Radar leakage measurement update

Abstract

This disclosure relates to quasi-fifth-generation (5G) or 5G communication systems to be provided for supporting higher data rates than fourth-generation (4G) communication systems such as Long Term Evolution (LTE). A method and electronic device for updating a leakage response for leakage elimination are also disclosed. The electronic device includes a radar transceiver, a memory, and a processor. The processor is configured to: determine whether an object is present in the vicinity of the radar transceiver and within the radar transceiver's field of view; in response to determining that no object is approaching the radar transceiver and within the radar transceiver's field of view; obtain a leakage measurement of the radar transceiver; and update the leakage response for leakage elimination based on the leakage measurement.

Description

Technical Field

[0001] This disclosure generally relates to resolving signal leakage in radar applications. More specifically, this disclosure relates to the timely updating of radar leakage measurements for radar transceivers. Background Technology

[0002] To meet the increased demand for wireless data services since the deployment of 4G communication systems, efforts have been made to develop improved 5G or near-5G communication systems. Therefore, 5G or near-5G communication systems are also referred to as "super 4G networks" or "post-LTE systems".

[0003] 5G communication systems are considered to be implemented in higher frequency (millimeter wave) bands (e.g., the 60 GHz band) to achieve higher data rates. To reduce radio wave propagation loss and increase transmission distance, beamforming, massive MIMO, full-dimensional MIMO (FD-MIMO), array antennas, analog beamforming, and massive MIMO technologies are discussed in 5G communication systems.

[0004] In addition, in 5G communication systems, development is underway to improve system networks based on advanced small cells, cloud radio access networks (RAN) ultra-dense networks, device-to-device (D2D) communication, wireless backhaul, mobile networks, cooperative communication, cooperative multipoint (CoMP), and receiver interference cancellation.

[0005] In 5G systems, hybrid FSK and QAM modulation (FQAM) and sliding window superposition coding (SWSC) have been developed as advanced coding modulation (ACM), as well as filter bank multicarrier (FBMC), non-orthogonal multiple access (NOMA) and sparse code multiple access (SCMA) as advanced access technologies.

[0006] Radars can operate in various frequency bands (including but not limited to 6-8 GHz, 28 GHz, 39 GHz, 60 GHz, and 77 GHz). Radar operation is used to locate targets within the radar's field of view in terms of azimuth (range) and / or elevation (angle) and / or velocity. For monostation radars, the transmitter and receiver are tightly mounted together, resulting in leakage signals being transmitted directly from the transmitter to the receiver. Leakage signals interfere with radar detection and ranging. Strong leakage signals can interfere with signals returned from the target, which can mask the target, thus hindering detection and / or causing inaccurate range estimation. Summary of the Invention

[0007] Technical issues

[0008] Leakage signals interfere with radar detection and ranging. Strong leakage signals can interfere with signals returned from the target, which can mask the target and thus hinder detection and / or make range estimation inaccurate.

[0009] Technical solution

[0010] Embodiments of this disclosure include a method for leak elimination, electronic devices, and a non-transitory computer-readable medium. In one embodiment, the electronic device includes a radar transceiver, a memory, and a processor. The processor is configured to determine whether an object is in the vicinity of the radar transceiver and within the radar transceiver's field of view; in response to determining that no object is approaching the radar transceiver and within the radar transceiver's field of view; obtain a leak measurement of the radar transceiver; and update a leak response for leak elimination based on the leak measurement.

[0011] In another embodiment, a method for eliminating a leak includes: determining, by an electronic device having a radar transceiver, whether there is an object in the vicinity of the radar transceiver and within the field of view of the radar transceiver; in response to determining that no object is approaching the radar transceiver and within the field of view of the radar transceiver, obtaining a leak measurement of the radar transceiver; and updating a leak response for leak elimination based on the leak measurement.

[0012] In another embodiment, an electronic device includes a non-transitory computer-readable medium. The non-transitory computer-readable medium stores instructions, when executed by the processor, to cause the processor to: determine whether an object is in the vicinity of the radar transceiver and within the radar transceiver's field of view; in response to determining that no object is approaching the radar transceiver and within its field of view, obtain a leakage measurement of the radar transceiver; and update a leakage response for leakage elimination based on the leakage measurement.

[0013] Other technical features will be obvious to those skilled in the art based on the accompanying drawings, description and claims.

[0014] Before proceeding with the detailed description below, it may be advantageous to define certain words and phrases used throughout this disclosure. The term “coupled” and its derivatives refer to any direct or indirect communication between two or more elements, whether or not these elements are physically in contact with each other. The terms “transmit,” “receive,” and “communicate,” and their derivatives, cover both direct and indirect communication. The terms “comprise” and “include,” and their derivatives, mean including but not limited to. The term “or” is inclusive, meaning “and / or.” The phrase “associated with” and its derivatives mean including, being included in, interconnected with, containing, being contained within, connected to or connected with, coupled to or coupled with, able to communicate with, cooperate with, interleaved, juxtaposed, proximate, bound to or bound with, having, possessing the properties of, having a relationship with, or having a relationship with, etc. When used with a list of items, the phrase “at least one of” means that different combinations of one or more of the listed items may be used, and that only one item from the list may be required. For example, "at least one of A, B, and C" includes any of the following combinations: A, B, C, A and B, A and C, B and C, and A and B and C. Similarly, the term "group" means one or more. Therefore, a group of items can be a single item or a collection of two or more items.

[0015] Furthermore, the various functions described below can be implemented or supported by one or more computer programs, each of which is formed by computer-readable program code and embodied in a computer-readable medium. The terms "application" and "program" refer to one or more computer programs, software components, instruction sets, procedures, functions, objects, classes, instances, associated data, or portions thereof suitable for implementation in appropriate computer-readable program code. The phrase "computer-readable program code" includes any type of computer code, including source code, object code, and executable code. The phrase "computer-readable medium" includes any type of medium accessible by a computer, such as read-only memory (ROM), random access memory (RAM), hard disk drive, compact disc (CD), digital video disc (DVD), or any other type of storage. "Non-transitory" computer-readable media does not include wired, wireless, optical, or other communication links that transmit transient electrical or other signals. Non-transitory computer-readable media includes media that can permanently store data and media that can store data and later rewrite it, such as rewritable optical discs or erasable memory devices.

[0016] Definitions of certain other words and phrases are provided throughout this disclosure. Those skilled in the art will understand that, in many cases (if not most), such definitions apply to the prior and future use of the words and phrases defined in this way.

[0017] Beneficial effects

[0018] This disclosure generally relates to solving signal leakage in radar applications. Attached Figure Description

[0019] To gain a more complete understanding of this disclosure and its advantages, reference is now made to the following description in conjunction with the accompanying drawings, wherein like reference numerals denote like parts:

[0020] Figure 1 Electronic devices according to various embodiments of the present disclosure are shown;

[0021] Figure 2 Monostation radars according to various embodiments of the present disclosure are shown;

[0022] Figure 3 Examples of channel impulse response (CIR) according to various embodiments of this disclosure are shown;

[0023] Figure 4 Timing diagrams for radar transmission according to various embodiments of the present disclosure are shown;

[0024] Figure 5 Flowcharts for leak elimination according to various embodiments of the present disclosure are shown;

[0025] Figure 6 A flowchart illustrating steps for timely updating leak measurements according to various embodiments of the present disclosure is shown;

[0026] Figure 7 A flowchart illustrating steps for determining the validity of a leak measurement according to various embodiments of the present disclosure is shown;

[0027] Figure 8 A flowchart illustrating the determination of the validity of a leakage measurement with reference to time as a state variable, according to various embodiments of the present disclosure, is shown.

[0028] Figure 9 A flowchart illustrating the effectiveness of a leak measurement using reference temperature and humidity as state variables, according to various embodiments of the present disclosure, is shown.

[0029] Figure 10 A flowchart illustrating a leak measurement update decision for a radar-based application is shown according to various embodiments of the present disclosure;

[0030] Figure 11 A flowchart is shown for updating a leak measurement decision for radar-based presence detection, according to various embodiments of the present disclosure;

[0031] Figure 12A flowchart illustrating radar-based range estimation using an updated leak response, according to various embodiments of the present disclosure, is shown.

