Map-aware MIMO space-time radar circuit and method

Abstract

Radar systems and methods are disclosed that utilize a space-time waveform that includes a shaped beam having a time domain code to determine an object in an observation area. A radar system includes one or more transmitter circuits to transmit a space-time waveform including one or more shaped beams having a time domain code toward an area of observation, one or more receiver circuits to receive a reflected signal associated with the space-time waveform, and a radar processor. The radar processor: retrieves predetermined occupancy data identifying a position of an object relative to the radar system; determining a beamforming weight vector using the predetermined occupancy data; determining one or more time domain codes using the predetermined occupancy data; generating the space-time waveform comprising one or more shaped beams, the one or more shaped beams comprising the one or more time domain codes and based on the beamforming weight vector; and transmitting the space-time waveform toward the observation area using the one or more transmitter circuits.

Description

Technical Field

[0001] This disclosure generally relates to radar systems, circuits, and methods, and more specifically to map-aware multiple-input multiple-output (MIMO) active sensing methods and circuits, such as space-time radar circuits, light detection and ranging (LiDAR) circuits, ultrasonic circuits, and other active sensing circuits. Background Technology

[0002] Automotive radar solutions for Advanced Driver Assistance Systems (ADAS) are currently being deployed on a large scale and are typically implemented as long-range radar (LRR) or short-range radar (SRR) applications. Both applications typically use frequency-modulated continuous wave (FMCW) modulation techniques to identify objects, such as vehicles or pedestrians, near the radar system. These radar systems typically utilize millimeter-wave (mmWave) frequencies to transmit and receive radar signals. The same or similar radar technologies are also used in robotic systems, safety systems, and other systems that utilize data associated with objects in one or more areas surrounding the radar system.

[0003] Radar systems can be configured to transmit electromagnetic signals in one or more directions and receive reflections of the transmitted signals from objects interfering with the electromagnetic signals. Variations in the time delay between signal transmission and signal reflection reception (and variations between the timing of different signal reflections) can be determined and used to determine the distance, velocity, or any combination thereof of the object causing the reflection. For example, in automotive applications, automotive radar systems can be used to determine the distance, velocity, and other parameters of objects (such as oncoming vehicles and other obstacles) in the vehicle's direction of travel, and this data can be transmitted to other systems. In some automation applications, data from automotive radar systems can enable advanced driver assistance system functions, such as assisted cruise control, emergency braking, blind spot monitoring and warning, lane assist, other functions, or any combination thereof, and ultimately, fully autonomous driving platforms. Summary of the Invention

[0004] According to a first aspect of the present invention, a method is provided, comprising:

[0005] The radar system is used to receive predetermined information about the observation area of ​​the radar system.

[0006] At least one transmitter circuit of the radar system determines a beamforming weight vector based on the predetermined information, the beamforming weight vector defining a spatial domain beam.

[0007] One or more time-domain codes are determined by the at least one transmitter circuit based at least in part on the predetermined information;

[0008] The spatial domain beam and one or more time domain codes are combined using the at least one transmitter circuit to form a space-time waveform; and

[0009] The space-time waveform is transmitted at a selected angle toward the observation area of ​​the radar system using at least one transmitter circuit of the radar system.

[0010] In one or more embodiments, the predetermined information includes one or more of the following: distance data, angle data, or Doppler data corresponding to one or more objects within the observation area.

[0011] In one or more embodiments, the predetermined information includes one or more of the following: an occupancy map, driving lane topology information including drivable areas with lane information, or an occupancy grid.

[0012] In one or more embodiments, receiving the predetermined information includes retrieving the predetermined information from a memory.

[0013] In one or more embodiments, determining the beamforming weight vector includes:

[0014] At the at least one transmitter circuit, one or more occupancy probabilities are determined based on the predetermined information; and

[0015] At the at least one transmitter circuit, the beamforming weight vector is determined based on the one or more occupancy probabilities.

[0016] In one or more embodiments, determining the one or more time-domain codes includes determining that one or more time-domain waveforms have reduced correlation with each other.

[0017] In one or more embodiments, determining the one or more time-domain codes includes determining a time-domain waveform for each selected angle.

[0018] In one or more embodiments, the method further includes:

[0019] At least one receiver circuit of the radar system is used to receive a reflected signal from the observation area of ​​the radar system, the reflected signal being correlated with the space-time waveform;

[0020] At the at least one receiver circuit, spatial domain data is determined based on the reflected signal. The spatial domain data includes probability data indicating the probability that one or more objects are present in the observation area for the selected angle.

[0021] At the at least one receiver circuit, time-domain data corresponding to the time-domain code is determined from one or more of the reflected signal or the spatial-domain data; and

[0022] For each of one or more selected angles, the at least one receiver circuit is used to determine the probability that an object is within a selected area of ​​the observation region based on the spatial domain data and the temporal domain data.

[0023] In one or more embodiments, determining the spatial domain data includes applying an angle domain matched filter to determine the direction of arrival and distance data for each of the selected angles.

[0024] In one or more embodiments, determining the time-domain data includes applying a time-domain matched filter to determine the time-domain data corresponding to the time-domain code of the space-time waveform.

[0025] In one or more embodiments, determining the time-domain data includes correlating distance information based on the time-domain data to determine one or more targets in the direction of the selected angle.

[0026] In one or more embodiments, correlating the distance information includes reducing weighted sidelobe data based on the time-domain data.

[0027] In one or more embodiments, the radar system is coupled to one of a vehicle or a mobile robot system.

[0028] In one or more embodiments, sending the space-time waveform toward the observation region includes:

[0029] Multiple shaped beams are sent toward the observation area, and

[0030] The beamforming gain or beam pattern will change at different locations within the observation area.

