Patent Description:
Cars are ubiquitous in today's society. For various reasons, including to prevent theft or unauthorized use, authentications mechanisms have been developed to control who can enter and/or operate a particular car.

In conventional cars, a lock is placed in the door handle to prevent unauthorized entry to the car, where a corresponding key (i.e., a metallic key) is used to open or close the lock. An additional lock is placed near the steering wheel to prevent unauthorized operation of the car, where a corresponding key is used to allow the car to turn on. In many cars, the same key is used to open the car and to operate the car.

With the advance of technology, wireless authentication mechanisms to control entry of the car are now common. For example, a remote control may be used to open the car. Some cars rely on a proximity sensor that is triggered when a transponder car key is within a certain distance of the car. Typically, authentication for remote controls and transponder car keys rely on encrypted communication.

In some cars, the remote control or transponder key may be used to enable the car to start the engine when the remote control is near the car (known as keyless ignition).

User authentication mechanisms for cars that rely on a physical key may be susceptible to unauthorized entry or operation if such physical key is lost or stolen. Patent document <NUM>, <CIT>, relates to methods and systems for interacting with and controlling a vehicle using smartphones or similar portable telecommunications devices. Patent document <NUM>, <CIT>, relates to an apparatus and a method for radar-based gesture detection. Patent document <NUM>, <CIT>, relates to a method for operating a driver assistance system to support at least one person outside a motor vehicle by activating at least one vehicle system to carry out at least one measure. Document <NUM>, <NPL>], relates to a method of using mm-wave sensors to identify various individuals. Patent document <NUM>, <CIT>, relates to a radio frequency system that is a part of a gesture sensing system of a wearable consumer device. Patent document <NUM>, <CIT>, which is considered closest prior art, relates to a fingerprint identification module and a fingerprint identification method. The subject-matter of the independent claims differs over the disclosure of patent document D6 essentially in that the RF or radar sensor does not determine the proximity of the user or user's hand as a requirement before measuring the fingerprint; instead the radar sensor is activated when the capacitive sensor determines that the fingerprint does not match with the stored fingerprint. Patent document <NUM>, <CIT>, relates to azimuth determination with the aid of a radar sensor. Patent document <NUM>, <CIT>, relates to a radar system including an antenna array for transmitting and receiving electromagnetic radiation. Patent document <NUM>, <CIT>, relates to an operating assembly for a motor vehicle with operating device in a steering wheel rim.

There may be a demand for providing an improved concept for a method for authenticating a user of a car, a millimeter-wave radar, and a millimeter-wave radar system.

Such a demand may be satisfied by the subject matter of any of the claims.

In accordance with an embodiment of the invention as claimed in claim <NUM>, a method for authenticating a user of a car includes: after detecting by a millimeter-wave radar of the car the proximity of a user to the car, transmitting a plurality of radiation pulses through a predetermined portion of a surface of the car towards a portion of a hand of the user using the millimeter-wave radar of the car; receiving a reflected signal from the portion of the hand using the millimeter-wave radar; generating a fingerprint signature based on the reflected signal; comparing the fingerprint signature to a database of authorized fingerprint signatures; and authorizing the user based on whether the fingerprint signature matches an authorized fingerprint signature of the database of authorized fingerprint signatures.

In accordance with an embodiment as claimed in independent claim <NUM>, millimeter-wave radar for a car, configured to detect proximity of a user to the car, includes: two transmitting antennas configured to after detecting the proximity of the user, transmit a plurality of radiation pulses through a predetermined portion of a surface of the car towards a portion of a hand of a user; two receiving antennas configured to receive a reflected signal from the portion of the hand corresponding to the transmitted plurality of radiation pulses; and a processor. The processor is configured to: generate a fingerprint signature based on the reflected signal, compare the generated fingerprint signature to a database of authorized fingerprint signatures, and authorize access to the car based on whether the fingerprint signature matches an authorized fingerprint signature of the database of authorized fingerprint signatures.