[0032] Figure 13 A flowchart is shown for updating a decision on leaked measurements for radar-based facial authentication, according to various embodiments of the present disclosure;

[0033] Figure 14 The following illustrations depict user interaction with electronic devices for radar-based facial authentication according to various embodiments of the present disclosure.

[0034] Figure 15 A flowchart is shown for updating decisions based on leak measurements of radar-based emotion or heartbeat monitoring, according to various embodiments of this disclosure;

[0035] Figure 16 A flowchart is shown for a leak measurement update decision for an application using non-radar sensors and radar transceivers, according to various embodiments of the present disclosure;

[0036] Figure 17 A general flowchart for leak measurement update decisions for non-radar applications is shown according to various embodiments of the present disclosure;

[0037] Figure 18 A flowchart is shown for a leak measurement update decision for non-radar applications using sensors, according to various embodiments of the present disclosure;

[0038] Figure 19 A flowchart is shown illustrating a process for updating a leak measurement decision for vision-based facial authentication in non-radar applications, according to various embodiments of the present disclosure.

[0039] Figure 20 A flowchart is shown illustrating a process for updating a decision on leakage measurement of a proximity sensor in a non-radar application, according to various embodiments of the present disclosure.

[0040] Figure 21 Flowcharts illustrating various embodiments of the present disclosure for integrating confidence levels into leak measurement update decisions are shown;

[0041] Figure 22 Flowcharts illustrating various embodiments of the present disclosure for integrating confidence level decisions into leak measurement update decisions are shown;

[0042] Figure 23 A flowchart is shown illustrating a process for making leak measurement update decisions for a voice or video call application according to various embodiments of the present disclosure;

[0043] Figure 24A flowchart illustrating a process for making alternative leakage measurement update decisions for voice or video call applications according to various embodiments of this disclosure is shown; and

[0044] Figure 25 A flowchart is shown illustrating a process for timely updating a leak response according to various embodiments of the present disclosure. Detailed Implementation

[0045] The accompanying drawings and various embodiments included herein, used to describe the principles of this disclosure, are merely illustrative and should not be construed in any way as limiting the scope of this disclosure. Those skilled in the art will understand that the principles of this disclosure can be implemented in any suitably arranged communication system, whether wired or wireless.

[0046] Figure 1 Electronic devices according to various embodiments of the present disclosure are shown. Figure 1 The embodiment of the electronic device 100 shown is for illustrative purposes only. Other embodiments may be used without departing from the scope of this disclosure.

[0047] like Figure 1 As shown, electronic device 100 includes a radio frequency (RF) transceiver 110, transmit (TX) processing circuitry 115, a microphone 120, receive (RX) processing circuitry 125, a speaker 130, a processor 140, an input / output (I / O) interface 145, a memory 160, a display 165, an input 170, and a sensor 175. Non-limiting examples of the sensor 175 include inertial sensors, proximity sensors, infrared sensors, ultrasonic sensors, laser sensors, and capacitive sensors that can provide contextual operational data that can be used to update the leak response in a timely manner. The memory 160 includes an operating system (OS) 162 and one or more applications 164. The one or more applications 164 can be Type 1 or Type 2 applications that can be used to provide additional contextual operational data that can also be used to update the leak response in a timely manner.

[0048] Transceiver 110 sends signals to other components in the system and receives incoming signals sent by other components in the system. For example, transceiver 110 sends RF signals such as Bluetooth or Wi-Fi signals to access points (such as base stations, Wi-Fi routers, Bluetooth devices) of a network (such as Wi-Fi, Bluetooth, cellular, 5G, LTE, LTE-A, WiMAX, or any other type of wireless network) and receives RF signals such as Bluetooth or Wi-Fi signals from access points (such as base stations, Wi-Fi routers, Bluetooth devices) of the network (such as Wi-Fi, Bluetooth, cellular, 5G, LTE, LTE-A, WiMAX, or any other type of wireless network). The received signals are processed by RX processing circuitry 125. RX processing circuitry 125 can send the processed signals to speaker 130 (such as for voice data) or to processor 140 for further processing (such as for web browsing data). TX processing circuitry 115 receives voice data from microphone 120 or other outgoing data from processor 140. Outgoing data may include web data, email, or interactive video game data. The TX processing circuit 115 processes the outgoing data to generate a processed signal. The transceiver 110 receives the processed signal from the TX processing circuit 115 and converts the received signal into an RF signal to be transmitted via an antenna. In other embodiments, the transceiver 110 may transmit and receive radar signals to detect potentially present objects in the environment surrounding the electronic device 100.

[0049] In this embodiment, one of the transceivers 110 is a radar transceiver 150, configured to transmit and receive signals for detection and ranging purposes. For example, the radar transceiver 150 can be any type of transceiver, including but not limited to WiFi transceivers such as 802.11ay transceivers. The radar transceiver 150 includes an antenna array 155 comprising an antenna array of a transmitter 157 and a receiver 159. In some embodiments, the signals transmitted by the radar transceiver 150 may include, but are not limited to, millimeter-wave (mmWave) signals. The radar transceiver 150 can receive the signal initially transmitted from the radar transceiver 150 after it has bounced or reflected from a target object in the environment surrounding the electronic device 100. The processor 140 can analyze the time difference between the signal transmitted by the radar transceiver 150 and the signal received by the radar transceiver 150 to measure the distance of the target object from the electronic device 100.

[0050] Transmitter 157 and receiver 159 can be tightly fixed to each other, such that the distance between them is small. For example, transmitter 157 and receiver 159 can be located within a few centimeters of each other. In some embodiments, transmitter 157 and receiver 159 can be co-located in a way that makes the distance between them indistinguishable. Based on contextual information that can be obtained from other applications executing on electronic device 100, processor 140 executes instructions to cause the electronic device to update leakage measurements for transmitter 157 and receiver 159 in a timely manner, which can be used to eliminate leakage signals transmitted from transmitter 157 to receiver 159. Leakage measurements can be performed by, for example, Figure 3 The CIR designation is described in more detail below.

[0051] TX processing circuitry 115 receives analog or digital voice data from microphone 120, or other outgoing baseband data (such as web data, email, or interactive video game data) from processor 140. TX processing circuitry 115 encodes, multiplexes, and / or digitizes the outgoing baseband data to generate a processed baseband or intermediate frequency (IF) signal. Transceiver 110 receives the outgoing processed baseband or IF signal from TX processing circuitry 115 and up-converts the baseband or IF signal into an RF signal transmitted via antenna 105.

[0052] Processor 140 is also capable of executing operating system 162 in memory 160 to control the overall operation of electronic device 100. For example, processor 140 can move data into or out of memory 160 as needed for the execution process. In some embodiments, processor 140 is configured to execute application 164 based on OS program 162 or in response to signals received from external devices or operators. In some embodiments, memory 160 is also configured to store data, such as leakage responses for leakage elimination, which processor 140 can use to enable various components of the electronic device to perform leakage elimination individually or collaboratively. In some embodiments, processor 140 can control transceiver 110, RX processing circuitry 125, and TX processing circuitry 115 to receive forward channel signals and transmit reverse channel signals according to known principles. In some embodiments, processor 140 includes at least one microprocessor or microcontroller.

[0053] The processor 140 is also coupled to an I / O interface 145, a display 165, inputs 170, and sensors 175. The I / O interface 145 provides the electronic device 100 with the ability to connect to other devices such as laptops and handheld computers. The I / O interface 145 is the communication path between these accessories and the processor 140. The display 165 may be a liquid crystal display (LCD), a light-emitting diode (LED) display, an organic LED (OLED), an active-matrix OLED (AMOLED), or other displays capable of displaying text and / or graphics such as those from websites, videos, games, images, etc.

[0054] Processor 140 may be coupled to input 170. An operator of electronic device 100 may use input 170 to input data or other information into electronic device 100. Input 170 may be a keyboard, touchscreen, mouse, trackball, voice input, or any other device capable of serving as a user interface allowing the user to interact with electronic device 100. For example, input 150 may include voice recognition processing, thereby allowing the user to input voice commands via microphone 120. As another example, input 150 may include a touch panel, (digital) pen sensor, key, or ultrasonic input device. Touch panel may recognize touch input using at least one of capacitive, pressure-sensitive, infrared, or ultrasonic methods.

