Angular and Linear Motion Detection and Correction for User Equipment - Patent application

Abstract

In some implementations, a user equipment (UE) may determine angular motion using at least one gyroscope. The UE may adjust at least one measurement from at least one sensor associated with the UE and used to measure a relative position based at least in part on the angular motion. Additionally, in some implementations, the UE may determine at least one distance between the at least one sensor and an estimated grip associated with the UE, and determine at least one translation associated with the at least one sensor based at least in part on the angular motion and the at least one distance. Thus, the UE may adjust the at least one measurement by offsetting the at least one measurement based at least in part on the at least one translation.

Description

[Technical field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This patent application claims priority to U.S. Non-provisional Patent Application No. 17 / 193,971, filed March 5, 2021, entitled “ANGULAR AND LINEAR MOVEMENT DETECTION AND COMPENSATION FOR USER EQUIPMENT,” which is expressly incorporated herein by reference.

[0002] Aspects of the present disclosure relate generally to motion compensation for user equipment, e.g., detecting angular and linear motion to compensate for user equipment motion. [Background technology]

[0003] User equipment (UE), such as smartphones, tablets, and other mobile computing devices, are often required to reduce their transmit power when in close proximity to living beings, especially for 5G wavelength transmissions such as millimeter wave (mmW) transmissions. These reductions may be for safety reasons and may be mandated by government agencies such as the Federal Communications Commission (FCC). The UE may detect nearby objects using one or more techniques, such as infrared sensing, radio frequency radar, camera detection, and / or other similar techniques, and classify those objects as animate or inanimate (e.g., based at least in part on the motion of those objects). Thus, the UE may reduce its transmit power based on the detection and classification of nearby objects as animate. Summary of the Invention [Means for solving the problem]

[0004] In some implementations, a method of motion detection performed by a user equipment (UE) includes determining angular motion using at least one gyroscope of the UE and adjusting at least one measurement from at least one sensor associated with the UE and used to measure a relative position based at least in part on the angular motion.

[0005] In some implementations, the UE includes a memory and one or more processors operably coupled to the memory, where the memory and the one or more processors are configured to determine, using the at least one gyroscope, an angular motion and to adjust, at least in part, at least one measurement from at least one sensor associated with the UE and used to measure a relative position based at least in part on the angular motion.

[0006] In some implementations, a non-transitory computer-readable medium storing a set of instructions for wireless communication includes one or more instructions that, when executed by one or more processors of a UE, cause the UE to determine an angular motion using at least one gyroscope of the UE, and to adjust at least one measurement from at least one sensor associated with the UE and used to measure a relative position based at least in part on the angular motion.

[0007] In some implementations, an apparatus for wireless communication includes means for determining angular motion using at least one gyroscope and means for adjusting at least one measurement from at least one sensor associated with the apparatus and used to measure a relative position based at least in part on the angular motion.

[0008] Aspects generally include methods, apparatus, systems, computer program products, non-transitory computer-readable media, user devices, user equipment, wireless communication devices, and / or processing systems as fully described with reference to and as illustrated in the drawings and this specification.

[0009] The foregoing has outlined rather broadly the features and technical advantages of examples according to the present disclosure so that the following detailed description may be better understood. Additional features and advantages are described below. The concepts and examples disclosed may be readily used as a basis for modifying or designing other structures for carrying out the same purposes of the present disclosure. Such equivalent structures do not depart from the scope of the appended claims. The characteristics of the concepts disclosed herein, both their organization and methods of operation, together with associated advantages, will be better understood from the following description when considered in conjunction with the accompanying drawings. Each of the figures is provided for the purpose of illustration and explanation, and not as a definition of the limits of the claims.

[0010] So that the above-mentioned features of the present disclosure may be understood in detail, a more detailed description may be had by referring to embodiments, some of which are illustrated in the accompanying drawings. It should be noted, however, that the accompanying drawings illustrate only some typical embodiments of the present disclosure and therefore should not be considered as limiting its scope, since the present description may admit of other equally effective embodiments. The same reference numbers in different drawings may identify the same or similar elements. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 illustrates an example environment in which a UE described herein may be implemented, in accordance with the present disclosure. [Figure 2A] 2 illustrates example components of one or more devices shown in FIG. 1, such as a UE, in accordance with the present disclosure. [Figure 2B]FIG. 1 illustrates an exemplary component diagram of a frequency-modulated continuous-wave (FMCW) radar device in accordance with the present disclosure. [Figure 3A] FIG. 1 illustrates an example relating to measurement correction for UE motion in accordance with the present disclosure. [Figure 3B] FIG. 1 illustrates an example relating to measurement correction for UE motion in accordance with the present disclosure. [Figure 4] FIG. 13 illustrates another example relating to measurement correction for UE motion in accordance with the present disclosure. [Diagram 5] FIG. 1 illustrates an example relating to determining linear translation from gyroscope and accelerometer measurements in accordance with the present disclosure. [Figure 6] 1 is a flowchart of an example process related to correcting measurements for UE motion in accordance with the present disclosure. [Figure 7] 1 is a flowchart of an example process related to estimating a handgrip of a UE in accordance with the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Various aspects of the present disclosure will be described more fully below with reference to the accompanying drawings. However, the present disclosure may be embodied in many different forms and should not be construed as limited to any particular structure or function presented throughout the present disclosure. Rather, these aspects are provided so that the disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art. Based on the teachings herein, those skilled in the art should appreciate that the scope of the present disclosure encompasses any aspect of the present disclosure disclosed herein, whether implemented independently of or in combination with any other aspect of the present disclosure. For example, an apparatus may be implemented or a method may be practiced using any number of the aspects described herein. In addition, the scope of the present disclosure is intended to encompass such an apparatus or method practiced using other structures, functions, or structures and functions in addition to or other than the various aspects of the present disclosure described herein. It should be understood that any aspect of the present disclosure disclosed herein may be embodied by one or more elements of a claim.

[0013] The UE may detect and measure nearby objects using one or more techniques, such as infrared sensing, radio frequency radar (e.g., FMCW radar and / or other radar techniques), optical detection and classification of objects (e.g., using at least one camera), and / or other similar techniques. Additionally, the UE may classify objects as animate or inanimate based on the measurements of the objects. For example, small movements of nearby objects may indicate heartbeat patterns, breathing patterns, natural tremors, and / or other manifestations of animacy. Some technologies, such as FMCW radar, are precise enough to detect movements as small as 1 mm.

[0014] However, a user holding a UE may exhibit one or more small movements. For example, the user's heartbeat may have an amplitude between 0.08 mm and 0.4 mm, the user's breathing may exhibit an amplitude between 0.8 mm and 6.0 mm in front of the user's body and 0.2 mm behind the user's body, natural hand tremors may exhibit an amplitude between 0.5 mm and 2 mm, and other movements of the user's body may similarly confound measurements of nearby objects. Thus, FMCW radar and other technologies may miscategorize inanimate objects as animate and / or animate objects as inanimate based on errors in measurements caused by user movements.

