUM>, which aside from preserving electrical power, may reduce some health concerns related to operating the radar system <NUM> near the living object <NUM> or other occupants of the vehicle <NUM>. The radar system <NUM> thus increases the SNR without increasing computational load, power consumption, or cost.

<FIG> illustrates an example implementation of the radar system <NUM> as part of the vehicle <NUM>. The vehicle <NUM> includes vehicle-based systems <NUM> that rely on data from the radar system <NUM>, such as an occupancy detector system <NUM> and an autonomous driving system <NUM>. Generally, the vehicle-based systems <NUM> use radar data provided by the radar system <NUM> to perform a function. For example, the autonomous driving system <NUM> takes control of the vehicle <NUM> in response to the radar system <NUM> detecting a sleeping driver to bring the vehicle safely to a stop. The occupancy detector <NUM> sounds an alarm of the vehicle <NUM> and/or ventilates the vehicle <NUM> in response to the radar system <NUM> detecting a child or pet inadvertently left in the vehicle <NUM>, unattended.

The radar system <NUM> includes a communication interface <NUM> to transmit the radar data to the vehicle-based systems <NUM> or to another component of the vehicle <NUM> over a communication bus of the vehicle <NUM>, for example, when the individual components shown in the radar system <NUM> are integrated, including at different positions or locations, within the vehicle <NUM>. In general, the radar data provided by the communication interface <NUM> is in a format usable by the vehicle-based systems <NUM>. The communication interface <NUM> may provide information to the radar system <NUM>, such as the speed of the vehicle <NUM>, the interior temperature of the of the vehicle <NUM>, etc. The radar system <NUM> can use this information to appropriately configure itself. For example, the radar system <NUM> can enter "occupant-detection mode" where the radar system <NUM> configures itself to generate each frame with a multiple chirp pattern in response to receiving an indication that the vehicle <NUM> is parked and/or an internal temperature is above or nearing an unsafe temperature for human or animal occupants.

The radar system <NUM> also includes at least one antenna array <NUM> and a transceiver <NUM> to transmit and receive radar signals. The antenna array <NUM> includes a transmit antenna element, for example, one per each transmit channel. A receive antenna element of the antenna array <NUM> is coupled to each receive channel to receive radar reflections in response to the radar signals. The antenna array <NUM> can include multiple transmit antenna elements and multiple receive antenna elements to configure the radar system <NUM> as a MIMO (Multiple Input Multiple Output) radar system capable of transmitting multiple distinct waveforms at a given time (e.g., a different waveform per transmit antenna element). The antenna elements can be circularly polarized, horizontally polarized, vertically polarized, or a combination thereof.

Using the antenna array <NUM>, the radar system <NUM> can form beams that are steered or un-steered, and wide or narrow. The steering and shaping can be achieved through analog beamforming or digital beamforming. The one or more transmitting antenna elements can have an un-steered omnidirectional radiation pattern, or the one or more transmitting antenna elements can produce a wide steerable beam to illuminate a large volume of space. To achieve object angular accuracies and angular resolutions, the receiving antenna elements can be used to generate hundreds of narrow steered beams with digital beamforming. In this way, the radar system <NUM> can efficiently monitor an external or internal environment of the vehicle <NUM> to detect one or more objects within the field-of-view <NUM>.

The transceiver <NUM>, which may include multiple transceivers, includes circuitry and logic for transmitting radar signals and receiving radar reflections (also sometimes referred to as radar receive signals or radar returns) via the antenna array <NUM>. A transmitter of the transceiver <NUM> includes one or more transmit channels and a receiver of the transceiver <NUM> includes one or more receive channels, which may be of a similar or different quantity than a quantity of the transmit channels. The transmitter and receiver may share a local oscillator (LO) to synchronize operations. The transceiver <NUM> can also include other components not shown, such as amplifiers, mixers, phase shifters, switches, analog-to-digital converters, combiners, and the like.

The transceiver <NUM> is primarily configured as a continuous-wave transceiver <NUM> to execute FMCW operations, and may also include logic to perform in-phase/quadrature (I/Q) operations and/or modulation or demodulation in a variety of ways, including linear-frequency modulations, triangular-frequency modulations, stepped-frequency modulation, or phase modulation. The transceiver <NUM> may be configured to support pulsed-radar operations, as well.

A frequency spectrum (e.g., range of frequencies) of radar signals and radar reflections can encompass frequencies between one and ten gigahertz (GHz), as one example. The bandwidths can be less than one GHz, such as between approximately three hundred megahertz (MHz) and five hundred MHz. The frequencies of the transceiver <NUM> may be associated with millimeter wavelengths.

The radar system <NUM> also includes at least one processing unit <NUM> and computer-readable storage media (CRM) <NUM>. The CRM <NUM> includes a raw-data processing module <NUM> and a radar control module <NUM>. The raw-data processing module <NUM> and the radar control module <NUM> can be implemented using hardware, software, firmware, or a combination thereof. In this example, the processing unit <NUM> executes instructions for implementing the raw-data processing module <NUM> and the radar control module <NUM>. Together, the raw-data processing module <NUM> and the radar control module <NUM> enable the processing unit <NUM> to process responses from the receive antenna elements in the antenna array <NUM> to detect the living object <NUM> and generate radar data for the vehicle-based systems <NUM>.

The raw-data processing module <NUM> transforms receiver signals including raw data (e.g., digital beat signals including baseband data) provided by the transceiver <NUM> into radar data (e.g., an amplitude as a function of range) that is usable by the radar control module <NUM>. The radar control module <NUM> analyzes the radar data obtained over time to map one or more detections, e.g., of living objects. The radar control module <NUM> determines whether a living object <NUM> is present within the field-of-view <NUM> using a living-object detector <NUM> and optionally, an adaptive-threshold adjuster <NUM>.