[0055] The electronic device 100 may also include one or more sensors 175 that measure physical quantities or detect the activation state of the electronic device 100 and convert the measured or detected information into electrical signals. For example, sensors 175 may include one or more buttons for touch input, one or more cameras, gesture sensors, eye-tracking sensors, gyroscopes or gyro sensors, barometric pressure sensors, magnetic sensors or magnetometers, accelerometers or accelerometers, grip sensors, proximity sensors, color sensors, biophysical sensors, temperature / humidity sensors, illuminance sensors, ultraviolet (UV) sensors, electromyography (EMG) sensors, electroencephalography (EEG) sensors, electrocardiography (ECG) sensors, infrared (IR) sensors, ultrasound sensors, fingerprint sensors, etc. Sensors 175 may also include control circuitry for controlling at least one of the sensors included therein.

[0056] In various embodiments, electronic device 100 may be a telephone or a tablet computer. In other embodiments, electronic device 100 may be a robot or any other electronic device using a radar transceiver. Figure 1 This disclosure is not intended to be limited to any particular type of electronic device.

[0057] Figure 2 A monostation radar according to various embodiments of the present disclosure is shown. Figure 2The embodiment of the monostation radar 200 shown is for illustrative purposes only, and other embodiments may be used without departing from the scope of this disclosure. Figure 2 The monostation radar 200 shown includes a processor 210, a transmitter 220, and a receiver 230. In some embodiments, the processor 210 may be a processor 140.

[0058] In some embodiments, transmitter 220 and receiver 230 may be radar transceiver 150 and are respectively connected to transmitter 157 and receiver 159 antenna arrays included in antenna array 155. In various embodiments, transmitter 220 and receiver 230 are co-located using a common antenna, or nearly co-located while using separate but adjacent antennas. It is assumed that the monostation radar 200 is coherent, such that transmitter 220 and receiver 230 are synchronized via a common time reference.

[0059] Processor 210 controls transmitter 220 to transmit radar signals or radar pulses. The radar pulses are generated to achieve a desired "radar waveform," which is modulated onto a radio carrier frequency and transmitted omnidirectionally or focused in a specific direction via a power amplifier and antenna (shown as a parabolic antenna) such as transmitter 220. After the radar pulse is transmitted, a target 240 at a distance R from radar 200 and within the field of view of the transmitted pulse will be transmitted at an RF power density for the duration of the transmission. (in W / m) 2 (units) are irradiated. For first order, Described by Equation 1:

[0060]

[0061] in, P T It is the transmission power [W]. It is the transmit antenna gain [dBi]. It is the effective pore area [m2]. R is the wavelength [m] of the radar signal RF carrier signal, and R is the target distance [m].

[0062] The transmitted power density impacting the target surface causes reflection due to material composition, surface shape, and dielectric behavior at the radar signal frequency. Off-direction scattered signals are generally insufficient to be recovered at receiver 230, therefore only direct reflection contributes to the detectable received signal. Thus, one or more illumination areas of the target with normal vectors pointing back to receiver 230 are used as transmitting antenna apertures with directivity or gain, depending on their effective aperture area. Reflected power Described by Equation 2:

[0063]

[0064] in, It is the effective (isotropic) target reflection power [W]. It is the effective target area perpendicular to the radar direction [m 2 ], It refers to the material's reflectivity and shape [0,...,1]. This corresponds to the aperture gain [dBi], and RCS is the radar cross-section [m]. 2 ].

[0065] As shown in Equation 2, the radar cross section (RCS) is an equivalent area scaled proportionally to the square of the actual reflective area, inversely proportional to the square of the wavelength, and decreases depending on various shape factors and the reflectivity of the material itself. For example, for a wavelength with l 2 Compared to a large flat, perfectly reflective mirror area , Due to material and shape dependence, even if the distance R from the target to radar 200 is known, it is difficult to infer the actual physical area of ​​target 240 based on reflection power.

[0066] The target reflected power at the location of receiver 230 is based on the reflected power density collected at a reverse distance R in the receiver antenna aperture region. The received target reflected power. Described by Equation 3:

[0067]

[0068] in, It is the received target reflected power [W], and This is the effective aperture area of ​​the receiver antenna [m2]. In some embodiments, Can be with same.

[0069] This radar system is usable as long as the receiver signal exhibits a sufficient signal-to-noise ratio (SNR). The specific value of SNR depends on the waveform used and the detection method. SNR is described by Equation 4:

[0070]

[0071] in, It is Boltzmann constant × temperature [W / Hz], B is radar signal bandwidth [Hz], and F is receiver noise factor, which refers to the degradation of the received signal SNR caused by the noise contribution to the receiver circuit itself.

[0072] In some embodiments, the radar signal may be a signal consisting of... The duration or width of the pulse is indicated. In these embodiments, the delay t between transmission and the reception of the corresponding echo will be equal to... Where c is the speed of light propagation in a medium (such as air). In some embodiments, multiple targets 240 may exist at slightly different distances R. In these embodiments, the individual echoes of each individual target 240 are distinguished only if the delays differ by at least one pulse width, and the radar range resolution is described as... Duration The rectangular pulse exhibits power spectral density The first zero point is in its bandwidth. Therefore, the relationship between the radar's range resolution and the radar waveform bandwidth is described by Equation 5:

[0073]

[0074] Based on the reflected signal received by receiver 230, processor 210 generates a metric that measures the response of the reflected signal as a function of the distance of target 240 from radar. In some embodiments, the metric may be CIR.

[0075] Figure 3 Examples of CIR measurements depicting leakage response according to various embodiments of this disclosure are shown. CIR is a response metric based on the signal received by receiver 230. For example, CIR is a measure of the amplitude and / or phase of the reflected signal as a function of distance. Figure 3 As shown, CIR is depicted as a delay tap index representing the measured distance on the x-axis and the amplitude [dB] of the radar measurement on the y-axis. In a monostatic radar (e.g., radar 200) with separate transmit and receive antenna modules, a strong signal can be radiated directly from transmitter 220 to receiver 230, causing a strong response at a delay corresponding to the interval between transmitter 220 and receiver 230. The strong signal radiated from transmitter 220 to receiver 230 is referred to as the leakage signal. Even if it can be assumed that the direct leakage signal from transmitter 220 corresponds to a single delay, the effect of the direct leakage signal can still affect multiple delay taps adjacent to the direct leakage signal.

[0076] exist Figure 3 In the measured leakage response shown, the main leakage peak is represented at tap 11. Furthermore, taps 10 and 12 also exhibit strong responses, noting that these responses are greater than 20 dB above the noise floor. Due to the additional responses such as those shown at taps 10 and 12, it is difficult to reliably detect and estimate the target distance within those first few taps from the leakage taps.

[0077] Figure 4Timing diagrams for radar transmission according to various embodiments of the present disclosure are shown. Specifically, Figure 4 The diagram illustrates a frame structure that divides time into frames, with each frame comprising multiple pulse trains. Each pulse train consists of multiple pulses. Figure 4 The timing diagram shown assumes a basic pulse compression radar system.

[0078] like Figure 4 As shown, each frame includes N pulse trains, such as pulse train 1, pulse train 2, pulse train 3, up to pulse train N. Each pulse train is formed by multiple pulses. For example, Figure 4 The pulse train 1 is shown to include multiple pulses labeled as pulse 1, pulse 2, and so on up to pulse M.

[0079] For example, in pulse train 1, a radar transceiver such as transmitter 157 can transmit pulse 1, pulse 2, and pulse M. In pulse train 2, transmitter 157 can transmit similar pulses, pulse 1, pulse 2, and pulse M. Each different pulse (pulse 1, pulse 2, and pulse M) and pulse train (pulse train 1, pulse train 2, pulse train 3, etc.) can be identified using different transmit / receive antenna configurations, where the transmit / receive antenna configuration is the effective set of antenna elements and the corresponding analog / digital beamforming weights. For example, each pulse or pulse train can be identified using different effective sets of antenna elements and corresponding analog / digital beamforming weights.

[0080] After each frame, a processor (e.g., processor 140) connected to transmitter 157 obtains radar measurements at the end of each frame. For example, the radar measurements can be depicted as a three-dimensional complex CIR matrix. The first dimension may correspond to the burst index, the second dimension to the pulse index, and the third dimension to the delay tap index. The delay tap index can be converted into a measurement of the distance or time of flight of the received signal.