[0015] Cameras may use electronic image stabilization (EIS) and / or optical image stabilization (OIS) to adjust for these small movements. However, EIS relies on sacrificing some captured pixels, and similar procedures to sacrifice some measurements do not improve the accuracy of FMCW radar or other technologies. OIS relies on physical movement of the camera lens to compensate for user movement. However, antennas used for FMCW and / or other sensors used to detect nearby objects cannot be placed on a mechanical assembly and moved to compensate for user movement.

[0016] Most UEs include at least one gyroscope (e.g., embedded within an inertial measurement unit (IMU) or other device). Some implementations described herein allow the UE to use measurements from the at least one gyroscope to compensate for the angular motion of the UE. As a result, FMCW radar and other techniques can be used to obtain more accurate measurements of nearby objects. Moreover, this may result in more accurate classification of those objects as animate or inanimate. Additionally, in some implementations, the UE may use at least one accelerometer (e.g., embedded within an IMU or other device) to further compensate for the linear motion of the UE. As a result, the accuracy of FMCW radar and other techniques may be further enhanced.

[0017] 1 is a diagram of an example environment 100 in which systems and / or methods described herein may be implemented. As shown in FIG. 1, the environment 100 may include a base station 110 and a UE 120. The devices of the environment 100 may interconnect via wired connections (e.g., the base station 110 may connect to the core via a wired backhaul), wireless connections (e.g., the UE 120 may connect to the base station 110 via an over-the-air (OTA) interface, such as a Uu interface), or a combination of wired and wireless connections (e.g., the base station 110 may connect to the core network via a wireless backhaul in addition to or instead of a wired backhaul).

[0018] The UE 120 may include a communication device and / or a computing device. For example, the UE 120 may include a wireless communication device, a mobile phone, a user equipment, a laptop computer, a tablet computer, a gaming console, a wearable communication device (e.g., a smart watch, smart glasses, a head mounted display, or a virtual reality headset), or a similar type of device. As shown in FIG. 1, the UE 120 may further include one or more sensors, such as antennas 112-1 and 112-2. As shown in FIG. 1, the antenna 112-1 receives a signal (S RF (t)) and the signal may be reflected by one or more external objects (e.g., target 120). RF (t) may be detected by antenna 112-2. Thus, UE 120 may detect and measure nearby objects using antennas 112-1 and 112-2. In other examples, UE 120 may use additional antennas (e.g., three or more antennas), fewer antennas (e.g., a single antenna), and / or other sensors (e.g., one or more cameras and / or one or more infrared sensors). In some implementations, UE 120 may implement systems and / or methods for measurement correction for UE motion, as described elsewhere herein.

[0019] The base station 110 may include one or more devices capable of communicating with the UE 120 and may also be referred to as a New Radio (NR), base station (BS), Node B, gNB, 5G node B (NB), access point, transmit receive point (TRP), or other similar terminology. Additionally, the base station 110 may include one or more devices capable of receiving coordination and control signals from a core network via a backhaul. For example, the base station 110 may connect to a telecommunications core network, such as a 5G next generation core network (NG Core), Long Term Evolution (LTE), evolved packet core (EPC), and / or other similar telecommunications core network. The base station 110 may provide communication coverage to a particular geographic area. In standards promulgated by the Third Generation Partnership Project (3GPP®), the term "cell" can refer to the coverage area of ​​a BS and / or the BS subsystem serving this coverage area, depending on the context in which the term is used.

[0020] The number and arrangement of devices and networks shown in Figure 1 are provided as an example. In practice, there may be additional devices and / or networks, fewer devices and / or networks, different devices and / or networks, or differently arranged devices and / or networks than those shown in Figure 1. Furthermore, two or more devices shown in Figure 1 may be implemented within a single device, or a single device shown in Figure 1 may be implemented as multiple distributed devices. Additionally or alternatively, a set of devices (e.g., one or more devices) of environment 100 may perform one or more functions described as being performed by another set of devices of environment 100.

[0021] 2A is a diagram illustrating example components of a device 200 according to the present disclosure. The device 200 may correspond to a UE 120. In some implementations, the UE 120 may include one or more of the devices 200 and / or one or more components of the devices 200. As shown in FIG. 2A, the device 200 may include a bus 205, a processor 210, a memory 215, a storage component 220, an input component 225, an output component 230, a communication interface 235, a gyroscope 240, an accelerometer 245, an object detector 250, a position sensor 255, etc.

[0022] The bus 205 includes components that enable communication between the components of the device 200. The processor 210 is implemented in hardware, firmware, or a combination of hardware and software. The processor 210 is a central processing unit (CPU), a graphics processing unit (GPU), an accelerated processing unit (APU), a microprocessor, a microcontroller, a digital signal processor (DSP), a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), or another type of processing component. In some implementations, the processor 210 includes one or more processors that can be programmed to perform functions. The memory 215 includes random access memory (RAM), read only memory (ROM), and / or another type of dynamic or static storage device (e.g., flash memory, magnetic memory, and / or optical memory) that stores information and / or instructions for use by the processor 210.

[0023] The storage component 220 stores information and / or software related to the operation and use of the device 200. For example, the storage component 220 may include a solid state drive (SSD), flash memory, RAM, ROM, and / or another type of non-transitory computer-readable medium.

[0024] Input components 225 include components that enable device 200 to receive information, such as through user input (e.g., a touchscreen display, a keyboard, a keypad, a mouse, buttons, switches, and / or a microphone). Output components 230 include components that provide output information from device 200 (e.g., a display, a speaker, haptic feedback components, audio or visual indicators, etc.).

[0025] The communications interface 235 includes transceiver-like components (e.g., a transceiver and / or a separate receiver and transmitter) that enable the device 200 to communicate with other devices, such as via a wired connection, a wireless connection, or a combination of wired and wireless connections. The communications interface 235 may enable the device 200 to receive information from and / or provide information to another device. For example, the communications interface 235 may include an Ethernet interface, an optical interface, a coaxial interface, an infrared interface, a radio frequency interface, a universal serial bus (USB) interface, a wireless local area interface (e.g., a Wi-Fi interface), a cellular network interface, etc.

[0026] Gyroscope 240 includes components that generate one or more measurements related to angular motion of device 200. In some implementations, the one or more measurements may include angular rate (e.g., from a coordinate system centered on gyroscope 240), roll angle, pitch angle, yaw angle, and / or another angle. For example, gyroscope 240 may include a microelectromechanical systems (MEMS) gyroscope and / or another type of gyroscope.

[0027] The accelerometer 245 includes components that generate one or more measurements related to the linear acceleration of the device 200. In some implementations, the one or more measurements may include an appropriate acceleration (e.g., relative to a rest frame of the accelerometer 245 rather than a fixed coordinate system). For example, the accelerometer 245 may include a piezoelectric accelerometer, a surface micromachined capacitive accelerometer, a resonance accelerometer, and / or another type of accelerometer.

[0028] Object detector 250 includes components that detect and measure the movement of objects external to device 200. For example, object detector 250 may include an infrared sensor, one or more antennas configured to perform radio frequency radar (e.g., FMCW radar and / or other radar techniques), a camera, and / or another similar sensor.