The living-object detector <NUM> causes the radar control module <NUM> to operate in an occupant-detection mode where the radar signal <NUM> is analyzed for signs of living objects obscured by (e.g., thermal) noise. The living-object detector <NUM> determines a standard deviation between multiple frames to isolate stationary living objects, which move even if only to breath, from non-living objects, which remain mostly stationary from one frame to the next. The living-object detector <NUM> uses a noise threshold to determine whether the standard deviation at a particular range from the radar system <NUM> is a living object. The noise threshold is set to ensure that the movement is sufficient to indicate presence of a living object. Using the noise threshold, the radar system <NUM> can differentiate between a living object and either a stationary object or thermal noise produced by the radar system <NUM>.

The living-object detector <NUM> may determine a respective amplitude as a function of range for each of M plurality of frames by applying a Fourier transform, such as an FFT, to respective receiver signals of the N chirps in each frame. In processing the radar signal <NUM>, for example, the living-object detector <NUM> applies a Fourier transform to the receiver signal of each chirp in each frame. The results of each of the Fourier transforms are integrated over frames, using non-coherent integration (NCI). The living-object detector <NUM> determines a respective amplitude as a function of range for each of the M plurality of frames. A standard deviation of the amplitude as a function of range between two or more of the plurality of frames is determined by integrating, using non-coherent integration, results of the Fourier transform applied to the respective receiver signal of each new frame M, with the standard deviation in amplitude over the previously received, plurality of frames <NUM> through (M - <NUM>).

The adaptive-threshold adjuster <NUM> is an optional component of the radar system <NUM>. The living-object detector <NUM> may rely on the adaptive-threshold adjuster <NUM> to set the noise threshold used by the living-object detector <NUM> while the radar system <NUM> is operating in the occupant-detection mode. As the environment within the vehicle <NUM> changes, the adaptive-threshold adjuster <NUM> automatically sets the noise threshold used, by the radar system <NUM>, to detect a living object by accounting for the environmental changes. For example, during power-on, the radar signal <NUM> may undergo power drift until settling down to a normal level. As the effects of power drift become less, the adaptive-threshold adjuster <NUM> modifies the noise threshold settle to a nominal level. Over time, as the environment continues to change, the adaptive-threshold adjuster <NUM> increases and decreases the noise threshold with changes in noise levels, smoothing changes to the noise threshold between sequential frames.

The radar control module <NUM> produces the radar data for the vehicle-based system <NUM>. Example types of radar data include a Boolean value that indicates whether or not the object <NUM> is present within a particular region of interest, a number that represents a characteristic of the object <NUM> (e.g., position, speed, or direction of motion), or a value that indicates the type of object <NUM> detected (e.g., a living or non-living). The radar control module <NUM> configures the transceiver <NUM> to emit radar signals and detect radar reflections via the antenna array <NUM>. The radar control module <NUM> outputs information associated with the radar reflections detected from radar signals that reach objects, such as the object <NUM>.

<FIG> illustrates an example operation <NUM> of the radar system <NUM>. Within the vehicle <NUM>, the living object <NUM> is located at a particular slant range and angle from the antenna array of the radar system <NUM>. To detect the living object <NUM>, the radar system <NUM> transmits and receives a radar signal <NUM>-<NUM>, which is an example of a frame <NUM> of the radar signal <NUM>. The radar signal <NUM>-<NUM> is transmitted as a radar transmit signal <NUM>. At least a portion of the radar transmit signal <NUM> is reflected by the living object <NUM>. This reflected portion represents a radar reflection or a radar receive signal <NUM>. The radar system processes the radar receive signal <NUM> to extract data for a vehicle-based system, such as the vehicle-based systems <NUM>. As shown in <FIG>, an amplitude of the radar receive signal <NUM> is smaller than an amplitude of the radar transmit signal <NUM> due to losses incurred during propagation and reflection.

Although the radar transmit signal <NUM> is illustrated as having a single waveform, the radar transmit signal <NUM> can be composed of multiple radar transmit signals <NUM> that have distinct waveforms to support MIMO operations. Likewise, the radar receive signal <NUM> can be composed of multiple radar receive signals <NUM> that also have different waveforms.

The radar transmit signal <NUM> includes one or more chirps <NUM>-<NUM> to <NUM>-N, where N represents a positive integer. The radar system <NUM> can transmit the chirps <NUM>-<NUM>, <NUM>-<NUM>,. , <NUM>-N (collectively "the chirps <NUM>") in a continuous sequence or transmit the chirps as time-separated pulses. The chirps <NUM>, when followed by a period of idle time, represent a frame <NUM>. The radar transmit signal <NUM> can include a quantity of M frames <NUM>, where M represents a positive integer.

Individual frequencies of the chirps <NUM> can increase or decrease over time, but the slope or rate of change in the individual frequencies between the chirps <NUM> can be consistent. In the depicted example, the radar system <NUM> employs a single-slope cycle to linearly decrease the frequencies of the chirps <NUM> over time. Other types of frequency modulations are also possible, including a two-slope cycle and/or a non-linear frequency modulation. In general, transmission characteristics of the chirps <NUM> (e.g., bandwidth, center frequency, duration, and transmit power) can be tailored to achieve a particular detection range, range resolution, or Doppler coverage for detecting the living object <NUM>.

At the radar system <NUM>, the radar receive signal <NUM> represents a delayed version of the radar transmit signal <NUM>. The amount of delay is proportional to the slant range (e.g., distance) from the antenna array <NUM> of the radar system <NUM> to the living object <NUM>. In particular, this delay represents a summation of a time it takes for the radar transmit signal <NUM> to propagate from the radar system <NUM> to the living object <NUM> and a time it takes for the radar receive signal <NUM> to propagate from the living object <NUM> to the radar system <NUM>. If the living object <NUM> and/or the radar system <NUM> is moving, the radar receive signal <NUM> is shifted in frequency relative to the radar transmit signal <NUM> due to the Doppler effect. In other words, characteristics of the radar receive signal <NUM> are dependent upon motion of the living object <NUM> and/or motion of the vehicle <NUM>. Similar to the radar transmit signal <NUM>, the radar receive signal <NUM> is composed of one or more of the chirps <NUM>. The chirps <NUM> enable the radar system <NUM> to make multiple observations of the object living <NUM> over a first time period during each of the frames <NUM>.