[0081] Leakage signals from the radar transmitter to the radar receiver can impair the radar's target detection and range estimation capabilities, particularly for objects within the vicinity of the radar transceiver and within its field of view. In some exemplary embodiments, an object is considered to be within the vicinity of the radar transceiver and within its field of view when it is less than approximately 20 cm away. In a more specific embodiment, an object is considered to be within the vicinity of the radar transceiver and within its field of view when it is less than approximately 10 cm away.

[0082] Eliminating leakage signals can overcome this problem. Leakage signals of predicted quantities stored on electronic devices (such as memory 160 of electronic device 100) can be used to eliminate leakage signals from radar measurements. This method is feasible because leakage signals propagate through a strictly defined path determined by the device hardware, which can be assumed to be constant over a relatively long period under similar environmental conditions. Occasional updates to the stored leakage measurements can ensure the accuracy of radar-based sensing. To avoid the inconvenience or unnecessarily discontinuous use of resources to update leakage measurements, novel aspects of the various embodiments disclosed herein relate to updating stored leakage measurements as needed and / or as appropriate when possible. For example, recently acquired stored leakage measurements may not need to be updated and can therefore be considered valid. If a stored leakage measurement is no longer valid, it can only be updated when possible. For example, if an object is in the vicinity of the radar transceiver and within the radar transceiver's field of view, the stored leakage measurement cannot be updated.

[0083] Various embodiments of this disclosure involve using contextual information from various applications running on an electronic device to determine whether a stored leakage measurement is still valid, and if not, when the stored leakage measurement can be updated. Regardless of whether the application being executed directly utilizes radar measurements, successful operation of these applications typically depends on the absence of objects in the vicinity of the radar transceiver and within the radar transceiver's field of view. An exemplary application, which will be explained in more detail in the accompanying drawings below, relates to radar-based facial authentication. In this case, for successful operation, there must be no obstruction between the radar antenna module and the user's face, typically at a distance between 20 cm and 50 cm. The latest leakage measurement can be extracted from radar measurements that have already produced the desired result (e.g., successful authentication). The extracted leakage measurement can be used to update the leakage response of the radar transceiver in the electronic device by canceling the leakage signal of the radar measurement. The updated leakage response can then be used for reliable target detection and accurate ranging, particularly in the vicinity of the radar transceiver and within its field of view.

[0084] Figure 5 A flowchart illustrating general operations for leak elimination according to various embodiments of the present disclosure is shown. Processor (such as...) Figure 1The processor 140 of the electronic device 100 can execute instructions to cause the electronic device to undergo operations described in flowchart 500 for eliminating the effects of leakage signals transmitted directly from the transmitter to the receiver. For example, the radar measurement performed in operation 502 includes a leakage signal that can be eliminated in operation 506 by a stored leakage measurement obtained from operation 504. The stored leakage measurement is data describing the signal strength of a set of leakage signals relative to a delay tap index, which can be attributed to leakage signals transmitted directly from the transmitter to the receiver of the radar transceiver. The stored leakage measurement can be performed in... Figure 3 As shown in the CIR diagram. Target detection and range estimation can be achieved using radar measurements after leakage elimination in operation 508.

[0085] Figure 5 Stored leak measurements can be associated with one or more state variables, such as timestamps describing the conditions under which the stored leak measurements were obtained, temperature, or humidity. Each of these state variables can be further divided into one or more categories or ranges. For example, leak measurements can be stored for each temperature category (such as high, medium, low, or the temperature can be divided into multiple intervals of size N degrees). Leak measurements can then be updated separately for each temperature category. Furthermore, when stored measurements are used for radar detection and leak estimation, the temperature at which the radar measurement was performed can be used to select the appropriate stored leak measurement for leak removal. Other types of information can also be used in a similar manner. For example, humidity is another factor that can affect the behavior of the device's circuitry and therefore leak behavior, and it can be used as part of the description of the operating environment.

[0086] Figure 6 A flowchart illustrating operations for timely updating leak measurements according to a non-limiting embodiment of this disclosure is shown. Processor (such as...) Figure 1 The processor 140 of the electronic device 100 can execute instructions to cause the electronic device to undergo the operations described in flowchart 600 to determine the validity of the stored leakage measurements and update the stored leakage measurements when necessary and possible.

[0087] In operation 602, the state of the electronic device is identified. The state of the device is based on one or more state variables, examples of which may include time, temperature, and humidity. Based on the state of the device, the validity of the stored leakage measurement can be determined in operation 604. Figures 7-9 The flowcharts and related embodiments depicted illustrate some non-limiting examples of the effectiveness of determining storage leakage measurements based on state variables.

[0088] If the stored leak measurement is still valid, it is not updated in operation 606. Otherwise, if, as determined in operation 604, the stored leak measurement is no longer valid, a determination is made in operation 608 regarding whether the stored leak measurement can be updated. If the stored leak measurement cannot be updated, flowchart 600 proceeds to operation 610, or if the stored leak measurement can be updated, flowchart 600 proceeds to operation 612.

[0089] Different methods exist for updating stored leak measurements in operation 612. For example, a simple method is to replace stored leak measurements with newly acquired leak measurements. Another method involves averaging, either a simple average of all past valid leak measurements or a weighted average. In one embodiment, a weighted average may include all historical leak measurements, and in another embodiment, the weighted average spans only a specific time window to include only a subset of historical leak measurements. Another weighted averaging method can use the timestamps of the leak measurements to determine the age of the measurements and perform an average weighted by the freshness of the measurements (e.g., giving more weight to more recent leak measurements). Note that if leak measurements are stored for different types of categories of radar operating environments (e.g., defined by state variables such as temperature and / or humidity), the averaging methods described so far can be used separately for measurements belonging to each operating environment category.

[0090] Figure 7 A flowchart illustrating steps for determining the validity of a storage leakage measurement according to various embodiments of the present disclosure is shown. In operation 706, the classifier can be based on the storage state variable (S) of the storage leakage measurement from operation 702. lk ) and the current state variables (S) from the electronic device operating 704. cu To determine whether a leak update is needed (i.e., to make a validity determination), the stored state variable can be maintained in memory 160 and compared with a corresponding state variable determined by one or more sensors 175 and / or applications 164. Based on the result of the determination made in operation 706, if the stored leak measurement is invalid, flowchart 700 proceeds to operation 708, or if the stored leak measurement is still valid, flowchart 700 proceeds to operation 710.

[0091] Figure 8 A flowchart illustrating the determination of the validity of a leakage measurement with reference to time as a state variable, according to various embodiments of this disclosure, is shown. The processor can use a stored timestamp (t) of the stored leakage measurement from operation 802 in operation 806. lk ) and the current timestamp (t) from operation 804 cuThe processor determines the validity of the stored state variable. The stored state variable can be maintained in memory 160 and compared with a corresponding state variable determined by one or more applications 164 capable of providing the current timestamp. For example, in operation 806, the processor can determine whether the difference between the stored timestamp and the current timestamp exceeds a predefined threshold. If the difference exceeds the predefined threshold, the stored leakage measurement is considered invalid in operation 808, or valid in operation 810.

[0092] Figure 9 A flowchart illustrating the determination of the validity of a leak measurement with reference to temperature and humidity as state variables, according to various embodiments of the present disclosure, is shown. In operation 910, the processor can determine the validity of a leak measurement based on the temperature (T) of the leak measurement stored from operation 902. lk ) and the current temperature (T) from the electronic device operating 908 cu The comparison of humidity (H) with that of storage leaks from Operation 904, and / or the measurement of humidity (H) from storage leaks. lk ) and the current humidity (H) from the electronic device operating 906 cu The validity of the state variable is determined by comparison with the corresponding state variable determined by one or more sensors 175 that are capable of providing the current temperature and / or humidity.

[0093] exist Figure 9 In the non-limiting embodiment shown, if the current temperature (T) cu ) and the storage temperature (T) associated with storage leakage measurements. lk The difference between the values ​​exceeds the temperature threshold, and / or if the current humidity (H) cu ) and the storage humidity (H) associated with storage leakage measurements. lk If the difference between the temperature threshold, humidity threshold, and humidity threshold exceeds the humidity threshold, a validity determination can be made in operation 910. If the difference exceeds the temperature threshold, humidity threshold, or both, flowchart 900 proceeds to operation 912. If neither the temperature threshold nor the humidity threshold is exceeded, flowchart 900 proceeds to operation 914.