[0029] The position sensor 255 includes components that determine a position associated with the device 200. In some implementations, the position sensor 255 may generate measurements of an absolute position (e.g., using inertial coordinates) associated with the device 200 or a relative position (e.g., with respect to a stationary point such as the center of the Earth or a base station, and / or with respect to a surface such as the surface of the Earth) associated with the device 200. For example, the position sensor 255 may include a global navigation satellite system (GNSS) device, a magnetometer, and / or another similar sensor.

[0030] The device 200 may perform one or more processes described herein. The device 200 may perform these processes based on the processor 210 executing software instructions stored by a non-transitory computer-readable medium, such as the memory 215 and / or the storage component 220. A computer-readable medium is defined herein as a non-transitory memory device. A memory device includes memory space within a single physical storage device or memory space spread across multiple physical storage devices.

[0031] Software instructions may be read into memory 215 and / or storage component 220 from another computer-readable medium or another device via communications interface 235. When executed, the software instructions stored in memory 215 and / or storage component 220 may cause processor 210 to perform one or more processes described herein. Additionally or alternatively, hardwired circuitry may be used in place of or in combination with software instructions to perform one or more processes described herein. Thus, the aspects described herein are not limited to any specific combination of hardware circuitry and software.

[0032] In some implementations, the device 200 includes means for performing one or more processes described herein and / or means for performing one or more operations of the processes described herein. For example, the device 200 may include means for determining angular motion using at least one gyroscope and / or means for adjusting at least one measurement from at least one sensor associated with the apparatus and used to measure relative position based at least in part on the angular motion. In some implementations, such means may include one or more components of the device 200 described with respect to FIG. 2A, such as the bus 205, the processor 210, the memory 215, the storage component 220, the input component 225, the output component 230, the communication interface 235, the gyroscope 240, the accelerometer 245, the object detector 250, the position sensor 255, etc.

[0033] In some implementations, the device 200 may further include means for classifying the external object as animate or inanimate based at least in part on the adjusted at least one measurement. Additionally or alternatively, the device 200 may further include means for determining at least one distance between the at least one sensor and an estimated grip associated with the device 200. Thus, the device 200 may further include means for determining at least one translation associated with the at least one sensor based at least in part on the angular motion and the at least one distance.

[0034] Additionally or alternatively, device 200 may include means for determining at least one linear movement of device 200 using at least one measurement from the at least one accelerometer. Additionally, device 200 may include means for receiving at least one relative distance between the at least one sensor and the at least one accelerometer, and means for determining at least one translation associated with the at least one sensor based at least in part on the angular movement, the at least one linear movement, and the at least one relative distance.

[0035] In some implementations, the device 200 may further include means for projecting the at least one translation into a direction associated with the at least one sensor.

[0036] The number and arrangement of components shown in Figure 2A are provided as an example. In practice, device 200 may include additional, fewer, different, or differently arranged components than those shown in Figure 2A. Additionally or alternatively, a set of components (e.g., one or more components) of device 200 may perform one or more functions that are described as being performed by another set of components of device 200.

[0037] 2B is a diagram illustrating example components of a device 260 according to the present disclosure. The device 260 may be a radar device, such as an FMCW radar device. The device 260 may be included in the device 200 of FIG. 2A. Thus, in some implementations, the UE 120 may include one or more devices 260 and / or one or more components of the device 260. As shown in FIG. 2B, the device 260 may include a bus 265, a processor 270, a memory 275, a modulator 280, a demodulator 285, a communication interface 290, one or more antennas 295, etc.

[0038] The bus 265 includes components that enable communication between the components of the device 260. The processor 270 is implemented in hardware, firmware, or a combination of hardware and software. The processor 270 is a CPU, GPU, APU, microprocessor, microcontroller, DSP, FPGA, ASIC, or another type of processing component. In some implementations, the processor 270 includes one or more processors that can be programmed to perform functions. For example, the processor 270 may transmit a signal to the modulator 280 and / or the antenna 295 that causes the transmission of one or more radar signals. Additionally or alternatively, the processor 270 may perform some pre-processing on the received signal from the demodulator 285 and / or the antenna 295 before the pre-processed signal is sent (e.g., via the communication interface 290) to another processor (e.g., the processor 210 of the device 200) for further processing. Memory 275 includes RAM, ROM, and / or another type of dynamic or static storage device (e.g., flash memory, magnetic memory, and / or optical memory) that stores information and / or instructions for use by processor 270.

[0039] The modulator 280 includes components that generate an analog signal for transmission (e.g., using the antenna 295). For example, the modulator 280 may encode a digital signal as an electromagnetic signal that may be transmitted over the air (e.g., by the antenna 295). Similarly, the demodulator 285 includes components that generate a digital signal for processing based at least in part on the analog signal (e.g., received using the antenna 295). For example, the demodulator 285 may decode a digital signal based at least in part on the electromagnetic signal received (e.g., by the antenna 295). In some implementations, the device 260 may function as a continuous wave radar (e.g., FMCW radar) such that the processor 270 and / or the modulator 280 cause the antenna 295 to transmit continuous radio waves with a stable frequency, and the demodulator 285 and / or the processor 270 filter the analog signal from the antenna 295 based at least in part on the stable frequency such that objects near the device 260 may be detected using the Doppler effect.

[0040] The communications interface 290 includes transceiver-like components (e.g., a transceiver and / or a separate receiver and transmitter) that enable the device 260 to communicate with other devices, such as via a wired connection, a wireless connection, or a combination of wired and wireless connections. The communications interface 290 may enable the device 260 to receive information from and / or provide information to another device. For example, the communications interface 290 may include an Ethernet interface, an optical interface, a coaxial interface, an infrared interface, a radio frequency interface, a USB interface, a wireless local area interface (e.g., a Wi-Fi interface), a cellular network interface, etc.

[0041] The antenna 295 includes one or more antenna elements that transmit an electromagnetic signal based at least in part on an analog signal and / or generate an analog signal based at least in part on a received electromagnetic signal. In some implementations, the antenna 295 may include or be included within one or more antenna panels, antenna groups, sets of antenna elements, and / or antenna arrays, among other examples. The antenna panels, antenna groups, sets of antenna elements, and / or antenna arrays may include one or more antenna elements. The antenna panels, antenna groups, sets of antenna elements, and / or antenna arrays may include sets of coplanar antenna elements and / or sets of non-coplanar antenna elements. The antenna panels, antenna groups, sets of antenna elements, and / or antenna arrays may include antenna elements in a single housing and / or antenna elements in multiple housings.

[0042] Device 260 may perform one or more processes described herein. Device 260 may perform these processes based on processor 270 executing software instructions stored by a non-transitory computer-readable medium, such as memory 275. A computer-readable medium is defined herein as a non-transitory memory device. A memory device includes memory space within a single physical storage device or memory space spread across multiple physical storage devices.

[0043] Software instructions may be read into memory 275 from another computer-readable medium or another device via communications interface 290. When executed, the software instructions stored in memory 275 may cause processor 270 to perform one or more processes described herein. Additionally or alternatively, hardwired circuitry may be used in place of or in combination with software instructions to perform one or more processes described herein. Thus, the aspects described herein are not limited to any specific combination of hardware circuitry and software.