In accordance with an embodiment as claimed in independent claim <NUM>, a millimeter-wave radar system for a car includes a first millimeter-wave radar configured to detect a proximity of a user to the car, a second millimeter-wave radar, a first processor, and a second processor. The first millimeter-wave radar includes: a first transmitting antenna configured to, after detecting the proximity of the user, generate a plurality of radiation pulses through a portion of a handle of the car towards a portion of a hand of a user, a first receiving antenna configured to receive a first reflected signal from the portion of the hand corresponding to the plurality of radiation pulses transmitted by the first transmitted antenna. The first processor is configured to: generate a fingerprint signature based on the first reflected signal, compare the generated fingerprint signature to a database of authorized fingerprint signatures, and authorize access to the car based on whether the fingerprint signature matches an authorized fingerprint signature of the database of authorized fingerprint signatures. The second millimeter-wave radar includes: two transmitting antennas configured to generate a plurality of radiation pulses through a predetermined portion of a steering wheel of the car, two receiving antennas configured to receive a second reflected signal corresponding to the plurality of radiation pulses transmitted by the two transmitting antennas. The second processor is configured to: generate a gesture signature based on the second reflected signal, compare the generated gesture signature to a predetermined authorized gesture signature, and start an engine of the car based on whether the gesture signature matches the predetermined authorized gesture signature.

In an embodiment of the present invention, a millimeter-wave radar system is used to determine whether a human requesting access to a car is authorized to access the car. The millimeter-wave radar system captures a fingerprint of the human after the human touches, e.g., a handle of the car. The millimeter-wave radar then compares the captured fingerprint to a database of authorized fingerprint to determine whether the captured fingerprint matches an authorized fingerprint. As a second mode of authentication, when the millimeter-wave radar system determines that the fingerprint of the human matches an authorized fingerprint, the millimeter-wave radar system monitors a gesture of a finger of the human and compares the gesture to a predetermined gesture. When the gesture of the finger matches the predetermined gesture (where the predetermined gesture may be associated with the fingerprint of the human), access to the car is granted.

Using a millimeter-wave radar to control access to the car advantageously allows access to the car to authorized user while preventing access to the car to unauthorized users without relying on physical keys, such as metallic keys or remote keys. By avoiding the use of a physical key to authorize access to the car, unauthorized access to the car associated with the theft of the physical key, for example, is eliminated. By using an additional second mode of authentication, unauthorized access associated with, e.g., replication of an authorized fingerprint, is reduced. In some embodiments, the two modes of authentication are performed using a single millimeter-wave radar.

<FIG> shows car <NUM> having millimeter-wave radar system <NUM>, according to an embodiment of the present invention. Millimeter wave radar system <NUM> includes millimeter-wave radar <NUM>, and processor <NUM>. <FIG> illustrate a flow chart of embodiment method <NUM> for authenticating a user, according to an embodiment of the present invention. <FIG> may be understood in view of <FIG>.

During step <NUM>, human <NUM> approaches car <NUM>.

According to the invention as claimed, the proximity of human <NUM> is detected using millimeter-wave radar <NUM> by detecting a moving object approaching car <NUM> (using, e.g., range FFT and tracking object movements, e.g., in slow time). In yet other embodiments, the proximity of human <NUM> is detected by detecting a touch in a surface of car <NUM>, such as a surface of a handle of car <NUM> (e.g., during step <NUM>).

During step <NUM>, human <NUM> touches a surface of car <NUM>, where millimeter-wave radar <NUM> has a field-of-view that includes such surface. In some embodiments, such surface includes a portion of a surface of a handle of car <NUM>. In other embodiments, such surface includes a portion of a door, window, or roof of car <NUM>. For example, in some embodiments, car <NUM> may include a scanning plaque (e.g., a plastic scanning plaque), where millimeter-wave radar <NUM> scans the fingerprint when a finger is in contact with the scanning plaque. Other surfaces of car <NUM> may also be used.

During step <NUM>, while human <NUM> is touching, e.g., the handle of car <NUM>, millimeter-wave radar <NUM> transmits a plurality of radiation pulses <NUM>, such as chirps (e.g., linear chirps), through the handle of car <NUM> and towards a finger in contact with the handle to capture fingerprint <NUM>. The transmitted radiation pulses are reflected by the finger of human <NUM>. The reflected radiation pulses (not shown in <FIG>), which are also referred to as the echo signal, are detected by millimeter-wave radar <NUM> and processed by processor <NUM> to generate a fingerprint signature (i.e., a digital representation). The fingerprint signature is configured to identify a person, advantageously uniquely. Millimeter-wave radar system <NUM> (e.g., using processor <NUM>) then compares the fingerprint signature to authorized fingerprint signatures stored in database <NUM> to determine whether the fingerprint signature matches any of the authorized signatures stored in database <NUM>.