Where the radar system <NUM> is used to detect very slow motions, such as movements of a chest wall during respiration and heartbeat, amplitude of the radar receive signals <NUM> within a few microseconds will not change much. The radar signal <NUM>-<NUM> is based on a waveform structure with a combination of fast chirps and very slow chirps (or idle time) in each frame <NUM>. The fast chirps <NUM> are followed by an idle period. The waveform includes N fast chirps <NUM> during a repetition period of a few microseconds. After the N fast chirps <NUM>, a long idle period of the waveform precedes the start of the next frame <NUM>. The idle period may be as long as <NUM> milliseconds. Each set of N fast chirps <NUM> in combination with the idle period forms a slow frame <NUM>.

The operation <NUM> is further described in the context of <FIG>. During transmission, the transceiver <NUM> accepts a control signal from the processing unit <NUM>. Using the control signal, the processing unit <NUM> directs the transceiver <NUM> to operate in a particular configuration or operational mode, such as an occupant-detection mode. As an example, the control signal can specify types of waveforms to be generated by the transmit channels of the transceiver <NUM>. Different waveform types can have a different N quantity of chirps <NUM>, M quantity of frames <NUM>, chirp durations, frame durations, center frequencies, bandwidths, types of frequency modulation (e.g., a single-slope modulation, a two-slope modulation, a linear modulation, or a non-linear modulation), or types of phase modulations (e.g., different orthogonal coding sequences). Additionally, the control signal can specify which transmit channels are enabled or disabled. In the example of <FIG>, the control signal specifies the characteristics of the radar signal <NUM>-<NUM> as having a quantity of N chirps <NUM>, a recurring idle time at the end of each frame <NUM>, and a total quantity of M frames <NUM>.

Based on the control signal, the transceiver <NUM> generates a frequency-modulated radar signal <NUM>-<NUM> at radio frequencies on the transmit channels. A phase modulator of the transceiver <NUM>, may modulate phases of chirps within the frequency-modulated radar signal to generate a frequency-modulated and phase-modulated radar signal in cases where phase-modulation is used. For example, the phases of the chirps <NUM> can be determined based on a coding sequence specified by the control signal. The control signal directs the transceiver <NUM> to transmit a FMCW radar signal and in return receive FMCW radar reflections from objects in the field-of-view <NUM>.

During reception, the receive antenna elements of the antenna array <NUM> receive a version of a radar receive signal <NUM>. Relative phase differences between these versions of the radar receive signal <NUM> are due to differences in locations of the receive antenna elements and the transmit antenna elements of the antenna array <NUM>. Within each receive channel, a mixer performs a beating operation, which down-converts and demodulates the radar receive signals <NUM> to generate corresponding beat signals.

A frequency of a beat signal for a chirp pattern that relies on a chirp pattern with a single chirp <NUM> between each idle period corresponds to a difference in frequency between the radar transmit signal <NUM> and the radar receive signal <NUM>. This frequency difference is proportional to a slant range between the antenna array <NUM> and the object <NUM>. The beat signal for each frame <NUM> represents a combination of the beat signals for some or all of the chirps <NUM> within each frame <NUM>.

<FIG> illustrates amplitudes, as a function of range, of multiple radar signals received by an example FMCW radar system. As depicted in <FIG>, the radar system <NUM> receives radar signals <NUM>-<NUM> through <NUM>-<NUM>, which are each an example of a frame <NUM> of the radar signal <NUM>. The radar system <NUM> determines amplitudes of the radar signals <NUM>-<NUM> through <NUM>-<NUM> as a function of range. Each of the radar signals <NUM>-<NUM> through <NUM>-<NUM> is unique to a single frame <NUM>. At a range of <NUM>, the peak amplitude of each of the radar signals <NUM>-<NUM> through <NUM>-<NUM> decreases from one signal to the next. The change in amplitude across a sequence of frames <NUM> at the range <NUM> indicates movement at the range <NUM>. In contrast, at <NUM> and most other ranges, the amplitude of the radar signals <NUM>-<NUM> through <NUM>-<NUM> remains consistent from one frame <NUM> to the next. A consistent amplitude between frames <NUM>, e.g., at the range <NUM> and other ranges excluding the range <NUM>, indicates a lack of movement at a particular range.

Due to radar-cross-section-decorrelation at certain ranges, the radar system <NUM> detects enough amplitude variation. Decorrelation occurs when the observation of radar-cross-section is significantly changed by an alteration of time, frequency, or angle. Once a target moves about a range, geometry of a reflecting surface undergoes some changes and hence radar-cross-section-decorrelation occurs. This radar-cross-section-decorrelation is the source of amplitude variation for detecting a living object. A choice of frequency is dependent on an amount of fluctuation expected for a particular geometry of the reflecting surface.

The variable peaks of the radar signals <NUM>-<NUM> through <NUM>-<NUM> at the range <NUM> from one frame <NUM> to the next frame <NUM> can be indicative of a moving or living object at that range. The lack of movement at a particular range, however, from one frame <NUM> to the next frame <NUM> can be indicative of a stationary or non-living object at that range. To determine whether the variable peaks are indicative of a living object, the radar system computes a standard deviation <NUM> of the amplitude, as a function of range, of the radar signals <NUM>-<NUM> through <NUM>-<NUM>.

<FIG> illustrates the standard deviation <NUM> of the radar signal <NUM> from <FIG>. As in <FIG>, the standard deviation <NUM> of the radar signals <NUM>-<NUM> through <NUM>-<NUM>, is depicted as a function of range. The standard deviation <NUM> is mostly consistent and below a noise threshold for the multiple frames <NUM>. However, at the range <NUM>, where each of the radar signals <NUM>-<NUM> through <NUM>-<NUM> peaks with varying amplitudes, the standard deviation <NUM> of the radar signals <NUM>-<NUM> through <NUM>-<NUM> is above the noise threshold, which is indicative of movement. Certain movement, for example, when the standard deviation <NUM> exceeds the noise threshold and/or has other characteristics (e.g., a rate of repetition), may be indicative of a vital sign from a living object. A deviation in amplitude above the noise threshold, for multiple sets of frames <NUM>, may be a sign of respiration or a heartbeat. The radar system <NUM> detects a living object in response to detecting movement over multiple successive frames with sufficient deviation to be indicative of a living object. For example, in response to determining that the standard deviation <NUM> for multiple frames <NUM> exceeds the noise threshold at the range <NUM>, the radar system <NUM> outputs an indication of a detection of a living object.