[0094] For ease of discussion, timely updates to leakage measurements can be categorized into two different types of applications. The first type of application (which may be referred to as Type 1 applications in this paper) uses radar measurements. These radar-based applications do not necessarily require target detection as in typical radar use cases. Some examples include facial authentication and gesture recognition, which do not require explicit radar detection (although explicit radar detection can still be used). The second type of application (which may be referred to as Type 2 applications in this paper) does not use radar measurements. Type 2 applications may use other non-radar sensors (e.g., cameras) or not use sensors at all. Operational context data from non-radar sensors or the application itself can be used to infer whether an update to the leakage measurement is possible (i.e., there is no object in the radar field of view, making it possible to obtain a new leakage measurement). In both Type 1 and Type 2 applications, the decision to update the leakage measurement is based on inferences used to determine whether the object is within the vicinity of the associated radar transceiver and within the field of view of the associated radar transceiver (which would hinder the capture of an accurate leakage measurement).

[0095] Figure 10 A flowchart illustrating a leak measurement update decision for a radar-based application, according to various embodiments of the present disclosure, is shown. The processor (such as...) Figure 1 The processor 140 of the electronic device 100 can execute instructions to cause the electronic device to undergo the operations described in flowchart 1000 to arrive at a leak measurement update decision. Typically, Type 1 applications acquire and process radar measurements to generate some application-specific operational context data describing the operational state of the application. The operational context data can then be used to determine whether... Figure 10 Update the leak measurements as described in the subsequent figures.

[0096] In flowchart 1000, radar measurements are obtained for type 1 application in operation 1002. Radar measurements can be obtained from... Figure 1 The radar transceiver 150 in the radar system acquires the radar measurements. The radar measurements include the leakage signal transmitted directly from the radar transmitter 157 to the radar receiver 159, and the signal returned to the receiver 159 from the target within the field of view of the radar transceiver 150.

[0097] Based on the radar measurements obtained in operation 1002, a determination is made in operation 1004 as to whether the leakage measurements can be updated. If the leakage measurements can be updated, the measurements corresponding to the leakage signal are extracted from the radar measurements in operation 1006. In a particular embodiment, extraction is achieved by selecting the signal response corresponding to a small delay tap (e.g., in the range between 0-20 cm, or in the range between approximately 0-15 cm). Alternatively, these small delay taps may be referred to as "leakage taps." Because leakage is a direct transmission between the transmitter and receiver, the path length is short, and therefore its main impact is at short distances. For this reason, in order to eliminate the main leakage, particular attention is paid to radar measurements at close range or equivalent small delay indices.

[0098] In operation 1008, the stored leak measurement can be updated using the extracted measurement corresponding to the leak signal. If it is determined in operation 1004 that the leak measurement cannot be updated, then the leak measurement is not updated in operation 1010.

[0099] Figure 11 A flowchart illustrating a leak measurement update decision for radar-based presence detection according to various embodiments of this disclosure is shown. The leak measurement update decision can be made at least in part based on information from a Type 1 application employing an algorithm to process the raw radar measurement to detect the presence of an object nearby. The raw radar measurement includes a contribution from the leak signal. The application may also have range estimation capabilities that may be inaccurate due to the influence of the leak signal, particularly at close ranges such as less than about 20 cm or less than about 10 cm. Presence detection is achieved by observing the behavior of the CIR near the leak tap. The leak contribution from a static source exhibits specific behavior. The presence of an object can be detected by detecting deviations in the measured radar signal. Various methods can be used as detection algorithms. Some examples include classical signal processing algorithms and machine learning methods. Some example signal processing methods could be methods for detecting shape changes in the leak CIR. This method can calculate some conceptual distances to some stored templates of the pure leak CIR, and if the obtained distance deviates from a certain threshold, a target is detected; otherwise, no target is detected. Some example machine learning methods could be any classifier, such as a k-nearest neighbor-based or support vector machine-based classifier or even a neural network. A classifier can be trained to identify the behavior of pure leak CIRs, making it able to distinguish between pure leak CIRs and non-pure leak CIRs (i.e., when one or more targets are present).

[0100] processors (such as) Figure 1The processor 140 of the electronic device 100 can execute instructions to cause the electronic device to undergo a series of operations described in flowchart 1100. In operation 1102, radar measurements for presence detection are obtained. These measurements can be obtained from... Figure 1 The radar transceiver 150 obtains the information. In operation 1104, a determination is made regarding whether the presence of a target is detected. If the presence of a target is not detected, then no object is in the vicinity of the radar transceiver and within the radar transceiver's field of view. In operation 1106, a measurement corresponding to the leakage signal between the transmitter and receiver is extracted, and in operation 1108, this measurement is used to update the stored leakage measurement.

[0101] If a target is detected in operation 1104, there is a possibility that the object may be in the vicinity of the radar transceiver and within the radar transceiver's field of view. Therefore, flowchart 1100 proceeds to operation 1110, and the stored leak is not updated.

[0102] Figure 12 A flowchart illustrating radar-based range estimation using an updated leak response, according to various embodiments of this disclosure, is shown. Processors (such as...) Figure 1 The processor 140 of the electronic device 100 can execute instructions to cause the electronic device to undergo a series of operations for distance estimation as described in flowchart 1200. In operation 1202, radar measurements for presence detection are obtained. In operation 1204, a determination is made as to whether a target is detected. If no target is detected, the stored leakage measurement is updated in operation 1206 if necessary. In a non-limiting embodiment, the stored leakage measurement is updated by extracting a leakage signal from the radar measurement obtained in operation 1202. Returning to operation 1204, if a target is detected, the distance to the target is estimated in operation 1208 using the previously obtained updated leakage response.

[0103] Figure 13 A flowchart of a leak measurement update decision for radar-based facial authentication, according to various embodiments of the present disclosure, is shown. Flowchart 1300 illustrates the use of operational context data from a radar-based facial authentication application for leak update decisions. Radar measurements for facial authentication are input into the facial authentication algorithm, and the output of the facial authentication application contains the desired operational context data. For example, if the facial authentication application successfully performs the radar measurement, regardless of whether the user is authenticated, it can be assumed that the face was correctly captured in the radar measurement without any obstructing objects in the environment between the radar transceiver and the user's face. Figure 14 The diagram illustrates a typical use case for an electronic device used for facial authentication. The radar measurement of the user's face includes a leakage signal in a small delay tap that can be used to update the leakage measurement.

[0104] Using the radar measurements obtained in operation 1302 for facial authentication, a determination is made in operation 1304 regarding whether facial authentication was successfully completed. In one embodiment, successful completion of facial authentication means authenticating a user performing a radar-based facial authentication application on the electronic device. In another embodiment, successful completion of facial authentication may be based on accessibility radar measurements rejecting the user's authentication attempt.

[0105] If facial authentication is successful, the measurement corresponding to the leakage signal is extracted from the radar measurements in operation 1306. In operation 1308, the extracted measurement is used to update the stored leakage measurement. If facial authentication fails in operation 1304, the leakage measurement is not updated in operation 1310.

[0106] Figure 14 The following illustrations depict user interaction with electronic devices for radar-based facial authentication according to various embodiments of the present disclosure. As such... Figure 1 The electronic device 1400 of the device 100 performs a radar-based authentication application (not shown) for authenticating user 1402. The electronic device 1400 maintains a distance D from the face of user 1402. Typically, this distance is between 20cm and 50cm, which ensures that there are no objects in the vicinity of the electronic device 1400 and within the field of view of the electronic device 1400 (i.e., between 0 and 20cm from the electronic device).

[0107] Figure 15 A flowchart illustrating a leak measurement update decision for radar-based emotion or heartbeat monitoring, according to various embodiments of the present disclosure, is shown. Flowchart 1500 depicts the use of operational context data from a radar-based emotion or heartbeat monitoring application for leak update decisions. Type 1 applications can use radar measurements to monitor a user's emotion or heartbeat; an example is a mobile application used to monitor driver drowsiness or incapacitation. Radar can be used to infer the driver's physical state based on physiological patterns such as heartbeat and breathing. In this embodiment, the mobile device executing the Type 1 application may be placed on a dashboard facing the driver. In typical use cases, there will be no obstruction between the radar transceiver and the driver.