[0044] In some implementations, the device 260 includes means for performing one or more processes described herein and / or means for performing one or more operations of the processes described herein. For example, the device 260 may include means for conditioning at least one measurement from the device 260. In some implementations, such means may include one or more components of the device 260 described with respect to FIG. 2B, such as the bus 265, the processor 270, the memory 275, the modulator 280, the demodulator 285, the communication interface 290, the antenna 295, etc. In some implementations, the device 260 may further include means for classifying an external object as animate or inanimate based at least in part on the at least one measurement after conditioning.

[0045] The number and arrangement of components shown in Figure 2B are provided as an example. In practice, device 260 may include additional, fewer, different, or differently arranged components than those shown in Figure 2B. Additionally or alternatively, a set of components (e.g., one or more components) of device 260 may perform one or more functions described as being performed by another set of components of device 260.

[0046] 3A is a diagram illustrating an example 300 relating to measurement correction for UE motion according to the present disclosure. As shown in FIG. 3A, the example 300 includes a UE 120. In some implementations, the UE 120 may include at least one gyroscope. For example, the UE 120 may include at least one inertial measurement unit (IMU) including at least one gyroscope and / or may include at least one stand-alone gyroscope.

[0047] The UE 120 may use at least one gyroscope to determine the angular motion 305. For example, the at least one gyroscope may output an angular velocity such that the UE 120 may determine the angular motion associated with the UE 120 by calculating an angle from the at least one gyroscope. For example, the UE 120 may use a gyro quaternion or a rotation matrix (e.g., with tilt correction and / or other corrections) to determine the angular motion 305. In some implementations, the angular motion may be defined by the amplitude and phase of the angular oscillation of the UE 120. The amplitude and phase may depend on the motion associated with the UE 120, such as motion caused by the user's heartbeat, breathing, hand tremors, and / or other similar actions.

[0048] The UE 120 may adjust at least one measurement from at least one sensor associated with the UE 120 and used to measure the relative position based at least in part on the angular motion 305. In some implementations, the at least one sensor may include an infrared sensor, one or more antennas configured to perform radio frequency radar (e.g., FMCW radar and / or other radar techniques), a camera, and / or another similar sensor used to detect and measure the relative position of an external object. Thus, the UE 120 may adjust at least one measurement based at least in part on the angular motion 305 by increasing or decreasing one or more measurements from the infrared sensor to account for the angular motion 305 of the UE 120, by increasing or decreasing one or more measurements of a reflected signal from the radar to account for the angular motion 305 of the UE 120, by mapping pixels from one measurement of the camera to pixels of another measurement from the camera to account for the angular motion 305 of the UE 120, and / or by otherwise accounting for the angular motion 305.

[0049] In some implementations, the UE 120 may further determine at least one distance between the at least one sensor and an estimated grip associated with the UE 120 (e.g., the hand grip 310 in example 300). In some aspects, the UE 120 may estimate the hand grip 310 based at least in part on measurements from at least one gyroscope, accelerometer, ambient light sensor, and / or another sensor of the UE 120. For example, as described below with respect to FIG. 7, the UE 120 may estimate an orientation of the UE 120 and estimate an axis based at least in part on the orientation. In some aspects, as described below with respect to FIG. 7, the UE 120 may further estimate the hand grip 310 and estimate an axis based at least in part on the hand grip 310. Additionally or alternatively, as described below with respect to FIG. 7, the UE 120 may further estimate one or more grip points associated with the hand grip 310 and estimate an axis based at least in part on the one or more grip points. The at least one distance may comprise a radius 315 between an axis associated with the angular motion and determined based at least in part on the hand grip 310 and a location associated with the at least one sensor. The axis may be within the volume of the UE 120 or may be outside the volume, as shown in FIG. 3A. The UE 120 may receive the location associated with the at least one sensor from a storage device (e.g., the location may be stored on a chipset of the UE 120 by an original equipment manufacturer (OEM) or an operating system (OS) developer) or may determine the location associated with the at least one sensor (e.g., based on measurements of electrical signals sent to and received from the at least one sensor by another component of the UE 120).

[0050] Thus, the UE 120 may determine at least one translation 320 associated with the at least one sensor based at least in part on the angular motion and the at least one distance. For example, the UE 120 may combine (e.g., multiply) at least a portion of the angular motion (e.g., a portion of the angular motion 305 projected along an axis associated with the radius 315, as described below) with the radius 315 to determine the at least one translation 320.

[0051] In some implementations, the UE 120 may adjust the at least one measurement by offsetting the at least one measurement based at least in part on the at least one translation 320. For example, the UE 120 may increase or decrease the at least one measurement as described above. In some implementations, the UE 120 may project the at least one translation 320 into a direction associated with the at least one sensor such that the at least one measurement is adjusted based at least in part on the projection. For example, the UE 120 may discard a component of angular motion along an axis parallel to the radius 315 and use a component of angular motion along an axis orthogonal to the radius 315 to determine the at least one translation 320.

[0052] In some implementations, the at least one sensor may include multiple sensors (e.g., two or more antennas, at least one antenna in combination with an infrared sensor and / or a camera, and / or another combination of two or more sensors). Thus, the UE 120 may determine corresponding distances (e.g., corresponding radii) and thereby corresponding translations associated with the sensors. For example, the UE 120 may project angular motion onto different axes for each sensor to calculate the corresponding translations. The UE 120 may further adjust one or more measurements from each sensor based on the corresponding translation for that sensor.

[0053] As described above, the at least one sensor may be used to measure a relative position with respect to an external object that is to be classified as animate or inanimate. Thus, the UE 120 may classify the external object as animate or inanimate based at least in part on the at least one measurement after the adjustment. For example, if the at least one measurement before the adjustment indicated animate (e.g., by satisfying an animacy threshold and / or one or more other animate conditions), the at least one measurement after the adjustment may no longer indicate animate. Similarly, if the at least one measurement before the adjustment indicated inanimate (e.g., by satisfying an inanimacy threshold and / or one or more other inanimate conditions), the at least one measurement after the adjustment may no longer indicate inanimate.

[0054] 3A, the UE 120 may correct for angular motion of the UE 120 when detecting and measuring external objects. As a result, FMCW radar and other techniques may be used to obtain more accurate measurements of nearby objects. Moreover, the UE 120 may more accurately classify external objects as animate or inanimate based on the measurements.

[0055] As noted above, Figure 3A is provided as an example, other examples may differ from those described with respect to Figure 3A.

[0056] 3B illustrates another example 300' relating to measurement correction for UE motion according to the present disclosure. Example 300' is similar to example 300 and includes UE 120 with at least one gyroscope. For example, UE 120 may include at least one IMU that includes at least one gyroscope and / or may include at least one stand-alone gyroscope.

[0057] In example 300', UE 120 may use at least one gyroscope to determine angular motion 305, as described above with respect to FIG. 3A, and adjust at least one measurement from at least one sensor associated with UE 120 and used to measure relative position based at least in part on the angular motion 305.

[0058] Additionally, in some implementations, as described above with respect to FIG. 3A, the UE 120 may further determine at least one distance between the at least one sensor and an estimated grip associated with the UE 120 (e.g., hand grips 310a and 310b in example 300′). The at least one distance may comprise a radius 315 between an axis associated with the angular motion and determined based at least in part on the hand grips 310a and 310b and a location associated with the at least one sensor.