<FIG> illustrates example operations performed by an FMCW radar system, such as the radar system <NUM>. For example, the processing unit <NUM> configures the radar system <NUM> to perform operations <NUM> through <NUM> by executing instructions associated with the radar control module <NUM>, the living-object detector <NUM>, or the adaptive-threshold adjuster <NUM>. The operations (or acts) <NUM> through <NUM> are performed but not necessarily limited to the order or combinations in which the operations are shown herein. Further, any of one or more of the operations may be repeated, combined, or reorganized to provide other operations.

At <NUM>, the radar system <NUM> generates a plurality of frames using a chirp pattern that has a first period of multiple chirps followed by a second period of idle time. For example, the radar signal <NUM>, including the chirps <NUM>, is generated for a plurality of frames <NUM>.

At <NUM>, the radar system <NUM> applies a Fourier transform to the generating of the first period within each of the plurality of frames. For example, the radar system applies a fast Fourier transform to a receiver signal of each of the chirps <NUM>. The radar system <NUM> may instead collectively apply a Fourier transform to the chirps <NUM> by applying the Fourier transform to a combined (e.g., averaged, summed) receiver signal for the chirps <NUM> in each frame <NUM>.

At <NUM>, the radar system <NUM> determines a respective amplitude as a function of range for each of the plurality of frames. At <NUM>, the radar system <NUM> determines a standard deviation in the respective amplitude, as a function of range, between at least two of the plurality of frames. When captured over several frames <NUM>, the radar signal <NUM> may have the standard deviation <NUM>.

At <NUM>, the radar system determines whether the standard deviation satisfies a noise threshold. If "No" at <NUM>, the standard deviation does not satisfy the noise threshold at any range, and the radar system <NUM> returns to operation <NUM> to repeat the generating process. If "Yes" at <NUM>, the standard deviation range satisfies the noise threshold and a moving object, specifically a living object, is detected. When captured over several frames <NUM>, the radar signal <NUM> may have the standard deviation <NUM>, which indicates a living object detected at the range <NUM>.

At <NUM>, an indication of a living object detected during the at least two of the frames is output. For example, the radar system <NUM> generates radar data usable by the vehicle-based systems <NUM> in controlling the vehicle <NUM>. The vehicle-based systems <NUM> may control heating or cooling to maintain a particular temperature or temperature range within the vehicle <NUM>. For example, in response to detecting a living object in the vehicle <NUM> while the vehicle <NUM> is heating or cooling towards an unsafe temperature, the vehicle-based systems <NUM> turn on a heating and cooling system or open a window to ventilate and keep the vehicle <NUM> within a safe range of temperatures.

<FIG> and <FIG> illustrate different examples of the living-object detector <NUM> of the radar system <NUM>. Each of the <FIG> and <FIG> is described in the context of the radar signal <NUM> from <FIG>, which is reproduced in <FIG> and <FIG> for readability. The radar system <NUM> may perform the operations <NUM> through <NUM> by causing the processing unit <NUM> to execute instructions associated with a living-object detector <NUM>-<NUM> or <NUM>-<NUM>, each of which is an example of the living-object detector <NUM>. The radar signal <NUM> includes a plurality, M, of frames using a chirp pattern that has a period of multiple, N, chirps <NUM> followed by a second period of idle time, which is free from chirps.

The living-object detector <NUM>-<NUM> is configured to apply one of Fourier Transforms (FT) <NUM>-<NUM> through <NUM>-N (collectively referred to as "Fourier transforms <NUM>") to a respective receiver signal of a corresponding one of the chirps <NUM>-<NUM> through <NUM>-N. For example, the living-object detector <NUM>-<NUM> applies the Fourier transform <NUM>-<NUM> to the receiver signal of the first chirp <NUM>-<NUM>, the living-object detector <NUM>-<NUM> applies the Fourier transform <NUM>-<NUM> to the receiver signal of the second chirp <NUM>-<NUM>, and so forth. In each frame M, the living-object detector <NUM>-<NUM> uses a respective one of the Fourier transforms <NUM> for the receiver signal of each of the N chirps <NUM>.

After applying a respective one of the Fourier transforms <NUM> to the respective receiver signal of each of the N chirps <NUM>, a non-coherent integrator <NUM> of the living-object detector <NUM>-<NUM> integrates, using non-coherent integration, each result of the Fourier transforms <NUM> to determine a respective amplitude, as a function of range, associated with each of the N chirps <NUM>, as integrated over a sequence of M frames <NUM>. The non-coherent integrator <NUM> outputs non-coherent integration (NCI) results <NUM>, which each indicate a respective amplitude, as a function of range, for each of the N chirps <NUM>, over M frames <NUM>. The results <NUM> can represent amplitude/range graphs as shown in <FIG>.

A statistical detector <NUM> of the living-object detector <NUM>-<NUM> applies a statistical operation, such as standard deviation, to the NCI results <NUM> to determine a standard deviation of amplitude, as a function of range, for the M frames <NUM>. For example, the statistical detector <NUM> outputs the standard deviation <NUM> in response to receiving the results <NUM> determined from the radar signals <NUM>-<NUM> through <NUM>-<NUM>.

In response to the standard deviation satisfying a threshold, the living-object detector <NUM>-<NUM> outputs a detection alert <NUM>. The processing unit <NUM> is configured to output the indication of the passenger of the vehicle <NUM> to an alert system (e.g., a mobile phone) that is configured to output an alert about the passenger of the vehicle.