When millimeter-wave radar system <NUM> (e.g., using processor <NUM>) determines that the fingerprint signature matches an authorized fingerprint signature of database <NUM>, millimeter-wave radar system <NUM> (e.g., using processor <NUM>) authenticates human <NUM> and authorizes access to car <NUM> (e.g., by unlocking the doors of car <NUM>) during step <NUM>. If the fingerprint signature does not match any authorized fingerprint signatures in database <NUM>, millimeter-wave radar system <NUM> then detects an intrusion attempt during step <NUM> and takes appropriate action (e.g., reporting intrusion to owner of record via a smartphone app, sounding an alarm, or other action). In some embodiments, a predetermined number of attempts (e.g., <NUM> attempts) are allowed during step <NUM> before detecting an intrusion during step <NUM>.

In some embodiments, more than one authorized fingerprint signatures are associated with an authorized user (e.g., for different fingers of the same human).

In some embodiments, the fingerprint signature is representative of a fingerprint such as fingerprint <NUM>. For instance, it includes details associated with the topology of the finger surface, including the ridges and valleys commonly associated with a fingerprint. In some embodiments, characteristics of additional or biological structures other than such details, e.g., up to a depth of <NUM>, are captured and included in a fingerprint signature. In some embodiments, instead of or in addition to being representative of common fingerprint characteristics, the fingerprint signature is representative of the way the body part that generated the signature is placed in space and/or on a surface.

In some embodiments, the fingerprint includes the scanning of the topology of the skin and other biological structures located in other portions of the hand (e.g., the palm of the hand) instead of or in addition to the finger. Other elements of the human body may be used to generate a fingerprint.

In some embodiments, a second mode of authentication is used after a fingerprint match is found and before granting access to car <NUM> (e.g., steps <NUM> and/or step <NUM>). For example, during step <NUM>, millimeter-wave radar <NUM> monitors a predetermined area for gestures, such as finger gesture <NUM>. For example, in some embodiments, millimeter-wave radar <NUM> transmits a plurality of radiation pulses <NUM> through the handle of car <NUM> and towards a finger to capture finger gesture <NUM>. The transmitted radiation pulses are reflected by the finger of human <NUM>. The reflected radiation pulses (not shown in <FIG>) are detected by millimeter-wave radar <NUM> and processed by processor <NUM> to generate a gesture signature (i.e., a digital representation) corresponding to finger gesture <NUM>. Millimeter-wave radar system <NUM> (e.g., using processor <NUM>) then compares the gesture signature to an authorized gesture signature, such as an authorized gesture signature stored in database <NUM>, to determine whether the gesture signature matches any of the authorized gesture signatures in database <NUM>.

When millimeter-wave radar system <NUM> (e.g., using processor <NUM>) determines that the gesture signature matches an authorized gesture signature, millimeter-wave radar system <NUM> (e.g., using processor <NUM>) authorizes access to car <NUM> (e.g., by unlocking the doors of car <NUM>) during step <NUM>. If the gesture signature does not match any authorized gesture signatures in database <NUM>, millimeter-wave radar system <NUM> then detects an intrusion during step <NUM> and takes appropriate action (e.g., reporting intrusion to owner of record via a smartphone app, sounding an alarm, or other action). In some embodiments, a predetermined number of attempts (e.g., <NUM> attempts) are allowed during step <NUM> before detecting an intrusion during step <NUM>.

In some embodiments, database <NUM> includes a single authorized gesture signatures associated with a particular authorized user. Such authorized user may be identified using a fingerprint signature during step <NUM>. For example, in some embodiments, database <NUM> includes a first authorized gesture associated with a first authorized human, and a second authorized gesture associated with a second authorized human. When the first authorized human is detected during step <NUM>, only the first authorized gesture results in a match during step <NUM>. Other embodiments may include a plurality of authorized gesture signatures associated with the particular authorized user. In some embodiments, one or more authorized gesture signatures may be independent (i.e., not associated with a particular authorized user).

In some embodiments, instead of using database <NUM> to of authorized gesture signatures for authenticating the user, an authorized gesture signature is automatically, randomly or pseudo-randomly, generated and delivered to an authorized smartphone (e.g., after a fingerprint match is found during step <NUM>). Such automatically generated gesture signature has an expiration time (e.g., <NUM> minutes). In other words, if, during step <NUM>, millimeter-wave radar <NUM> does not capture the automatically generated gesture within the expiration time, an intrusion attempt may be detected (step <NUM>).

In some embodiments, finger gesture <NUM> is performed, for example, in the air. In some embodiments, finger gesture <NUM> is performed while the finger is in contact with a surface, such as the surface of the handle of car <NUM>. In some embodiments, the gesture is performed in a projected unlock area, such as an area projected (e.g., with light) in a window of car <NUM> (e.g., a pattern may be projected in the window of the car). In some embodiments, an additional millimeter-wave radar (not shown in <FIG>) is used for detecting the gesture of the finger.