[0108] Flowchart 1500 begins with radar measurements obtained in operation 1502 for emotion or heartbeat monitoring. Using those radar measurements, operation 1504 determines whether the leak measurement can be updated based on signal strength and / or the Doppler effect. Regarding the possibility of purity in the leak measurement, additional precautions can be incorporated to ensure better quality of the captured measurements. For example, signal strength and Doppler information can be used to provide additional operational context data that can be used to determine whether the vehicle is moving. Movement in the vehicle will manifest as vibrations in the electronics, which are micro-movements relative to other objects in the vehicle. By confirming that there is no large energy in the leak tap signal in the non-zero Doppler channel, it can be inferred that there is no obstructing object near the radar transceiver, and the leak can be updated. In other words, an object in the vicinity of the radar transceiver and within the radar transceiver's field of view will have a reflected energy level in the leak tap that exceeds the background level. Conversely, an object absent in the vicinity of the radar transceiver and within the field of view will have a reflected energy level in the leak tap that is proportional to the background level. The amount of energy in the non-zero Doppler channel at the small delay tap is taken as the reciprocal of the confidence level. In other words, the stronger the energy, the less likely the leak can be replaced. (See below) Figure 21 and 22 The confidence level will be discussed in more detail in the next section.

[0109] If the leak measurement can be updated, then in operation 1506, the measurement corresponding to the leak signal is extracted from the radar measurement used in the emotion or heartbeat application. However, if the leak measurement cannot be updated based on the result of operation 1504, then the leak measurement is not updated in operation 1510.

[0110] Figure 16 A flowchart illustrating a leak measurement update decision for applications using non-radar sensors and radar transceivers, according to various embodiments of this disclosure, is shown. Processors (such as...) Figure 1 The processor 140 of the electronic device 100 can execute instructions to cause the electronic device to undergo the operations described in flowchart 1600 for making updated decisions using non-radar sensors and radar-based sensors. In a particular embodiment, the non-radar sensor is an inertial sensor that can be used to determine the movement of the electronic device, and subsequent analysis of radar measurements from the radar transceiver can be used to determine whether new leakage measurements can be obtained.

[0111] If an electronic device moves relative to its surroundings, Doppler information and signal strength can be used to detect the presence of any obstacles nearby. This can also be achieved without using inertial sensors, such as... Figure 15The following describes in more detail the use of Type 1 applications to infer device motion. Since the device moves relative to its surroundings, if an obstructing object is present near the radar antenna module, the reflection from that object will have a non-zero Doppler effect. The leakage, as a direct signal from the radar transmitting antenna rigidly mounted on the device to the receiving antenna rigidly mounted on the device, will be static relative to each other. The leakage signal will fall into the zero Doppler channel. Therefore, by confirming that there is no large energy in the leakage tap signal in the non-zero Doppler channel, it can be inferred that there is no obstructing object near the radar transceiver, and the leakage can be updated. Note that in this case, the amount of energy in the non-zero Doppler channel at the small delay tap can be used as the reciprocal of the confidence level. That is, the stronger the energy, the less likely the leakage can be updated, a fact that can be used during the calculation of the confidence level.

[0112] Flowchart 1600 begins with obtaining input from one or more sensors in operation 1602. Using the sensor input, operation 1604 determines whether the device is in motion. If the device is not in motion, the leak measurement is not updated in operation 1606. However, if the device is in motion, a radar measurement is obtained in operation 1608, and the flowchart proceeds to operation 1610, where a determination is made as to whether the leak measurement can be updated using signal strength and the Doppler effect. If the leak measurement can be updated using signal strength and the Doppler effect, the flowchart proceeds to operation 1612, where the measurement corresponding to the leak signal is extracted from the radar measurement. The leak measurement is updated in operation 1614. However, if it is determined at operation 1610 that the leak measurement cannot be updated using signal strength and the Doppler effect, the leak measurement is not updated in operation 1616.

[0113] Figure 17 A general flowchart for leak measurement update decisions for non-radar applications is shown, according to various embodiments of this disclosure. Processors (such as...) Figure 1 The processor 140 of the electronic device 100 can execute instructions to cause the electronic device to go through a series of steps described in flowchart 1700 for making a leak measurement update decision.

[0114] The operational context data obtained in operation 1702 can be used to make a leak measurement update decision in operation 1704. In some embodiments, the Type 2 application uses non-radar sensors (such as proximity sensors and inertial sensors) to obtain the operational context data, and in other embodiments, the operational context data is derived directly from the execution of the application. In either case, if the leak measurement can be updated, a radar leak measurement is performed in operation 1706. In operation 1708, a radar leak measurement is performed by activating a radar transceiver to perform a set of radar measurements, which can be processed to obtain a leak measurement to update the stored leak measurement. If the leak measurement cannot be updated in operation 1704, the leak measurement is not updated in operation 1710.

[0115] Figure 18 A flowchart illustrating a leak measurement update decision for non-radar applications using sensors, according to various embodiments of this disclosure, is shown. Processors (such as...) Figure 1 The processor 140 of the electronic device 100 can execute instructions to cause the electronic device to go through a series of steps, as described in flowchart 1800, for making a leak measurement update decision. Sensor measurements for a Type 2 application are obtained in operation 1802. Sensor measurements can be captured directly from one or more sensors, or derived from data captured by one or more sensors.

[0116] In operation 1804, a determination is made as to whether the leak measurement can be updated based on sensor measurements. If the leak measurement can be updated, a radar leak measurement is performed in operation 1806. In operation 1808, a radar leak measurement is performed by activating a radar transceiver to perform a set of radar measurements, which can be processed to obtain a leak measurement to update the stored leak measurement. If the leak measurement cannot be updated in operation 1804, the leak measurement is not updated in operation 1810.

[0117] Figure 19 A flowchart illustrating a process for updating a leak measurement decision for vision-based facial authentication in non-radar applications, according to various embodiments of this disclosure, is shown. Processors (such as...) Figure 1The processor 140 of the electronic device 100 can execute instructions to cause the electronic device to undergo a series of steps described in flowchart 1900 to make a leakage measurement update decision based on successful image capture. Specifically, if the user's face is successfully captured, it can be inferred that no object exists between the electronic device and the user's face, regardless of whether the user is actually authenticated. This also means that the environment near the radar transceiver is unobstructed for leakage measurement. In some embodiments, the outcome of the vision-based authentication application can be a factor considered in the determination of confidence level. For example, successful authentication may be weighted higher than unsuccessful authentication because unsuccessful authentication can be attributed to additional factors, such as unexpected and undetected obstructions from the user's hand or fingers.

[0118] To reduce or eliminate obstruction by the user's hands or fingers, additional sensor data can be captured and used to determine the position of the user's hands or fingers. For example, capacitive touch sensors can be used to detect a grip, or infrared-based proximity sensors near a radar transceiver can be used. (As will be...) Figure 21 and Figure 22 As described, sensor data can be incorporated into the calculation of confidence levels.

[0119] Returning to flowchart 1900, the process begins in step 1902 by capturing a camera image for a vision-based facial authentication application. In step 1904, it is determined whether the image capture was successful. If the image capture is successful, a radar leakage measurement is performed in step 1906, and the stored leakage measurement is updated in step 1908. However, if it is determined at step 1904 that the image capture was unsuccessful, the process continues to step 1910 without updating the stored leakage measurement.

[0120] Although Figure 19 The exemplary embodiments described herein relate to facial authentication, but the steps of flowchart 1900 can generally be applied to other forms of biometric authentication, such as iris sensor authentication and fingerprint authentication, wherein the operational context data obtained in step 1902 can be used to infer that there are no objects near the radar transceiver for the purpose of leakage measurement.

[0121] Figure 20 A flowchart illustrating a process for updating a leakage measurement decision for a proximity sensor in a non-radar application, according to various embodiments of the present disclosure, is shown. The processor (such as...) Figure 1The processor 140 of the electronic device 100 can execute instructions to cause the electronic device to undergo a series of steps described in flowchart 2000. Additionally, sensor 175 may include one or more proximity sensors capable of capturing sensor data that can be used to make updated decisions. Examples of proximity sensors include infrared, ultrasonic, laser, or capacitive sensors, or any other type of proximity sensor based on touch or hand grip, even including advanced methods such as using image processing on camera images to identify objects and measure their distance.