Instead of applying the Fourier transform on a chirp by chirp basis as is done by the living-object detector <NUM>-<NUM>, the living-object detector <NUM>-<NUM> in <FIG>, when executed by the processing unit <NUM>, configures the radar system <NUM> to apply the Fourier transform at a frame-level. The Fourier transform is applied to a common receiver signal for each frame <NUM>. The common receiver signal is representative of the receiver signal of some or all the chirps <NUM> in each frame <NUM>.

For example, the processing unit <NUM> determines the common receiver signal for the multiple chirps <NUM> in each frame <NUM> by averaging the respective receiver signals of the multiple chirps <NUM> in that frame <NUM>. The processing unit <NUM> may instead determine the common receiver signal for the multiple chirps <NUM> in each frame <NUM> by summing the respective receiver signals of the multiple chirps <NUM> in that frame <NUM>.

In response to the standard deviation satisfying a threshold, the living-object detector <NUM>-<NUM> outputs a detection alert <NUM>. For example, the processing unit <NUM> outputs the indication of the passenger of the vehicle <NUM> to an emergency alert system or car alarm that is configured to output an alert about the passenger in an unattended vehicle.

The common receiver signal may be determined using all the chirps <NUM> in a frame <NUM>. In other instances, only some of the chirps <NUM> are used to determine the common receiver signal. One or more of the radar signals <NUM>-<NUM> through <NUM>-<NUM> may be corrupted or redundant to another one of the radar signals <NUM>-<NUM> through <NUM>-<NUM> and therefore, may be excluded from the common receiver signal determination.

<FIG> illustrates examples of a standard deviation in an amplitude of radar reflections, as a function of range, determined by the living-object detectors of <FIG> and <FIG>, in contrast to a standard deviation in an amplitude of a conventional radar system. <FIG> shows a SNR of a conventional radar system that uses a typical chirp pattern with individual chirps separated by long idle periods, relative to a SNR of the radar system <NUM> which uses an atypical (multiple) chirp pattern, given different N quantities of chirps, over M quantity of frames, where M equals fifty. When five chirps are used, the SNR improvement over a conventional radar system is about six decibels. Using ten chirps per frame improves the SNR by ten decibels over the conventional radar system. Finally, if the radar system <NUM> uses thirty chirps over one of fifty frames, the SNR improvement will be just under fifteen decibels.

<FIG> illustrates example operations performed by an FMCW radar system, such as the radar system <NUM>. The processing unit <NUM> may configure the radar system <NUM> to perform operations <NUM> through <NUM> by executing instructions associated with the radar control module <NUM>, the living-object detector <NUM>, or the adaptive-threshold adjuster <NUM>. The operations <NUM> through <NUM> may be repeated, combined, or reorganized to provide other operations, without necessarily being limited to the order and combination shown in <FIG>.

To distinguish a living object <NUM> from noise, such as thermal noise from the radar system <NUM> itself or environmental noise of the vehicle <NUM>, the radar system <NUM> uses a noise threshold to determine if the standard deviation of the amplitude of the radar signal <NUM>, as a function of time, is strong enough to trigger an output of an indication of a live object <NUM>. Said differently, the noise threshold prevents false triggers to detections or detections with low-amplitude, which improves accuracy of the radar system <NUM>.

In some examples, the noise threshold can be set to a predetermined value based on a predefined set of radar characteristics. A predetermined threshold is application dependent and is set to a value that makes the living objects detectable when a standard deviation in amplitude, peaks above expected noise levels. Rather than a predetermined threshold, the radar system <NUM> uses an adaptive threshold, which is set by performing the operations <NUM> through <NUM>.

In summary, the adaptive threshold is determined initially when the radar system <NUM> powers-on, powers-up, or otherwise starts to operate. The adaptive threshold can also be updated periodically, randomly, or otherwise as needed, anytime the radar system <NUM> performs the operations <NUM> through <NUM>. To calculate the threshold, the radar transmits N fast chirps. For each fast chirp, a Fourier transform is used to process the receiver signal associated with the chirp, which is then used to generate a range profile across M frames. The range profile represents a function for determining amplitude of a radar receive signal, as a function of range. The standard deviation in amplitude of the range profiles generated for the M frames is determined. The adaptive threshold, as a function of range, may be obtained optionally after adding an offset and/or smoothing the standard deviation from the previous frames <NUM> through (M - <NUM>) to a current frame M.

At <NUM>, the radar system <NUM> generates a plurality of frames using a chirp pattern that has a first period of multiple chirps followed by a second period of idle time. For example, the radar signal <NUM>, including the chirps <NUM>, is generated for a plurality of frames <NUM> (e.g., Frame <NUM> to frame M). At <NUM>, the radar system <NUM> applies a Fourier transform to radar reflections obtained during the first period within each of the plurality of frames. The radar system applies the Fourier transform to a respective receiver signal of each of the chirps <NUM>. The radar system <NUM> may instead apply the Fourier transform, collectively, to the chirps <NUM> by applying the Fourier transform to a combined (e.g., averaged, summed) receiver signal for each different chirp <NUM>, over multiple frames <NUM>.

At <NUM>, the radar system <NUM> determines a respective amplitude, as a function of range, for each of the plurality of frames. At <NUM>, the radar system <NUM> determines a baseline standard deviation in the respective amplitude of at least two of the plurality of frames. For example, the processing unit <NUM> is configured to determine a baseline standard deviation to be used for Frame <NUM>, based on a standard deviation in amplitude for Frames <NUM> through <NUM>. The baseline standard deviation in amplitude, as a function of range, for a current frame is set to the standard deviation in amplitude, as a function of range, of a plurality of prior frames.

At <NUM>, before optionally adding an offset to the baseline standard deviation, the radar system <NUM> optionally smooths the baseline standard deviation for the at least two frames. At <NUM>, after smoothing the baseline standard deviation, the radar system <NUM> determines the adaptive noise threshold by applying an offset to the baseline standard deviation. In other words, the processing unit <NUM> is configured to determine the adaptive noise threshold for a third frame by smoothing the baseline standard deviation for a prior first and second frame. Adjusting the adaptive noise threshold in this way enables accurate detections despite a dynamic and noisy environment.