In some embodiments, millimeter-wave radar <NUM> determines the location of the finger performing the gesture, and performs a corresponding finger location tracking by periodically determining the range component of the finger using range FFT and determining the azimuth component of the azimuth component of the finger by determining the angle of arrival, e.g., using a mono-pulse algorithm. In some embodiments, the Doppler velocity of the finger is also determined and used as part of the gesture recognition signature. Other gesture tracking mechanisms may also be used.

In some embodiments, millimeter-wave radar <NUM> advantageously performs both modes of authentication (steps <NUM> and <NUM>) without additional sensors.

Some embodiments may implement, instead of or in addition to the gesture recognition of step <NUM>, a facial recognition (step <NUM>) as a second mode of authentication. For example, during step <NUM>, an additional millimeter-wave radar (not shown in <FIG>) may be disposed in car <NUM> at a height suitable to reach a face of human <NUM> (e.g., such as in a roof of car <NUM>, or on a top portion of a door of car <NUM>).

The additional millimeter-wave radar transmits a plurality of radiation pulses <NUM> towards the face of human <NUM> to capture facial characteristics <NUM>, e.g., using time-of-flight (ToF) facial recognition. The transmitted radiation pulses are reflected by the face of human <NUM>. The reflected radiation pulses (not shown in <FIG>) are detected by the additional millimeter-wave radar and processed by a corresponding processor (which in some embodiments may be processor <NUM>) to generate a facial characteristic signature (i.e., a digital representation) corresponding to facial characteristic <NUM>. Millimeter-wave radar system <NUM> (e.g., using processor <NUM>) then compares the facial characteristic signature to an authorized facial characteristic signature, such as an authorized facial characteristic signature stored in database <NUM>, to determine whether the facial characteristic signature matches any of the authorized facial characteristic signatures.

When millimeter-wave radar system <NUM> (e.g., using processor <NUM>) determines that the facial characteristic signature matches an authorized facial characteristic signature, millimeter-wave radar system <NUM> (e.g., using processor <NUM>) authorizes access to car <NUM> (e.g., by unlocking the doors of car <NUM>) during step <NUM>. If the facial characteristic signature does not match any authorized facial characteristic signatures in database <NUM>, millimeter-wave radar system <NUM> then detects an intrusion during step <NUM> and takes appropriate action (e.g., reporting intrusion to owner of record via a smartphone app, sounding an alarm, or other action). In some embodiments, a predetermined number of attempts (e.g., <NUM> attempts) are allowed during step <NUM> before detecting an intrusion during step <NUM>.

In some embodiments, to avoid excessive power consumption, the additional millimeter-wave radar used during step <NUM> is only activated when prior authentications steps (e.g., <NUM> and/or <NUM>) matches an authorized user.

In some embodiments, database <NUM> includes a single authorized facial characteristic signatures associated with a particular authorized user. Such authorized user may be identified using a fingerprint signature during step <NUM>. For example, in some embodiments, database <NUM> includes a first authorized facial characteristic associated with a first authorized human, and a second authorized facial characteristic associated with a second authorized human. When the first authorized human is detected during step <NUM>, only the first authorized facial characteristic results in a match during step <NUM>. Other embodiments may include a plurality of authorized facial characteristic signatures associated with the particular authorized user. In some embodiments, one or more authorized facial characteristic signatures may be independent (i.e., not associated with a particular authorized user).

In some embodiments, millimeter-wave radar <NUM> is inside the handle of car <NUM>. In other embodiments, millimeter-wave radar <NUM> is behind a different surface of the car. For example, in some embodiments, car <NUM> does not have any handles. In such embodiments, millimeter-wave radar <NUM> is behind a predetermined surface of car <NUM> (e.g., located in a roof, door or other side surface of car <NUM>). When human <NUM> touches the predetermined surface, millimeter-wave radar <NUM> proceeds with the capturing of fingerprint <NUM> (step <NUM>) and other authentication steps (e.g., steps <NUM> and/or <NUM>), if applicable. Upon authentication of human <NUM> (step <NUM>), car <NUM> proceeds with the opening of a door of the car through an automated mechanism.

Millimeter-wave radar <NUM> operates as a frequency-modulated continuous wave (FMCW) radar or pulsed Doppler radar that includes a millimeter-wave radar sensor circuit, transmitting antennas, and receiving antennas. Millimeter-wave radar <NUM> transmits and receives signals in the <NUM> to <NUM> range. Alternatively, frequencies outside of this range, such as frequencies between <NUM> and <NUM>, or frequencies between <NUM>, and <NUM>, may also be used.