[0122] The proximity sensor data is obtained in step 2002 and used in step 2004 to determine whether an object is near the radar transceiver. If the object is not near the radar transceiver, a radar leakage measurement can then be performed in step 2006 as described in the previous embodiment. Before the process terminates, the stored leakage measurement can be updated in step 2008 using the results of the radar leakage measurement. If it is determined in step 2004 that the object is in the vicinity of the radar transceiver, the leakage measurement is not updated in step 2010, and the process terminates.

[0123] Figure 21 A flowchart illustrating various embodiments of the present disclosure for incorporating confidence levels into a leak measurement update decision is shown. A confidence level is a set of values ​​that can be used to weight the inputs of the leak measurement update process. Confidence levels can be determined by a processor in an electronic device (such as...). Figure 1 The processor 140 of the electronic device 100 calculates the data from data captured by one or more sensors 175 or from data from one or more applications as described above in the applications 164. Different methods can be used to perform leak measurement updates based on confidence levels. One example is performing a confidence-level-weighted average. Another possibility is to use weights calculated using both the confidence level and the freshness of the measurement (e.g., determined from the timestamp of the record).

[0124] In operation 2102, radar measurements are obtained for type 1 application. The confidence level can be calculated based on the radar measurements in operation 2104 and input into the leak measurement update process in operation 2108, which also takes into account the radar measurements corresponding to the leak signal extracted in operation 2106.

[0125] Although described relative to type 1 application Figure 21 The flowchart in the document describes how contextual operational data can be captured from Type 2 applications to calculate confidence levels that can be used to make decisions about leak measurement updates. For example, it can be used for... Figure 19The vision-based facial authentication application described herein calculates confidence levels by considering not only whether a successful image is captured for facial authentication, but also whether the facial authentication result is successful. Successful authentication can be given a higher confidence level than unsuccessful authentication.

[0126] Figure 22 A flowchart illustrating various embodiments of the present disclosure for incorporating confidence level decisions into leak measurement update decisions. The leak measurement update decision combines soft and hard decisions based on confidence levels. Confidence levels can be determined by a processor in an electronic device (such as...). Figure 1 The processor 140 of the electronic device 100 performs calculations from data captured by one or more sensors 175 or from data from one or more applications as described above in the applications 164.

[0127] In operation 2202, radar measurements are obtained for Type 1 application. In operation 2204, a confidence level is calculated based on those radar measurements. In operation 2206, it is determined whether the confidence level exceeds a threshold. If the confidence level exceeds the threshold, then in operation 2208, the measurement corresponding to the leakage signal is extracted from the radar measurements. In operation 2210, the stored leakage measurements are updated. However, if it is determined in operation 2206 that the confidence level does not exceed the threshold, then in operation 2212, the stored leakage measurements are not updated.

[0128] Although described relative to type 1 application Figure 22 The flowchart in the document describes how contextual operational data can be captured from Type 2 applications to calculate confidence levels that can be used to make decisions about leak measurement updates. For example, it can be used for... Figure 19 The vision-based facial authentication application described herein calculates the confidence level. Furthermore, the confidence level can be combined with... Figure 23 and Figure 24 The discussion in section 2 covers the use of contextual operation data derived from voice or video call applications in application type 2.

[0129] Figure 23 A flowchart illustrating a process for obtaining a leak measurement update decision for a voice or video application, according to an exemplary embodiment, is shown. This process can be implemented in a communication-enabled electronic device, such as a telephone, tablet, or smartwatch. Furthermore, it is assumed that a call accepted when the electronic device is not in hands-free mode will be performed by bringing the user's hand towards the user's face or holding it in mid-air to allow the call to be made on a speakerphone. The absence of hands-free mode reduces the likelihood that a call might be accepted when the electronic device is in a pocket.

[0130] The process begins when a call for a voice or video application is received in step 2302. In step 2304, a determination is made as to whether the call was accepted without hands-free mode. If the call was accepted without hands-free mode, a radar leakage measurement is performed in step 2306. In step 2308, the stored leakage measurement is updated using the new radar leakage measurement, and the process ends. Returning to step 2304, if it is determined that the call was not accepted without hands-free mode, the stored leakage measurement is not updated in step 2310, and the process ends.

[0131] In another embodiment, assuming the user holds the electronic device in a manner that does not introduce objects into the vicinity of the radar transceiver or the field of view, rejecting calls without activating hands-free mode can also be used to trigger radar leakage measurements.

[0132] In variations of these embodiments, a time delay may be applied after a call is accepted but before radar leakage measurement is allowed to be performed, to ensure that the device is in mid-air without any obstructions in the vicinity of the radar transceiver when leakage measurement is captured. In another variation, a time window may be applied for performing radar leakage measurement in step 2306 to ensure that leakage measurement is not obtained when the electronic device is close to or against the user's face.

[0133] exist Figure 23 In another variation of the embodiments described, other non-radar applications can replace voice / video applications, provided that other non-radar applications require the user to keep the electronic device in a specific location that can be used to infer that no object is in the vicinity of the radar transceiver and within the field of view. For example, some gaming applications may require the user to place their finger in a position that does not obstruct the radar antenna module.

[0134] Figure 24 A flowchart illustrating a process for updating a replacement leakage measurement for a voice or video call application, according to another exemplary embodiment, is shown. This process can be implemented in a communication-enabled electronic device (such as a phone, tablet, or smartwatch) with hands-free mode activated. Hands-free mode is activated when the electronic device is connected to the user via a wired or wireless headset, allowing the user to indirectly accept or reject calls regardless of the device's location. For example, a user could accept a call while the phone is in their pocket or face down, even if the radar antenna module is obstructed. Additional contextual data may be required to determine whether a radar leakage measurement should be performed. Examples of contextual data may include data from proximity sensors, light detection sensors, and positioning sensors, which can be used to reduce the likelihood of performing a radar leakage measurement when one or more objects are in the vicinity of the radar transceiver and within the field of view.

[0135] When a call for a voice or video application is received in step 2402, the process described in flowchart 2400 begins. In step 2404, a determination is made as to whether the call was accepted while hands-free mode is active. If the call was accepted while hands-free mode is active, a radar leakage measurement is performed in step 2406, if the context data allows. Thereafter, the stored leakage measurement is updated in step 2408, and the process terminates. If it is determined in step 2404 that the call was not accepted while hands-free mode is active, the leakage measurement is not updated in step 2410, and the process terminates.

[0136] It can also target Figure 23 and Figure 24 The embodiments described herein calculate confidence levels. For example, position sensors, light sensors, or proximity sensors provide operational context data consistent with the electronic device being in a pocket or face down on one side, which can be used to calculate confidence levels that are unfavorable for updating stored leakage measurements.

[0137] Figure 25 This is a flowchart of a process for timely updating a leak response according to various embodiments of this disclosure. Processor (such as...) Figure 1 The processor 140 of the electronic device 100 can execute instructions to cause the electronic device to go through the steps described in flowchart 2500 to update the leak response in a timely manner.

[0138] The process begins in step 2502 by determining whether a change in at least one state variable has been detected. The change in the state variable can be used to identify whether a stored leakage measurement associated with at least one state variable is still valid. Non-limiting examples of state variables may include time, temperature, humidity, or any other device-related state that may affect radar transmission in the electronic device. In some embodiments, a change in at least one state variable is determined by identifying any change in the state variable. In other embodiments, the change in the state variable may be a change exceeding a certain threshold. For example, the change in the state variable may be the elapsed time of a discrete-time quantity, or a temperature change exceeding a certain degree or a certain percentage.

[0139] If no change is detected in step 2502, the stored leak response does not need to be updated, and the process returns to the beginning. If a change in at least one state variable has been detected, then in step 2504, a determination is made regarding whether there is an object in the vicinity of the radar transceiver and within its field of view. If there is an object in the vicinity of the radar transceiver and within its field of view, the radar signal within the leak tap cannot be accurately attributed to either the leak signal or an object in the vicinity of the radar transceiver's field of view. Therefore, the process returns to the beginning.

[0140] If no object is in the vicinity of the radar transceiver or within the radar transceiver's field of view, a leakage measurement is obtained in step 2506. The leakage measurement can be obtained in any number of ways as described in the previous embodiments. For example, it can be obtained by extracting a set of signals from radar measurements captured during the execution of the Type 1 application, or by activating the radar transceiver after or during the execution of the Type 2 application to execute a set of radar measurements that can be processed to obtain the leakage measurement.