[0059] 3A , the UE 120 may determine at least one translation 320 associated with the at least one sensor based at least in part on the angular motion and the at least one distance, and may adjust the at least one measurement by offsetting the at least one measurement based at least in part on the at least one translation 320. Thus, similar to example 300, the UE 120 in example 300′ may classify the external object as animate or inanimate based at least in part on the adjusted at least one measurement.

[0060] As noted above, Figure 3B is provided as an example, other examples may differ from those described with respect to Figure 3B.

[0061] 4 is a diagram illustrating another example 400 relating to measurement correction for UE motion according to the present disclosure. As shown in FIG. 4, the example 400 includes a UE 120. In some implementations, the UE 120 may include at least one gyroscope and at least one accelerometer. For example, the UE 120 may include at least one IMU 410 including at least one gyroscope and / or at least one accelerometer. Additionally or alternatively, the UE 120 may include at least one independent gyroscope and / or at least one independent accelerometer.

[0062] The UE 120 may determine the angular motion 405 using at least one gyroscope. For example, the at least one gyroscope may output an angular velocity such that the UE 120 may determine the angular motion associated with the UE 120 by calculating an angle from the at least one gyroscope. For example, the UE 120 may use a gyro quaternion or a rotation matrix (e.g., with tilt correction and / or other corrections) to determine the angular motion 405. In some implementations, the angular motion may be defined by an amplitude and phase of the angular oscillation of the UE 120. The amplitude and phase may depend on the motion associated with the UE 120, such as motion caused by a user's heartbeat, breathing, hand tremors, and / or other similar actions. As described above with respect to FIG. 3A, the UE 120 may adjust at least one measurement from at least one sensor associated with the UE 120 and used to measure the relative position based at least in part on the angular motion 405.

[0063] In some implementations, the UE 120 may further determine at least one linear motion of the UE 120 using at least one measurement from the at least one accelerometer. For example, the at least one linear motion may include a linear motion 415 associated with the UE 120. In some implementations, the at least one linear motion may be defined by an amplitude and a phase associated with the motion of the UE 120. The amplitude and phase may depend on the motion associated with the UE 120, such as motion caused by a user walking, running, driving, and / or other similar actions. In some implementations, the UE 120 may adjust the at least one measurement from the at least one accelerometer based at least in part on the angular motion and use the at least one adjusted measurement to determine the at least one linear motion. For example, the UE 120 may determine the at least one linear motion as described below with respect to FIG. 5.

[0064] Thus, the UE 120 may additionally or alternatively adjust at least one measurement from the at least one sensor based at least in part on the linear motion 415. In some implementations, the at least one sensor may include an infrared sensor, one or more antennas configured to perform radio frequency radar (e.g., FMCW radar and / or other radar techniques), a camera, and / or another similar sensor used to detect and measure the relative position of an external object. Thus, the UE 120 may adjust at least one measurement based at least in part on the linear motion 415 by increasing or decreasing one or more measurements from the infrared sensor to account for the linear motion 415, by increasing or decreasing one or more measurements of a reflected signal from the radar to account for the linear motion 415, by mapping pixels from one measurement of the camera to pixels of another measurement from the camera to account for the linear motion 415, and / or by otherwise accounting for the linear motion 415.

[0065] In some implementations, the UE 120 may further receive at least one relative distance between the at least one sensor and the at least one accelerometer. The at least one distance may comprise a radius 420 between a location associated with the at least one accelerometer (e.g., included in the IMU 410 in example 400) and a location associated with the at least one sensor. UE 120 may receive at least one relative distance from a memory device (e.g., the location may be stored on the UE 120's chipset by an OEM or OS developer) or may determine at least one relative distance based at least in part on a location associated with the at least one accelerometer (e.g., stored in the UE 120's memory device or transmitted to the at least one accelerometer by another component of the UE 120 and determined based on measurements of electrical signals received from the at least one accelerometer) and a location associated with the at least one sensor (e.g., stored in the UE 120's memory device or transmitted to the at least one sensor by another component of the UE 120 and determined based on measurements of electrical signals received from the at least one sensor).

[0066] Thus, the UE 120 may determine at least one translation (e.g., translation 425 in example 400) associated with the at least one sensor based at least in part on the angular motion 405, the at least one linear motion (e.g., linear motion 415 in example 400), and the at least one relative distance (e.g., radius 420 in example 400). For example, the UE 120 may calculate a combination (e.g., multiplication) of at least a portion of the angular motion (e.g., a portion of the angular motion 405 projected along an axis associated with the radius 420, as described below) with the radius 420 and further combine (e.g., add) the calculation with the at least one linear motion (e.g., linear motion 415) to determine the at least one translation 425. Thus, the at least one translation 425 of the IMU 410 may include a vector sum of the linear motion 415 of the UE 120 with a translation based at least in part on the angular motion 405.

[0067] In some implementations, the UE 120 may additionally or alternatively adjust the at least one measurement by offsetting the at least one measurement based at least in part on the at least one translation 425. For example, the UE 120 may increase or decrease the at least one measurement as described above. In some implementations, the UE 120 may project the at least one translation 425 into a direction associated with the at least one sensor such that the at least one measurement is adjusted based at least in part on the projection. For example, the UE 120 may discard a component of angular motion along an axis parallel to the radius 420 and use a component of angular motion along an axis orthogonal to the radius 420 to determine the at least one translation 425 (e.g., as described above).

[0068] As described above, the at least one sensor may be used to measure a relative position with respect to an external object that is to be classified as animate or inanimate. Thus, the UE 120 may classify the external object as animate or inanimate based at least in part on the at least one measurement after the adjustment. For example, if the at least one measurement before the adjustment indicated animateness (e.g., by satisfying an animateness threshold and / or one or more other animateness conditions), the at least one measurement after the adjustment may no longer indicate animateness. Similarly, if the at least one measurement before the adjustment indicated inanimateness (e.g., by satisfying an inanimateness threshold and / or one or more other animateness conditions), the at least one measurement after the adjustment may no longer indicate inanimateness.

[0069] 4, the UE 120 may compensate for its linear motion when detecting and measuring external objects. As a result, FMCW radar and other techniques may be used to obtain more accurate measurements of nearby objects. Moreover, the UE 120 may more accurately classify external objects as animate or inanimate based on the measurements.

[0070] Example 400 may be combined with example 300 and / or 300'. In some implementations, UE 120 may determine at least one translation associated with at least one sensor based at least in part on an estimated grip associated with UE 120 (e.g., as described above with respect to FIGS. 3A-3B) and determine at least one translation associated with at least one sensor based at least in part on at least one relative distance between the at least one sensor and the at least one accelerometer (e.g., as described above with respect to FIG. 4). Thus, UE 120 may adjust at least one measurement by offsetting at least one measurement based at least in part on both translations. For example, UE 120 may combine (e.g., add) both translations and adjust at least one measurement accordingly.

[0071] As noted above, Figure 4 is provided as an example. Other examples may differ from those described with respect to Figure 4.