In some embodiments, the echo signals received by the receiving antennas of millimeter-wave radar <NUM> are filtered and amplified using band-pass filter (BPFs), low-pass filter (LPFs), mixers, low-noise amplifier (LNAs), and intermediate frequency (IF) amplifiers in ways known in the art by, e.g., millimeter-wave radar <NUM>. The echo signals are then digitized using one or more analog-to-digital converters (ADCs) for further processing, e.g., by processor <NUM>. Other implementations are also possible.

In some embodiments, millimeter-wave radar <NUM> communicates with processor <NUM> using communication interface <NUM>. Communication interface <NUM> may be, for example, of the serial peripheral interface (SPI), inter-integrated circuit (I<NUM>C), or universal asynchronous receiver-transmitter (UART) type. Other communication interfaces may be used.

Processor <NUM> may be implemented as a general purpose processor, controller or digital signal processor (DSP) that includes, for example, combinatorial circuits coupled to a memory. In some embodiments, the DSP may be implemented with an ARM architecture, for example. In some embodiments, processor <NUM> may be implemented as a custom application specific integrated circuit (ASIC). In some embodiments, processor <NUM> includes a plurality of processors, each having one or more processing cores. In other embodiments, processor <NUM> includes a single processor having one or more processing cores. Other implementations are also possible. For example, some embodiments may implement a decoder using software running in a general purpose micro-controller or processor having, for example, a CPU coupled to a memory and implemented with an ARM or x86 architecture. Some embodiments may be implemented as a combination of hardware accelerator and software running on a DSP or general purpose micro-controller.

In some embodiments, processor <NUM> may be implemented inside millimeter-wave radar <NUM>.

In some embodiments, databases <NUM>, <NUM>, and/or <NUM> are implemented inside processor <NUM>, such as in a local memory associated with processor <NUM>. In other embodiments, databases <NUM>, <NUM>, and/or <NUM> are implemented independently of processor <NUM>, such as in the cloud, for example. In some embodiments, databases <NUM>, <NUM>, and <NUM> are implemented inside the same database.

Other methods of authentication may be used instead of, or in addition to gesture recognition (step <NUM>) and facial recognition (step <NUM>). For example, in some embodiments, after a match is identified during step <NUM>, a user may tap on a surface of car <NUM> with a tapping pattern (e.g., captured by an accelerometer) that matches a predetermined tapping pattern signature to gain access to car <NUM>. Other authentication mechanisms are also possible.

Advantages of some embodiments include securely authenticating a user without using optical, thermal, ultrasound or capacitive sensors. For example, some embodiments exhibit smaller form factor, lower power consumption, and higher robustness when used with strong sun light, wet fingers, old or very your humans, when compared to conventional biometric acquisition systems, such as based on optical technology. Some embodiments are advantageously less susceptible to image distortion that may be caused by residual prints from a previous user when compared to conventional optical systems. Additionally, some embodiments are advantageously less susceptible to being fooled by, e.g., captured <NUM>-D images, or prosthetics, when compared to conventional optical systems. Some embodiments are not susceptible to wear of the coating and CCD arrays, thereby advantageously mainlining high accuracy as the system ages. Additional advantages include lower susceptibility to electromagnetic discharge (ESD).

<FIG> shows handle <NUM> of car <NUM>, according to an embodiment of the present invention. As shown in <FIG>, handle <NUM> includes millimeter-wave radar <NUM>. In some embodiments, millimeter-wave radar <NUM> is disposed inside handle <NUM>. For example, <FIG> shows a cross-sectional view of handle <NUM>, according to an embodiment of the present invention. Handle <NUM> includes outer material <NUM>. Outer material has outer surface 304a facing away from car <NUM> and inner surface <NUM> facing towards car <NUM>. As shown in <FIG>, for fingerprint capture during step <NUM>, the finger is in contact with outer surface 304a.

In some embodiments, outer material <NUM> includes plastic. Plastic advantageously allows for millimeter-wave signals (e.g., generated by millimeter-wave radar <NUM>) to travel through it. It is thus advantageously possible to hide millimeter-wave radar <NUM> inside handle <NUM>. Other materials that allow millimeter-waves to travel through may also be used, such as, for example, Teflon (PTFE), acrylonitrile butadiene styrene (ABS), nylon, polycarbonates (PC), ceramic, glass, or any substrate material(s) that allow millimeter-waves to travel through.