For example, the adaptive-threshold adjuster <NUM> may increase the baseline standard deviation by an offset. Based on the increased baseline standard deviation, a standard deviation for another plurality of frames is determined and smoothed by the adaptive-threshold adjuster <NUM>. This way, the adaptive-threshold adjuster <NUM> updates the adaptive noise threshold by setting the adaptive noise threshold to the smoothed, baseline standard deviation. Responsive to a standard deviation for subsequent frames satisfying the adaptive noise threshold, the radar system <NUM> outputs an indication of a living object <NUM> detected during the subsequent frames.

At <NUM>, the radar system detects living objects at ranges where a standard deviation in amplitude among received radar reflections peaks above the noise threshold. For example, the processing unit <NUM> is configured to direct a transceiver (e.g., the transceiver <NUM>) to generate a fast-N chirp pattern across a plurality of M frames. Based in part on the current standard deviation and a respective amplitude as a function of range for a subsequent frame, the processing unit <NUM> determines a new, updated standard deviation for the M frames. In response to the new standard deviation not satisfying the noise threshold, the processing unit <NUM> directs the radar system <NUM> to refrain from outputting the indication of the object. Alternatively, in response to the new standard deviation satisfying the noise threshold, the processing unit <NUM> directs the radar system <NUM> to output the indication of the object. For example, in response to detecting a living object <NUM> in the vehicle <NUM> while the vehicle <NUM> is heating or cooling towards an unsafe temperature, the vehicle-based systems <NUM> turn on a heating and cooling system or open a window to ventilate and keep the vehicle <NUM> within a safe temperature.

<FIG> and <FIG> illustrate different examples of adaptive-threshold adjusters <NUM> of the radar system <NUM>. Other examples of the adaptive-threshold adjuster <NUM> are possible including additional or fewer components than those shown in <FIG> and <FIG>. In either example, the adaptive-threshold adjusters <NUM>-<NUM> and <NUM>-<NUM> each apply a Fourier transform to a respective receiver signal of each chirp from a multiple chirp pattern.

An adaptive-threshold adjuster <NUM>-<NUM>, as depicted in <FIG>, applies a Fourier transform <NUM>-<NUM> through <NUM>-N, to the receiver signal of each chirp <NUM>-<NUM> through <NUM>-N in a plurality of M frames. A standard deviation component <NUM> computes a baseline standard deviation <NUM> and after smoothing and applying an offset using a smooth and offset component <NUM>, the adaptive-threshold adjuster <NUM>-<NUM> outputs an adaptive threshold <NUM>. For example, the standard deviation component <NUM> integrates, using non-coherent integration, results of the applying the Fourier transforms <NUM>-<NUM> through <NUM>-N to the respective receiver signal of each chirp from the multiple chirps <NUM> in each of the plurality of frames <NUM>.

The adaptive threshold <NUM> is determined as a function of the baseline standard deviation <NUM> plus an offset to tune the radar system <NUM> to be more or less susceptible to noise. To determine the adaptive noise threshold <NUM>, an offset may be added to the baseline standard deviation after smoothing the baseline standard deviation.

In <FIG>, an adaptive-threshold adjuster <NUM>-<NUM> applies a Fourier transform <NUM>-<NUM> through <NUM>-N, to a common receiver signal associated with each chirp <NUM>-<NUM> through <NUM>-N. The common receiver signal represents a combination (e.g., average, summation) of the receiver signal for a particular one of the chirps <NUM>, over the plurality of M frames. A combiner <NUM>-<NUM> through <NUM>-N feeds a corresponding one of the Fourier transforms <NUM>-<NUM> through <NUM>-N. For example, with five frames (e.g., M equals five), a combined receiver signal associated with the chirp <NUM>-<NUM> across the five frames is determined by averaging or summing the receiver signal of the chirp <NUM>-<NUM> for Frame <NUM>, with the chirp <NUM>-<NUM> for Frame <NUM>,. , and with the chirp <NUM>-<NUM> for Frame M.

A standard deviation component <NUM> computes a baseline standard deviation <NUM> based on the outputs from the Fourier transforms <NUM>-<NUM> through <NUM>-N. The baseline standard deviation <NUM> is smoothed and an offset is applied using a smooth and offset component <NUM>. The adaptive-threshold adjuster <NUM>-<NUM> outputs an adaptive threshold <NUM>. The adaptive threshold <NUM> is determined as a function of the baseline standard deviation <NUM> plus an offset to tune the radar system <NUM> to be more or less susceptible to noise. To determine the adaptive threshold <NUM>, an offset may be added to the baseline standard deviation after smoothing the baseline standard deviation.

<FIG> illustrates an example adaptive threshold during part of a frame generated by an FMCW radar system that uses the example adaptive-threshold adjusters of <FIG> or <FIG>. As shown in <FIG>, the adaptive threshold is able to follow the noise response of the radar system <NUM> and make the signature from the living object <NUM> readily detectable.

The adaptive-threshold adjuster <NUM> computes an adaptive noise threshold by adding an offset to a baseline standard deviation for a prior plurality of frames, after smoothing the baseline standard deviation. Based on the baseline standard deviation, a current standard deviation for a current plurality of frames (e.g., including the prior plurality of frames) is determined and smoothed by the adaptive-threshold adjuster <NUM>. This way, the adaptive-threshold adjuster <NUM> updates the adaptive-noise threshold by setting the adaptive-noise threshold for a plurality of frames generated using the chirp pattern to the smoothed standard deviation for a prior plurality of frames. Responsive to a standard deviation for the plurality of frames generated using the chirp pattern satisfying the adaptive noise threshold, the radar system <NUM> outputs an indication of a living object <NUM> detected during the plurality of frames.

When performed by the radar system <NUM>, the operations <NUM> through <NUM> configure the radar system <NUM> to incrementally compute a standard deviation in amplitude, as a function of range, associated with multiple chirps <NUM> and over multiple frames <NUM>. To calculate the standard deviation of multiple measurements, a conventional radar system waits until sufficient radar data has been collected from the transceiver(s) before performing the calculation. This conventional way requires a large memory to store all the radar data and ultimately increases an amount of time (response time) to detect living targets. Rather than wait to calculate the standard deviation, the radar system <NUM> performs operations <NUM> through <NUM> to incrementally update, e.g., at the end of each frame <NUM>, mean amplitude µ and standard deviation in amplitude σ calculations.