[0072] 5 illustrates an example 500 relating to determining linear translation from gyroscope and accelerometer measurements in accordance with the present disclosure. As shown in FIG. 5, the UE (e.g., UE 120) in example 500 may use measurements from at least one accelerometer of an IMU and measurements from at least one gyroscope of an IMU. Additionally or alternatively, the UE 120 in example 500 may use measurements from at least one independent accelerometer and / or measurements from at least one independent gyroscope.

[0073] As shown in FIG. 5, the angular velocity (in FIG. 5 ) of at least one IMU (or body) b and coordinated with respect to an inertial frame i is

[0074]

number

[0075] The angular velocity of the earth (represented as

[0076]

number

[0077] , which is the angular velocity of the Earth, e, and coordinated with respect to an inertial frame, i, and is corrected (e.g., via tensor multiplication) to account for the angular velocity of at least one IMU coordinated with respect to a navigational frame, n (in FIG. 5 ,

[0078]

number

[0079] ) can be obtained.

[0080] As further shown in FIG. 5, the acceleration (in FIG. 5 ) of at least one IMU (or body) b and coordinated with respect to an inertial frame i

[0081]

number

[0082] ) is measured by at least one accelerometer. This acceleration is expressed as the attitude of the body b with respect to the navigation frame n (in FIG. 5

[0083]

number

[0084] 5 ) to obtain the acceleration of the navigation frame n relative to the inertial frame i (

[0085]

number

[0086] ) can be obtained. A specific force can be determined from the integral of the angular velocity of the at least one IMU coordinated with respect to the navigation frame n (e.g., using a gyro quaternion or rotation matrix). The forward velocity of the at least one IMU (v in FIG. 5) can be obtained from the integral of the angular velocity of the at least one IMU coordinated with respect to the navigation frame n (e.g., using a gyro quaternion or rotation matrix). n-1 ) is the forward angular velocity of the navigation frame n relative to the Earth e (in Figure 5

[0087]

number

[0088] The previous velocity may be adjusted for the Coriolis effect (e.g., the previous velocity v n-1 In Fig. 5,

[0089]

number

[0090] This is done by crossing it with

[0091]

number

[0092] represents the angular velocity of the navigation frame n relative to the Earth e,

[0093]

number

[0094] represents the angular velocity of the Earth e relative to the inertial frame i). Therefore, the acceleration of the navigation frame n (in Figure 5

[0095]

number

[0096] ), the adjusted previous velocity, and the gravity vector (γ n ) is synthesized using numerical integration to obtain the current velocity (v in Figure 5) of at least one IMU. n In addition, the current velocity can be calculated based on the position in front of the IMU (p in FIG. 5). n-1 ) is numerically integrated and synthesized to obtain the current position of the IMU (p in Figure 5). n For example, the current position may be in curvilinear coordinates, and thus in FIG.

[0097]

number

[0098] , λ, and h.

[0099] As noted above, Figure 5 is provided as an example. Other examples may differ from those described with respect to Figure 5.

[0100] FIG. 6 is a flow chart of an example process 600 related to detecting and correcting angular and linear motion. In some implementations, one or more process blocks of FIG. 6 may be performed by a UE (e.g., UE 120). In some implementations, one or more process blocks of FIG. 6 may be performed by another device or group of devices separate from or including the UE, such as a gyroscope (e.g., gyroscope 240), an accelerometer (e.g., accelerometer 245), an object detector (e.g., object detector 250), and / or a position sensor (e.g., position sensor 255). Additionally or alternatively, one or more process blocks of FIG. 6 may be performed by one or more components of device 200, such as bus 205, processor 210, memory 215, storage component 220, input component 225, output component 230, and / or communication interface 235.

[0101] 6, process 600 may include determining angular motion of the UE (block 610). For example, the UE may determine the angular motion using at least one gyroscope (e.g., gyroscope 240), as described above.

[0102] 6, process 600 may include adjusting at least one measurement from at least one sensor associated with the UE and used to measure the relative position based at least in part on the angular motion (block 620). For example, the UE may adjust at least one measurement from the at least one sensor based at least in part on the angular motion (e.g., using processor 210) as described above.

[0103] Process 600 may include additional implementations, such as any single implementation or any combination of implementations described below and / or with respect to one or more other processes described elsewhere herein.

[0104] In a first implementation, the relative position is with respect to an external object that is to be classified as animate or inanimate.

[0105] In a second implementation, alone or in combination with the first implementation, the process 600 further includes classifying the external object as animate or inanimate based at least in part on the at least one adjusted measurement (e.g., using the processor 210).

[0106] In a third implementation, alone or in combination with one or more of the first and second implementations, at least one gyroscope is included in at least one IMU of the UE.

[0107] In a fourth implementation, alone or in combination with one or more of the first through third implementations, determining the angular motion includes calculating an angle from at least one gyroscope of the UE.

[0108] In a fifth implementation, alone or in combination with one or more of the first to fourth implementations, the angular motion is defined by an amplitude and a phase of an angular oscillation of the UE.

[0109] In a sixth implementation, alone or in combination with one or more of the first through fifth implementations, the process 600 further includes determining (e.g., using the processor 210) at least one distance between the at least one sensor and an estimated grip associated with the UE.

[0110] In a seventh implementation, alone or in combination with one or more of the first through sixth implementations, the process 600 further includes determining (e.g., using the processor 210) at least one translation associated with the at least one sensor based at least in part on the angular motion and the at least one distance.

[0111] In an eighth implementation, alone or in combination with one or more of the first through seventh implementations, adjusting the at least one measurement includes offsetting the at least one measurement based at least in part on the at least one translation.

[0112] In a ninth implementation, alone or in combination with one or more of the first to eighth implementations, the process 600 further includes projecting (e.g., using the processor 210) the at least one translation into a direction associated with the at least one sensor, and the at least one measurement value is adjusted based at least in part on the projection.

[0113] In a tenth implementation, alone or in combination with one or more of the first through ninth implementations, the process 600 further includes determining at least one linear motion of the UE using at least one measurement from at least one accelerometer of the UE (e.g., using the processor 210), wherein the at least one measurement from the at least one sensor is adjusted based at least in part on at least one translation associated with the at least one sensor determined from the angular motion and the at least one linear motion.

[0114] In an eleventh implementation, alone or in combination with one or more of the first through tenth implementations, at least one accelerometer is included in at least one IMU of the UE.

[0115] In a twelfth implementation, alone or in combination with one or more of the first through eleventh implementations, determining the at least one linear motion includes adjusting at least one measurement from the at least one accelerometer based at least in part on the angular motion, and determining the at least one linear motion using the at least one adjusted measurement.

[0116] In a thirteenth implementation, alone or in combination with one or more of the first to twelfth implementations, at least one linear motion is defined by an amplitude and a phase associated with the movement of the UE.

[0117] In a fourteenth implementation, alone or in combination with one or more of the first through thirteenth implementations, the process 600 further includes receiving (e.g., using the memory 215, the storage component 220, and / or the input component 225) at least one relative distance between the at least one sensor and the at least one accelerometer.