<FIG> shows a top view of a layout of millimeter-wave radar <NUM>, according to an embodiment of the present invention. Outer material <NUM> is not shown for clarity purposes. As shown in <FIG>, millimeter-wave radar <NUM> includes transmitting antennas <NUM> and <NUM> and receiving antennas <NUM> and <NUM>. Transmitting antennas <NUM> and <NUM> are aligned vertically, and receiving antennas <NUM> and <NUM> are misaligned vertically, as shown in <FIG>. As also shown in <FIG>, transmitting antenna <NUM> and receiving antenna <NUM> are aligned horizontally, and transmitting antennas <NUM> and receiving antennas <NUM> are aligned horizontally. Other antenna arrangements are also possible.

Some embodiments may include more than two transmitting antennas and/or more than two receiving antennas. Using more than two transmitting antennas and/or more than two receiving antennas advantageously allows for increase accuracy when performing space detection.

In some embodiments, fingerprint recognition may be performed with less than two transmitting/receiving antennas, such as with a single transmitting antenna (e.g., <NUM>) and a single receiving antenna (e.g., <NUM>). Using a single transmitting antenna and a single receiving antenna advantageously allows for fingerprint surface identification, for example.

Some embodiments include more than two transmitting antennas and/or more than two receiving antennas. Using more transmitting antennas and/or more receiving antennas may improve fingerprint and gesture recognition. For example, correlation of information can be done with more receiver channels as the number of receiving antennas increases. As another example, if transmitter beamforming is applied in combination with receiver beamforming, the cross-range image formation may improve.

<FIG> shows a finger of a human performing gesture <NUM> using millimeter-wave radar <NUM>, according to an embodiment of the present invention. As shown in <FIG>, during step <NUM>, pattern <NUM> is projected, e.g., in the air. Finger <NUM> performs gestures <NUM> on top of pattern <NUM>. In some embodiments, pattern <NUM> is invisible or not projected.

The embodiments of authentication systems and mechanisms discussed in <FIG> may also be used to control access to other features of car <NUM>. For example, in some embodiments, a millimeter-wave radar may be disposed at or near a steering wheel of car <NUM> to authorize a user to start and operate car <NUM> (such as start the engine of car <NUM> when a match is determined). For example, <FIG> shows steering wheel <NUM> of car <NUM>, according to an embodiment of the present invention. Steering wheel <NUM> includes (e.g., inside) millimeter-wave radar <NUM>. Millimeter-wave radar <NUM> operates in a similar manner as millimeter-wave radar <NUM>. Gesture recognition and facial recognition may also be used in, e.g., the steering wheel as second mode of authentication. In some embodiments a single processor (e.g., <NUM>) may be shared by millimeter-wave radar <NUM> and millimeter-wave radar <NUM>.

The embodiments of authentication systems and mechanisms discussed in <FIG> may be controlled using the Internet, e.g., via a smartphone app or through a website. For example, <FIG> shows human <NUM> including (i.e., registering) an authorized fingerprint signature into database <NUM>, according to an embodiment of the present invention. As shown human <NUM> scans a fingerprint with smartphone <NUM>, e.g., using an app. Smartphone <NUM> then sends the fingerprint signature through the cloud into database <NUM>. The same registration processes may be performed with other devices, such as a personal computer, laptop, tablet, etc. Some embodiments may also allow for registering a fingerprint signature using millimeter-wave radar <NUM>. A user may also delete an authorized signature through a smartphone, personal computer, laptop, tablet, or through an interface of car <NUM>.

A user may also include (or delete) authorized gesture signatures into database <NUM> and/or authorized facial recognition signatures into database <NUM> using a smartphone, personal computer, laptop, tablet, and/or a millimeter-wave radar. For example, <FIG> shows human <NUM> including (i.e., registering) an authorized gesture signature into database <NUM>, according to an embodiment of the present invention. As shown human <NUM> scans a gesture pattern in smartphone <NUM>, e.g., using an app. Smartphone <NUM> then sends the gesture signature through the cloud into database <NUM>. The same registration processes may be performed with other devices, such as a personal computer, laptop, tablet, etc. Some embodiments may also allow for registering a gesture signature using millimeter-wave radar <NUM>.

In some embodiments, an authorized user of car <NUM> may authorize another user through the cloud. For example, <FIG> shows a flow chart of embodiment method <NUM> of authorizing another user to car <NUM>, according to an embodiment of the present invention.

During step <NUM>, a new user, (such as a family member or friend of, e.g., the owner of car <NUM>, or a valet parking person) requests access to car <NUM> using smartphone <NUM>. During step <NUM>, the owner of car <NUM> (or, e.g., a designated administrator) receives the requests and can approve it or reject it using smartphone <NUM>. If approved, the new user then registers a fingerprint into database <NUM> using smartphone <NUM> during step <NUM>.