The standard equation for calculating an arithmetic mean µ is by using Equation <NUM>, where n is the total number of samples, xi is one particular sample in a quantity of i samples: <MAT> Each sample xi represents an amplitude of a radar receive signal or radar reflection, as a function of range, for a particular chirp or group of chirps, in a frame. A conventional radar collects and stores all the samples xi before calculating the mean µ amplitude as a function of range, according to the Equation <NUM>, which requires a processing unit to have access to a large memory if the quantity i of the samples xi is large. In addition, the computation may experience an overflow condition during summation if the quantity i of the samples xi sums to a value that is too great for the processing unit to handle.

The radar system <NUM> performs operations <NUM> through <NUM> to perform an incremental mean and standard deviation calculation based on an incremental mean µn computation expressed as Equation <NUM>. The Equation <NUM> is based on the Equation <NUM>, but rewritten as follows: <MAT> Each new or updated mean µn is set to the old or current mean µn-<NUM> but adjusted by a fraction <NUM>/n of the difference between the current sample xn and the current mean µn-<NUM>. Equation <NUM> provides a more stable computation than Equation <NUM> because Equation <NUM> avoids the accumulation of large sums.

Below is Equation <NUM>, which is the equation a conventional radar system uses to calculate the standard deviation σ: <MAT> In a simple implementation, a conventional radar system performs two passes over accumulated radar data to compute the standard deviation σ derived from the Equation <NUM>. During the first pass, the conventional radar system calculates the mean µ for all the samples xi. Then, during a second pass, the radar system sums the square of the distances from each of the samples xi to the mean µ.

After some rearrangement, the calculation of the standard deviation σ in the Equation <NUM> can be rewritten as Equation <NUM>, which follows as: <MAT> Computing the standard deviation σ according to the Equation <NUM> requires all the samples xi to be already collected and stored. Secondly, the Equation <NUM> is dependent on the arithmetic mean µ calculation (Equation <NUM>), which has overflow precision issues with large sample sizes (e.g., in implementations where i is a large integer). These two issues are resolved through use of an incrementally updated variance formula Sn, as explained below.

As shown below in Equation <NUM>, the radar system <NUM> incrementally updates the variance Sn by assuming: <MAT>.

When combined with the Equation <NUM>, the variance Sn from the Equation <NUM> can be re-written as shown below in Equation <NUM>: <MAT>.

After further derivation, the Equations <NUM> and <NUM> can be reduced to Equation <NUM>, the variance Sn: <MAT>.

The variance Sn from the Equation <NUM> leads to the incremental standard deviation σ, as shown in the Equation <NUM>: <MAT> Computing the Equations <NUM> and <NUM> does not require the radar system <NUM> to maintain a cumulative sum for all the frames, nor does the radar system <NUM> suffer from the potential overflow issues that a conventional radar system can experience by computing the standard deviation σ strictly following the Equation <NUM>.

The radar system <NUM> need not store any of the samples x for the final calculation. Instead, the radar system <NUM> can simply store a previous variance Sn-<NUM> value and continuously update the previously stored variance value Sn-<NUM> to compute the standard deviation σ according to the Equation <NUM>, as the radar system <NUM> receives new samples xn. Given the above derivation, the radar system <NUM> executes the operations <NUM> through <NUM> to update the standard deviation incrementally with each new sample xn based on the principles of the Equation <NUM>.

At <NUM>, the processing unit <NUM> of the radar system <NUM> directs a transceiver <NUM> to detect living objects by generating a first plurality of frames <NUM> through (n - <NUM>), using a chirp pattern that has a first period of multiple chirps followed by a second period of idle time. At <NUM>, the processing unit <NUM> applies a Fourier transform, such as a FFT, to radar reflections obtained during the first period within each of the first plurality of frames to determine a respective amplitude, as a function of range, for each of the first plurality of frames.

At <NUM>, the processing unit <NUM> determines a first standard deviation σ n-<NUM> in amplitude as a function of range based on the respective amplitude determined for each of the first plurality of frames. In computing the first standard deviation, the processing unit computes a mean amplitude. The processing unit <NUM> sets and stores, at <NUM>, a previous mean amplitude µn-<NUM> to a value equal to a mean amplitude µn-<NUM> for the first plurality of frames.

Then, at <NUM>, the processing unit <NUM> directs the transceiver <NUM> to detect living objects by generating a subsequent frame n using the same chirp pattern used at <NUM>. The processing unit <NUM> applies a Fourier transform to radar reflections obtained during the subsequent frame to determine an amplitude as a function of range of the receiver signal for the subsequent frame.

The processing unit <NUM> determines a current mean µn equal to the previous mean µn-<NUM> incremented by a fraction of the amplitude xn for the subsequent frame n, per the Equation <NUM>. The fraction of the amplitude xn of the subsequent frame n is equal to a difference between the amplitude xn of the subsequent frame n and the previous mean µn-<NUM>, the difference being divided by a total quantity of frames n among the plurality of frames <NUM> through n.

A standard deviation σn of the plurality of frames and the subsequent frame is determined by incrementing the standard deviation σn-<NUM> by a function of the range xn of the subsequent frame n, the previous mean µn-<NUM>, and the current mean µn. For example, the function of the range xn of the subsequent frame n, the previous mean µn-<NUM>, and the current mean µn is based on a product of the amplitude of the subsequent frame minus the previous mean and the amplitude of the subsequent frame minus the current mean (see the Equation <NUM> which controls the results of the Equation <NUM>).

At <NUM>, the radar system determines whether the standard deviation in the amplitude σn satisfies a noise threshold. Responsive to the standard deviation σn-<NUM> satisfying a noise threshold at <NUM>, the processing unit <NUM> outputs, at <NUM>, an indication of a living object <NUM> detected during the plurality of frames <NUM> through n. Otherwise, in response to the standard deviation σn-<NUM> not satisfying the noise threshold at <NUM>, the processing unit <NUM> returns to the operation <NUM> for generating additional frames to detect a living object <NUM>.