[0118] In a fifteenth implementation, alone or in combination with one or more of the first through fourteenth implementations, the process 600 further includes determining (e.g., using the processor 210) at least one translation associated with the at least one sensor based at least in part on the angular motion, the at least one linear motion, and the at least one relative distance.

[0119] In a sixteenth implementation, alone or in combination with one or more of the first to fifteenth implementations, the process 600 further includes projecting (e.g., using the processor 210) the at least one translation into a direction associated with the at least one sensor, and the at least one measurement value is adjusted based at least in part on the projection.

[0120] In a seventeenth implementation, alone or in combination with one or more of the first through sixteenth implementations, the at least one sensor includes a radar device, and conditioning the at least one measurement includes conditioning a signal from the radar device.

[0121] 6 illustrates example blocks of process 600, in some implementations process 600 may include additional, fewer, different, or differently arranged blocks compared to those illustrated in FIG 6. Additionally or alternatively, two or more of the blocks of process 600 may be performed in parallel.

[0122] 7 is a flowchart of an example process 700 related to hand grip determination. In some implementations, one or more process blocks of FIG. 7 may be performed by a UE (e.g., UE 120). In some implementations, one or more process blocks of FIG. 7 may be performed by one or more components of device 200, such as bus 205, processor 210, memory 215, storage component 220, input component 225, output component 230, and / or communication interface 235.

[0123] As shown in FIG. 7, process 700 may include determining an orientation of the UE (block 710). For example, the UE may determine the orientation using at least one gyroscope (e.g., gyroscope 240), as described above. Additionally or alternatively, the UE may determine the orientation using an ambient light sensor, an accelerometer (e.g., accelerometer 245), and / or another sensor. In some aspects, the orientation may include a portrait orientation, a landscape orientation, and / or another orientation of the UE. Thus, the UE may estimate an orientation based at least in part on one or more measurements from the gyroscope, the accelerometer, the ambient light sensor, and / or another sensor.

[0124] As further shown in FIG. 7, process 700 may include classifying a grip type associated with the UE (block 720). For example, the UE may classify the grip type based at least in part on orientation (e.g., using processor 210), as described above. In some aspects, the UE may apply machine learning to determine the grip type. For example, the UE may classify the grip type based at least in part on measurements from a gyroscope, an accelerometer, an ambient light sensor, and / or another sensor using a regression classifier, a neural network, and / or another trained model. In some aspects, the classification may include whether the UE is on the body of a user of the UE (e.g., in the user's hand or balanced on the user's leg or other limb), in the clothing of a user of the UE, and / or in another position. Additionally or alternatively, the classification may include one hand grip in landscape mode (e.g., right hand grip or left hand grip), two hand grips in landscape mode (e.g., as shown in FIG. 3B), one hand grip in portrait mode (e.g., as shown in FIG. 3A), and / or another grip type.

[0125] As further shown in FIG. 7, process 700 may include determining one or more grip points associated with the UE (block 730). For example, the UE may determine the grip point based at least in part on the orientation and / or hand grip (e.g., using processor 210), as described above. In some aspects, the UE may apply machine learning to determine the grip point. For example, the UE may determine the one or more grip points based at least in part on measurements from a gyroscope, an accelerometer, an ambient light sensor, and / or another sensor using a regression classifier, a neural network, and / or another trained model.

[0126] Based at least in part on the orientation, grip type, and / or one or more grip points, the UE may estimate an axis associated with the angular motion of the UE, which the UE may then use to perform angular and linear motion detection and correction, as described elsewhere herein.

[0127] Process 700 may include additional implementations, such as any single implementation or any combination of implementations described below and / or with respect to one or more other processes described elsewhere herein.

[0128] 7 illustrates example blocks of process 700, in some implementations process 700 may include additional, fewer, different, or differently arranged blocks compared to those shown in FIG 7. Additionally or alternatively, two or more of the blocks of process 700 may be performed in parallel.

[0129] The following provides a summary of several aspects of the disclosure.

[0130] Aspect 1: A method of motion detection performed by a user equipment (UE), comprising: determining angular motion using at least one gyroscope of the UE; and adjusting at least one measurement from at least one sensor associated with the UE and used to measure relative position based at least in part on the angular motion.

[0131] Aspect 2: The method of aspect 1, wherein the relative position is with respect to an external object that is to be classified as animate or inanimate.

[0132] Aspect 3: The method of aspect 2, further comprising classifying the external object as animate or inanimate based at least in part on the adjusted at least one measurement.

[0133] Example 4: The method of any of Examples 1-3, wherein the at least one gyroscope is included in at least one inertial measurement unit of the UE.

[0134] Aspect 5: The method of any of aspects 1-4, wherein determining the angular motion includes calculating angles from at least one gyroscope of the UE.

[0135] Aspect 6: The method of any of aspects 1-5, wherein the angular motion is defined by an amplitude and a phase of an angular oscillation of the UE.

[0136] Aspect 7: The method of any of aspects 1-6, further comprising determining at least one distance between at least one sensor and an estimated grip associated with the UE.

[0137] Aspect 8: The method of aspect 7, further comprising determining at least one translation associated with the at least one sensor based at least in part on the angular motion and the at least one distance.

[0138] Aspect 9: The method of aspect 8, wherein adjusting the at least one measurement comprises offsetting the at least one measurement based at least in part on the at least one translation.

[0139] Aspect 10: The method of any of aspects 8-9, wherein the method further includes projecting the at least one translation into a direction associated with the at least one sensor, and wherein the at least one measurement is adjusted based at least in part on the projection.

[0140] Aspect 11: The method of any of aspects 1-10, further comprising determining at least one linear motion of the UE using at least one measurement from at least one accelerometer of the UE, wherein the at least one measurement from the at least one sensor is adjusted based at least in part on at least one translation associated with the at least one sensor determined from the angular motion and the at least one linear motion.

[0141] Example 12: The method of example 11, wherein the at least one accelerometer is included in at least one inertial measurement unit of the UE.

[0142] Aspect 13: The method of any of aspects 11-12, wherein the step of determining the at least one linear motion includes the steps of adjusting at least one measurement from the at least one accelerometer based at least in part on the angular motion, and determining the at least one linear motion using the at least one adjusted measurement.

[0143] Example 14: The method of any of Examples 11-13, wherein the at least one linear motion is defined by an amplitude and phase associated with the movement of the UE.

[0144] Aspect 15: The method of any of aspects 11-14, further comprising receiving at least one relative distance between the at least one sensor and the at least one accelerometer.

[0145] Aspect 16: The method of aspect 15, further comprising determining at least one translation associated with the at least one sensor based at least in part on the angular motion, the at least one linear motion, and the at least one relative distance.

[0146] Aspect 17: The method of aspect 16, wherein the method further includes projecting the at least one translation into a direction associated with the at least one sensor, and wherein the at least one measurement is adjusted based at least in part on the projection.

[0147] Aspect 18: The method of any of aspects 1-17, wherein the at least one sensor includes a radar device, and wherein adjusting the at least one measurement includes adjusting a signal from the radar device.

[0148] Aspect 19: An apparatus for wireless communication in a device, comprising: a processor; a memory coupled to the processor; and instructions stored in the memory and executable by the processor to cause the apparatus to perform a method of one or more of aspects 1-18.