During step <NUM>, the new user scans a fingerprint using millimeter-wave radar by, e.g., performing steps <NUM>, <NUM>, and <NUM>. If a match is obtained, a request is sent to the smartphone <NUM> for approval.

During step <NUM>, the owner of car <NUM> receives the requests and can approve it or reject it using smartphone <NUM>. If approved, the owner of car <NUM> generates a gesture using smartphone <NUM> and sends it to smartphone <NUM>.

During step <NUM>, the new user receives the gesture on smartphone <NUM>, and performs the gesture in the field-of-view of millimeter-wave radar <NUM> (e.g., performing step <NUM>). If a match is found between the gesture performed by the new user and the gesture received in smartphone <NUM>, access is granted to car <NUM>.

Steps <NUM>, <NUM> and <NUM> may be performed once per new user to register the new user. Subsequent requests by an already registered user may begin in step <NUM>.

<FIG> illustrates a block diagram of embodiment method <NUM> for performing fingerprint recognition (step <NUM>) using millimeter-wave radar <NUM>, according to an embodiment of the present invention. Radar processing occurs as follows. In steps <NUM>, <NUM>, and <NUM>, radar data is collected from millimeter-wave radar <NUM> and objects (e.g., the finger) are detected in the field of view of millimeter-wave radar <NUM>. In step <NUM>, and <NUM>, a range-cross-range 2D image having azimuth and depth information (e.g., of the fingerprint) is generated, in part, using a Capon/MVDR analysis. During steps <NUM>, <NUM> and <NUM>, the 2D image is transformed according to a predictive model and is compared with 2D reference images of a signature database(e.g., the signatures in database <NUM>) to determine whether the captured fingerprint matches an authorized fingerprint signature. It is understood that method <NUM> may also be performed for gesture recognition (step <NUM>) and facial recognition (step <NUM>).

In step <NUM>, live radar data is collected from millimeter wave radar <NUM>. In some embodiments, this radar data is collected from digitized baseband radar data and includes separate baseband radar data from multiple antennas.

In step <NUM>, signal conditioning, low pass filtering and background removal is performed. During step <NUM>, radar data received during step <NUM> is filtered, DC components are removed, and IF data is filtered to, e.g., remove the Tx-Rx self-interference and optionally prefiltering the interference colored noise. In some embodiments, filtering includes removing data outliers that have significantly different values from other neighboring range-gate measurements. Thus, this filtering also serves to remove background noise from the radar data. In a specific example, a Hampel filter is applied with a sliding window at each range-gate to remove such outliers. Alternatively, other filtering for range preprocessing known in the art may be used.

In step <NUM>, a series of FFTs are performed on conditioned radar data produced by step <NUM>. In some embodiments, a windowed FFT having a length of the chirp (e.g., <NUM> samples) is calculated along each waveform for each of a predetermined number of chirps in a frame of data. Alternatively, other frame lengths may be used. The FFTs of each waveform or chirp may be referred to as a "range FFT. " In alternative embodiments, other transform types could be used besides an FFT, such as a Discrete Fourier Transform (DFT) or a z-transform.

In various embodiments, a beam is formed at the transmitter by post processing a plurality of baseband signals based on a plurality of signals received by different receivers or a combination thereof. Implementing beamforming by post processing received baseband signals may allow for the implementation of a low complexity transmitter.

In one example, a millimeter-wave sensor system is used with Nt = <NUM> transmit (TX) elements and Nr = <NUM> receive (RX) elements arranged in a array (e.g., as shown in <FIG>). Accordingly, there are Nt × Nr = <NUM> distinct propagation channels from the TX array to the RX array in an array configuration for azimuth angle profiling. If the transmitting source (TX channel) of the received signals can be identified at the RX array, a virtual phased array of Nt × Nr elements can be synthesized with Nt + Nr antenna elements. In various embodiments, a time division multiplexed MIMO array provides a low cost solution to a fully populated antenna aperture capable of near field imaging.

In step <NUM> data is saved from all virtual antennas in a line of detected range-Doppler bins. In step <NUM>, the antenna covariance matrix of the detected range-Doppler bins is estimated as follows: <MAT> where Rr,d is antenna covariance matrix, xr,d(n) represents the data over a particular (range, Doppler) = (r,d) and n represents the specific (r,d) data across multiple frames (n being the indices, and N is the number of frames considered). In step <NUM>, a MVDR algorithm is applied to the range and Doppler data as follows using the above derived covariance matrix: <MAT> where P(θ) represents azimuth spatial spectrum, and a(θ) is the virtual antenna steering vector along the azimuth angle for test angle θ within the field-of-view. In an embodiment, the value θ is found that provides a peak value for P(θ). This determined value for θ is the estimated azimuth angle θest of the detected target (e.g., the finger).