Each time the radar system <NUM> computes a current mean µn the radar system <NUM> later stores the current mean µn as the previous mean µn to be used during calculation of a subsequent mean µn+<NUM>. For example, the living-object detector <NUM> uses the previous mean µn-<NUM> to determine a current mean µn and stores the current mean µn as the previous mean µn-<NUM> in a memory of the computer-readable storage media <NUM> or storage media otherwise accessible to the processing unit <NUM>.

The operations <NUM> and <NUM> may be repeated until a living object <NUM> is detected, or based on some other criteria (e.g., quantity of frames, duration of time). For example, after generating another plurality of frames (n + <NUM>), the processing unit <NUM> determines the current mean µn+<NUM>. The current mean µn+<NUM> is equal to the previous mean µn incremented by a fraction of an amplitude xn+<NUM> of a current plurality of frames as a function of range. The fraction of the amplitude xn+<NUM> is equal to a difference between the amplitude xn+<NUM> of the new frame and the previous mean µn, the difference being divided by a total quantity (n + <NUM>) of frames.

A standard deviation σn+<NUM> of the plurality of frames (n + <NUM>) is determined by incrementing the standard deviation σn by a function of the amplitude xn+<NUM> of the plurality of frames n+<NUM>, the previous mean µn, and the current mean µn+<NUM>. At <NUM>, the radar system determines whether the standard deviation σn+<NUM> satisfies the noise threshold, which may be an adaptive threshold. Responsive to the standard deviation σn+<NUM> satisfying the noise threshold at <NUM>, the processing unit <NUM> outputs, at <NUM>, an indication of the living object <NUM> detected during the plurality of frames <NUM> through n + <NUM>.

Otherwise, in response to the standard deviation σn+<NUM> not satisfying the noise threshold at <NUM>, the processing unit <NUM> stores the current mean µn+<NUM> as the previous mean µn+<NUM> and returns to the operation <NUM> for generating additional frames to detect a living object <NUM>. In response to the standard deviation σn+<NUM> not satisfying the noise threshold at <NUM>, the processing unit <NUM> refrains from outputting an indication of a living object.

<FIG> illustrate an example of power drift in an FMCW radar system. For responsive and quick detection of living targets, the radar system <NUM> processes radar data as soon as the radar system <NUM> powers on. However, it is common that the components of the radar system <NUM> (e.g., which may be made of Silicon) need a period of time after the radar system <NUM> powers on, before the components are stable. An example of power drift is shown in the sequence of <FIG>. The radar system <NUM> takes more than four minutes, for example, to report a correct and stable amplitude x of radar reflections as a function of range. Power drifting may introduce a false trigger to a detection of a living target by introducing errors in the calculation of the standard deviation σ.

The radar system <NUM> may prevent false triggers to detections by correcting for a slope k of the power drifting. Where xn is the last sample and x<NUM> is the first sample, the radar system <NUM> obtains the slope k of the samples by calculating Equation <NUM> as follows: <MAT> To determine the standard deviation σ and/or the mean µn amplitude as a function of range, the radar system <NUM> compensates for false triggers to detections, based on the slope k of the samples x. To improve performance, the radar system <NUM> may incrementally compensate for the false triggers to detections resulting from the power drift.

<FIG> illustrates an example adaptive threshold during part of a frame generated by an FMCW radar system that corrects for power drift. <FIG> shows the effects of drift correction on an original signal; the false peak is substantially reduced after using drift correction. The original signal can represent a return from a living object. Similarly, an adaptive threshold that follows the noise response of the radar system <NUM> can benefit from drift correction to make the living object <NUM> readily detectable.

To put the slope correction into the incremental mean and standard deviation calculations of the Equations <NUM> and <NUM>, a new mean mn is defined in Equations <NUM> through <NUM>: <MAT> <MAT> <MAT> <MAT>.

Because both µn and In can be calculated incrementally, mn can also been calculated incrementally. Adding slope correction into the Equations <NUM> and <NUM> produces an Equation <NUM> for computing a new variance v with slope correction: <MAT>.

The Equation <NUM> can be reduced to Equations <NUM> through <NUM>. Based on the Equations <NUM> through <NUM>, the Equation <NUM> for the new variance v can be rewritten into Equation <NUM>, which enables incremental computation of the standard deviation σ including compensating for power drift. <MAT> <MAT>
<MAT>
<MAT> <MAT> <MAT> Because Sn, An, Bn, In, and µn can be calculated incrementally, the Equation <NUM> and the new variance v<NUM> can also be calculated incrementally. Computing the standard deviation from computing variance in this way significantly reduces memory requirements. With incremental calculation and slope correction, the radar system <NUM> detects living targets without potential for overflow or false triggers to detections.

Claim 1:
A frequency-modulated continuous-wave radar system (<NUM>) comprising:
an antenna array (<NUM>);
a transceiver (<NUM>) configured to generate radar signals (<NUM>) via the antenna array (<NUM>); and
a processing unit (<NUM>) configured to:
direct the transceiver (<NUM>) to generate, for a plurality of frames (<NUM>), the radar signals (<NUM>) having a chirp pattern that has a first period of multiple chirps (<NUM>) followed by a second period of idle time;
apply a Fourier transform to respective reflections of the radar signals (<NUM>) obtained during each of the plurality of frames (<NUM>) to determine a respective amplitude of the reflections as a function of range for each of the plurality of frames (<NUM>);
based on the respective amplitude of the reflections for each of the plurality of frames (<NUM>), determine a standard deviation (<NUM>) in the respective amplitude for the reflections within each of the plurality of frames (<NUM>); and
in response to the standard deviation (<NUM>) in the respective amplitude for any of the reflections within the plurality of frames (<NUM>) satisfying a noise threshold, output, an indication of a living object (<NUM>) detected during the plurality of frames (<NUM>)
characterized in that
the second period of idle time is longer than the first period of multiple chirps (<NUM>).