[0149] Aspect 20: A device for wireless communication comprising a memory and one or more processors coupled to the memory, wherein the memory and the one or more processors are configured to perform the method of one or more of aspects 1-18.

[0150] Aspect 21: An apparatus for wireless communication, comprising at least one means for performing the method of one or more of aspects 1-18.

[0151] Aspect 22: A non-transitory computer-readable medium storing code for wireless communication, the code comprising instructions executable by a processor to perform a method of one or more of aspects 1-18.

[0152] Aspect 23: A non-transitory computer-readable medium storing a set of instructions for wireless communication, the set of instructions comprising one or more instructions that, when executed by one or more processors of a device, cause the device to perform a method of one or more of aspects 1-18.

[0153] The above disclosure provides illustration and description, but is not intended to be exhaustive or to limit the embodiments to the precise form disclosed. Modifications and variations may be made in light of the above disclosure or may be acquired from practice of the embodiments.

[0154] As used herein, the term "component" shall be broadly construed as hardware, firmware, and / or a combination of hardware and software. As used herein, a processor is implemented in hardware, firmware, and / or a combination of hardware and software. It will be apparent that the systems and / or methods described herein may be implemented in different forms of hardware, firmware, and / or a combination of hardware and software. The actual dedicated control hardware or software code used to implement these systems and / or methods is not limiting of the aspects. Thus, the operation and behavior of the systems and / or methods are described herein without reference to specific software code. It should be understood that software and hardware can be designed to implement the systems and / or methods based at least in part on the description herein.

[0155] As used herein, "meeting a threshold" can refer to a value being greater than the threshold, greater than or equal to the threshold, less than the threshold, less than or equal to the threshold, equal to the threshold, not equal to the threshold, etc., depending on the context.

[0156] Although certain combinations of features are recited in the claims and / or disclosed herein, these combinations do not limit the disclosure of the various aspects. In fact, many of these features may be combined in ways not specifically recited in the claims and / or disclosed herein. Although each dependent claim listed below may directly depend on only one claim, the disclosure of the various aspects includes each dependent claim in combination with every other claim in the claim set. As used herein, a phrase referring to "at least one of" a list of items refers to any combination of those items, including single members. As an example, "at least one of a, b, or c" is intended to cover a, b, c, ab, ac, bc, and abc, as well as any combination having multiple identical elements (e.g., aa, aaa, aab, aac, abb, acc, bb, bbb, bbc, cc, and ccc, or any other order of a, b, and c).

[0157] No element, act, or instruction used herein should be construed as critical or essential unless expressly described as such. Also, as used herein, the articles "a" and "an" shall include one or more items and may be used interchangeably with "one or more." Additionally, as used herein, the article "the" shall include one or more items referred to with the article "the" and may be used interchangeably with "one or more." Additionally, as used herein, the terms "set" and "group" shall include one or more items (e.g., related items, unrelated items, or a combination of related and unrelated items) and may be used interchangeably with "one or more." When only one item is intended, the phrase "only one" or similar language is used. Also, as used herein, terms such as "has," "have," and "having" are intended to be open-ended terms. Additionally, the phrase "based on" shall mean "based at least in part on," unless otherwise specified. Additionally, as used herein, the term "or" is intended to be inclusive when used in a consecutive manner, and may be used interchangeably with "and / or" unless otherwise noted (e.g., when used in combination with "either" or "only one of"). [Explanation of symbols]

[0158] 100 Environment, e.g. 110 base station 112-1, 112-2, 295 Antenna 120UE, target 200, 260 devices 205, 265 Bus 210, 270 processor 215, 275 memory 220 Memory Components 225 Input Components 230 Output Components 235, 290 Communication interface 240 Gyroscope 245 Accelerometer 250 Object Detector 255 Position Sensor 280 Modulator 285 Demodulator 305, 405 Angular motion 310, 310a, 310b Hand Grips 315, 420 radius 320, 425 translation 410 IMU 415 Linear motion

Claims

1. 1. A method of motion detection performed by a user equipment (UE), comprising: determining angular motion using at least one gyroscope of the UE; adjusting at least one measurement from at least one sensor associated with the UE and used to measure a relative position based at least in part on the angular motion; Including, The relative position is with respect to an external object that is to be classified as animate or inanimate. method.

2. classifying the external object as animate or inanimate based at least in part on the adjusted at least one measurement. The method of claim 1, further comprising:

3. the at least one gyroscope is included in at least one inertial measurement unit of the UE; and / or wherein determining the angular motion comprises calculating an angle from the at least one gyroscope of the UE. The method of claim 1 , wherein the angular motion is defined by an amplitude and a phase of an angular oscillation of the UE.

4. determining at least one distance between the at least one sensor and an estimated grip associated with the UE; The method of claim 1, further comprising:

5. determining at least one translation associated with the at least one sensor based at least in part on the angular motion and the at least one distance.

5. The method of claim 4, further comprising:

6. The method of claim 5 , wherein adjusting the at least one measurement comprises offsetting the at least one measurement based at least in part on the at least one translation.

7. The method further comprising: projecting the at least one translation onto a direction associated with the at least one sensor. Further comprising: The method of claim 5 , wherein the at least one measurement is adjusted based at least in part on the projection.

8. The method further comprising: determining at least one linear movement of the UE using at least one measurement from at least one accelerometer of the UE; Further comprising: The at least one measurement from the at least one sensor is adjusted based at least in part on at least one translation associated with the at least one sensor determined from the angular motion and the at least one linear motion, and optionally, determining the at least one linear motion includes adjusting the at least one measurement from the at least one accelerometer based at least in part on the angular motion and determining the at least one linear motion using the at least one adjusted measurement. The method of claim 1.

9. The at least one accelerometer is included in at least one inertial measurement unit of the UE, and / or the at least one linear motion is defined by an amplitude and a phase associated with a movement of the UE. The method of claim 8.

10. receiving at least one relative distance between the at least one sensor and the at least one accelerometer; 9. The method of claim 8, further comprising:

11. determining at least one translation associated with the at least one sensor based at least in part on the angular motion, the at least one linear motion, and the at least one relative distance. and optionally further including: projecting the at least one translation onto a direction associated with the at least one sensor. Further comprising: The method of claim 10 , wherein the at least one measurement is adjusted based at least in part on the projection.

12. The method of claim 1 , wherein the at least one sensor includes a radar device, and conditioning the at least one measurement includes conditioning a signal from the radar device.

13. A user equipment (UE), Memory, and one or more processors operably coupled to the memory, wherein the memory and the one or more processors: determining angular motion using at least one gyroscope; and adjusting at least one measurement from at least one sensor associated with the UE and used to measure a relative position based at least in part on the angular motion. wherein the relative position is with respect to an external object that is to be classified as animate or inanimate. U.E.

14. The method according to claim 2, further comprising: The UE of claim 13.

15. 1. A non-transitory computer readable medium storing a set of instructions for wireless communication, the set of instructions comprising: When executed by one or more processors of a user equipment (UE), the UE is caused to carry out the method of any one of claims 1 to 12. A non-transitory computer-readable recording medium.

Images