[0141] In step 2508, the leak response is updated based on the leak measurement. The update can be a simple replacement, or it can combine an averaging process as described above. Additionally, the update can incorporate the confidence level as described above. The process terminates after the leak response has been updated.

[0142] As previously discussed in the preceding embodiments, when the process of flowchart 2500 is applied to some Type 1 applications, the step of determining whether there is an object in the vicinity of the radar transceiver and within the field of view involves performing a successful radar-based measurement on a target located outside the vicinity of the radar transceiver, and the step of obtaining the leakage measurement includes extracting signals corresponding to a set of leakage taps from the successful radar-based measurement.

[0143] As previously discussed in the preceding embodiments, when the process of flowchart 2500 is applied to some Type 1 application that has accessed operational context data including Doppler data, the step of determining whether there is an object in the vicinity of the radar transceiver and within the radar transceiver's field of view includes confirming that the reflected energy from the vicinity of the radar transceiver is proportional to the background level.

[0144] As previously discussed in the preceding embodiments, when the process of flowchart 2500 is applied to some type 2 application, the step of determining whether there is an object in the vicinity of the radar transceiver and within the radar transceiver's field of view includes performing a successful non-radar sensor-based measurement on a target located outside the vicinity of the radar transceiver, and the step of obtaining a leakage measurement includes measuring the leakage signal between the transmitter and receiver of the radar transceiver.

[0145] As previously discussed in previous embodiments, when the process of flowchart 2500 is applied to some Type 2 application that accesses operational context data from one or more proximity sensors, the step of determining whether there is an object in the vicinity of the radar transceiver and within the radar transceiver's field of view includes using a non-radar proximity sensor to determine that no target is detected in the vicinity of the radar transceiver, and the step of obtaining a leakage measurement includes measuring the leakage signal between the transmitter and receiver of the radar transceiver.

[0146] As previously discussed in the preceding embodiments, when the process of flowchart 2500 is applied to some Type 2 applications that do not access operational context data from sensors, the step of determining whether there is an object in the vicinity of the radar transceiver and within the radar transceiver's field of view includes receiving user input via electronic devices, which relates to the absence of any object in the vicinity of the radar transceiver. An example of the user input is... Figure 23 and Figure 24 The process has been described in more detail and may include accepting or rejecting voice or video calls when the electronic device is not operating in hands-free mode. Another example of user input could be the movement of the phone in three-dimensional space, such as when the user brings the phone to their ear. Furthermore, the step of obtaining leakage measurements also includes measuring the leakage signal between the transmitter and receiver of the radar transceiver.

[0147] The descriptions in this application should not be construed as implying that any particular element, step, or function is an essential element that must be included within the scope of the claims.

Claims

1. An electronic device comprising: Radar transceiver; The memory is configured to store data; as well as A processor is operatively connected to the radar transceiver. The processor is configured to: Based on an application that performs at least one of radar-based measurements or measurements based on non-radar sensors, obtain operational context data corresponding to the operations performed by said application; Based on the operational context data, it is determined that there is no object in the vicinity of the radar transceiver and within the field of view of the radar transceiver; In response to determining that no object exists in the vicinity of the radar transceiver and within the field of view of the radar transceiver, a leakage measurement of the radar transceiver is obtained by measuring the leakage signal between the transmitter and receiver of the radar transceiver; and The leak response used for leak elimination is updated based on the leak measurement. 2.The electronic device of claim 1, wherein, The processor is also configured to: Detecting changes in at least one state variable of the electronic device; and In response to detecting a change in the at least one state variable, it is determined that there is no object in the vicinity of the radar transceiver and within the field of view of the radar transceiver. 3.The electronic device of claim 1, wherein, The processor is configured to: Successful radar-based measurements of targets located outside the vicinity of the radar transceiver determine that no object exists within the vicinity of the radar transceiver and within the radar transceiver's field of view. The leakage signal is measured by extracting the signal corresponding to a set of leakage taps from the successful radar-based measurement.

4. The electronic device as claimed in claim 1, wherein, The processor is configured to: By confirming that the reflected energy from the area near the radar transceiver is proportional to the background level, it is determined that there is no object in the vicinity of the radar transceiver and within the field of view of the radar transceiver.

5. The electronic device as claimed in claim 1, wherein, The processor is also configured to: By performing successful non-radar sensor-based measurements on targets located outside the vicinity of the radar transceiver, it is determined that no object exists within the vicinity of the radar transceiver and within the field of view of the radar transceiver.

6. A method for updating a leak response, the method comprising: Based on an application that performs at least one of radar-based measurements or measurements based on non-radar sensors, obtain operational context data corresponding to the operations performed by said application; An electronic device with a radar transceiver determines, based on the operational context data, that there is no object in the vicinity of the radar transceiver and within the field of view of the radar transceiver. In response to determining that no object exists in the vicinity of the radar transceiver and within the field of view of the radar transceiver, a leakage measurement of the radar transceiver is obtained by measuring the leakage signal between the transmitter and receiver of the radar transceiver; and The leak response used for leak elimination is updated based on the leak measurement.

7. The method of claim 6, further comprising: Detect changes in at least one state variable of the electronic device; as well as The step of determining that there is no object in the vicinity of the radar transceiver and within the field of view of the radar transceiver includes: in response to detecting a change in the at least one state variable, determining that there is no object in the vicinity of the radar transceiver and within the field of view of the radar transceiver.

8. The method of claim 6, wherein, The step of determining that there are no objects in the vicinity of the radar transceiver and within the field of view of the radar transceiver further includes: performing a successful radar-based measurement on a target located outside the vicinity of the radar transceiver, and The step of measuring the leakage signal further includes: extracting signals corresponding to a set of leakage taps from the successful radar-based measurement.

9. The method of claim 6, wherein, The step of determining that there are no objects in the vicinity of the radar transceiver and within the field of view of the radar transceiver also includes confirming that the reflected energy from the vicinity of the radar transceiver is proportional to the background level.

10. The method of claim 6, wherein, The step of determining that there is no object in the vicinity of the radar transceiver and within the field of view of the radar transceiver further includes: performing a successful non-radar sensor-based measurement on a target located outside the vicinity of the radar transceiver.

11. A non-transitory computer-readable medium storing instructions that, when executed by a processor of an electronic device, cause the electronic device to perform the following operations: Based on an application that performs at least one of radar-based measurements or measurements based on non-radar sensors, obtain operational context data corresponding to the operations performed by said application; The electronic device determines, based on the operational context data, that there is no object in the vicinity of the radar transceiver of the electronic device and within the field of view of the radar transceiver of the electronic device. In response to determining that no object exists in the vicinity of the radar transceiver and within the field of view of the radar transceiver, a leakage measurement of the radar transceiver is obtained by measuring the leakage signal between the transmitter and receiver of the radar transceiver; and The leak response used for leak elimination is updated based on the leak measurement.

12. The non-transitory computer-readable medium of claim 11, further storing instructions that, when executed by the processor, cause the electronic device to perform the following operations: Detecting changes in at least one state variable of the electronic device; and In response to detecting a change in the at least one state variable, it is determined that there is no object in the vicinity of the radar transceiver and within the field of view of the radar transceiver.

13. The non-transitory computer-readable medium of claim 11, further storing instructions that, when executed by the processor, cause the electronic device to perform the following operations: Successful radar-based measurements of targets located outside the vicinity of the radar transceiver determine that no object exists within the vicinity of the radar transceiver and within the radar transceiver's field of view. The leakage signal is measured by extracting the signal corresponding to a set of leakage taps from the successful radar-based measurement.

14. The non-transitory computer-readable medium of claim 11, further storing instructions that, when executed by the processor, cause the electronic device to perform the following operations: By performing successful non-radar sensor-based measurements on targets located outside the vicinity of the radar transceiver, it is determined that there are no objects in the vicinity of the radar transceiver and within the field of view of the radar transceiver.

15. The non-transitory computer-readable medium of claim 11, further storing instructions that, when executed by the processor, cause the electronic device to perform the following operations: By using a non-radar proximity sensor to determine that no target is detected in the vicinity of the radar transceiver, it is determined that there is no object in the vicinity of the radar transceiver and within the field of view of the radar transceiver.

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