In step <NUM>, a range-cross-range 2D image having azimuth and range information is generated. In some embodiments, the range-cross-range 2D image includes information for all range bins. In other embodiments, the range-cross-range 2D image only includes information in the range bins in which the finger has been identified. Range bins without an identified object are populated with, e.g., zeros.

In step <NUM> the range-cross-range 2D image is compared with one or more reference signatures (e.g., fingerprint signatures) of a signature database (e.g., database <NUM>) using, e.g., a nearest neighbor algorithm, to determine whether there is a match between the captured fingerprint and a reference fingerprint. If a match is fount, the user is authenticated (step <NUM>).

In some embodiments, millimeter-wave radar system <NUM> may be trained to increase the accuracy and effectiveness of fingerprint recognition (step <NUM>), gesture recognition (step <NUM>) and/or facial recognition (step <NUM>). As a non-limiting example, such training may occur when human <NUM> purchases car <NUM>.

<FIG> illustrates a block diagram showing a machine learning pipeline for machine language based feature extraction and identification that can be used to generate reference signatures (step <NUM>) for an authorized signature database (e.g., databases <NUM>, <NUM>, and/or <NUM>) to classify a user as authenticated (a match from steps <NUM>, <NUM> and/or <NUM>), according to an embodiment of the present invention. The top portion <NUM> of <FIG> is devoted to the processing storage of features for comparison to later measurements. The data and steps shown in this portion represent the actions performed when radar measurements are performed and processed for a classification category. The bottom portion <NUM> is devoted to the processing and comparison of new measurements for comparison to stored data. These data and steps represent the actions performed when the system is identifying user as an authenticated (authorized) or not authenticated user.

As shown in the top portion <NUM> of <FIG>, training data <NUM> is transformed into stored feature vectors <NUM> and corresponding labels <NUM>. Training data <NUM> represents the raw data (e.g., echo). Feature vectors <NUM> represent sets of generated vectors that are representative of the training data <NUM>. Labels <NUM> represent user metadata associated with the corresponding training data <NUM> and feature vectors <NUM>.

As shown, training data <NUM> is transformed into feature vectors <NUM> using embodiment image formation algorithms. Data preparation block <NUM> represents the initial formatting of raw sensor data, and data annotation block <NUM> represents the status identification from training data <NUM>.

During operation, one or more radar images are taken of a controlled environment that includes, e.g., one or more attempts of fingerprint scanning (for fingerprint recognition), and/or one or more attempts of finger gesture scanning (for finger gesture recognition) using millimeter-wave radar <NUM>. In some embodiments, one or more radar images are taken of a controlled environment that includes, e.g., one or more attempts of facial scanning (for facial recognition) using the additional millimeter-wave radar.

In some cases, multiple radar images are recorded to increase the accuracy of identification. Machine learning algorithm <NUM> evaluates the ability of a prediction model <NUM> to identify feature vectors and iteratively updates training data <NUM> to increase the classification accuracy of the algorithm. The training performance of the machine learning algorithm may be determined by calculating the cross-entropy performance. In some embodiments, the machine learning algorithm <NUM> iteratively adjusts image formation parameters for a classification accuracy of at least <NUM>%. Alternatively, other classification accuracies could be used.

Machine learning algorithm <NUM> may be implemented using a variety of machine learning algorithms known in the art. For example, a random forest algorithm or neural network algorithm, such as a ResNet-<NUM> or other neural network algorithm known in the art, may be used for classification and analysis of stored feature vectors <NUM>. During the iterative optimization of stored feature vectors <NUM>, a number of parameters of image formation <NUM> may be updated.

Claim 1:
A method (<NUM>) for authenticating a user of a car, the method (<NUM>) comprising:
detecting (<NUM>) a proximity of the user to the car using a millimeter-wave radar of the car;
after detecting (<NUM>) the proximity of the user, transmitting a plurality of radiation pulses through a predetermined portion of a surface of the car towards a portion of a hand of the user using the millimeter-wave radar;
receiving a reflected signal from the portion of the hand using the millimeter-wave radar;
generating a fingerprint signature based on the reflected signal;
comparing (<NUM>) the fingerprint signature to a database of authorized fingerprint signatures; and
authorizing (<NUM>) the user based on whether the fingerprint signature matches an authorized fingerprint signature of the database of authorized fingerprint signatures.