[0031] In one or more embodiments, sending the space-time waveform toward the observation region includes sending a plurality of shaped beams toward the observation region, each shaped beam including a selected time-domain code.

[0032] According to a second aspect of the present invention, a radar system is provided, comprising:

[0033] One or more transmitter circuits are configured to transmit a space-time waveform toward an observation region, the space-time waveform including one or more shaped beams, the one or more shaped beams including time-domain codes;

[0034] One or more receiver circuits configured to receive reflected signals associated with the space-time waveform; and

[0035] The radar processor is configured to:

[0036] Retrieve predetermined occupancy data of the position of the identified object relative to the radar system;

[0037] The predetermined occupancy data is used to determine the beamforming weight vector;

[0038] One or more time-domain codes are determined using the predetermined occupancy data;

[0039] Generate the space-time waveform comprising one or more shaped beams, the one or more shaped beams including the one or more time-domain codes and based on the beamforming weight vector; and

[0040] The space-time waveform is transmitted toward the observation area using one or more transmitter circuits.

[0041] In one or more embodiments, the one or more time-domain codes are determined to reduce the autocorrelation of sidelobe information in the reflected signals received by the one or more receiver circuits.

[0042] In one or more embodiments, one or more of the beamforming gain, beam pattern, or time-domain code varies relative to the position within the observation area.

[0043] In one or more embodiments, each of the one or more receiver circuits includes:

[0044] An angle-domain matched filter determines arrival direction data associated with one or more angles based on the space-time waveform; and

[0045] A time-domain matched filter, which correlates time-domain code data based on the space-time waveform to determine distance information with reduced sidelobe interference.

[0046] In one or more embodiments, the radar processor is configured to determine one or more of an updated occupancy grid or occupancy map based on determined direction-of-arrival data and determined distance information.

[0047] These and other aspects of the invention will become apparent from the embodiments described below, and will be illustrated with reference to these embodiments. Attached Figure Description

[0048] The accompanying drawings provide a detailed description. In the drawings, the leftmost numeral of the reference numeral indicates the figure in which the reference numeral first appears. The use of the same reference numeral in different figures and detailed descriptions indicates similar or identical items or features.

[0049] Figure 1 A radar system, configured to perform interference suppression according to various embodiments, is described.

[0050] Figure 2Conceptual diagrams of radar systems according to various embodiments are shown. The radar system includes a receiver for receiving inputs of an occupancy grid map and a lane topology map, and for receiving time code information of reflections to reduce sidelobe interference.

[0051] Figure 3 Depicts lane topology maps and drivable space maps determined by a system including a radar system, according to various embodiments.

[0052] Figure 4A Plot the relationship between the autocorrelation level and autocorrelation hysteresis of the Chu waveform used in conventional radar systems.

[0053] Figure 4B Depicting various embodiments Figure 1-2 The relationship between the autocorrelation level and autocorrelation hysteresis of a radar system.

[0054] Figure 5A Depicting Chu waveforms (sequences) according to various embodiments and Figure 1-2 The graph shows the relationship between the detection probability and the false alarm probability of a radar system with a signal-to-noise ratio of 10 dB.

[0055] Figure 5B Depicting Chu waveforms (sequences) according to various embodiments and Figure 1-2 The graph shows the relationship between the detection probability and the false alarm probability of a radar system with a signal-to-noise ratio of 0 dB.

[0056] Figure 6A Plot the relationship between the matched filter output of the Zadoff-Chu sequence and the time lag / distance partition.

[0057] Figure 6B Depicting various embodiments for Figure 1-2 The diagram shows the output of the matched filter for the identification sequence of the radar system.

[0058] Figure 7 A flowchart depicts a method for generating an occupancy map based on spatial code data and time code data according to various embodiments.

[0059] While embodiments have been described by way of example in this disclosure, those skilled in the art will recognize that embodiments are not limited to the described examples or drawings. In fact, the drawings and their detailed description are not intended to limit embodiments to the disclosed form, but rather to cover all modifications, equivalents, and alternatives falling within the spirit and scope defined by the appended claims. The headings used in this disclosure are for organizational purposes only and are not intended to limit the scope of the specification or claims. As used throughout this application, the word “may” is used in an permissible sense (in other words, the term “may” is intended to mean “possibly”) rather than in a mandatory sense (as in “must”). Similarly, the term “include / including / includes” means including, but not limited to, those examples. Detailed Implementation

[0060] Automotive radar systems can access rich side information about a driving scene being sensed in the form of an occupancy map. The radar systems, methods, and apparatuses described herein can be configured to dynamically design space-time codes at the radar transmitter using knowledge of occupancy map information and lane topology information. In one or more embodiments, the radar system can be configured to use beamforming to transmit beams to determine the probability of an object in an area where a target may be located, and to configure time-domain codes for transmission in the shaped beam. The radar system can receive reflected signals, determine spatial and temporal data, and utilize the separate spatial and temporal data to achieve a higher detection rate than conventional automotive radar systems.

[0061] Radar technology is used in automotive systems, autonomous robotic systems, and other applications for detecting and sensing objects. In one or more embodiments, automotive radar systems and methods can be configured to utilize adaptive beamforming of transmitted radar signals to achieve higher power-efficiency operation and improve object detection in the automotive radar system. In one or more embodiments, the radar system can be configured to beamform in the spatial domain to enhance the echo intensity from cells associated with higher occupancy uncertainty, and to optimize the temporal waveform to minimize the correlation between echoes of targets within the drivable space. Spatial and temporal optimization achieves a higher detection probability than radar employing standard waveforms. In one or more embodiments, the radar system can be configured to combine space-time codes and temporal codes to determine a space-time waveform based on predetermined occupancy data, which achieves a higher detection rate than conventional space-time waveforms that do not rely on prior occupancy information (temporal data or temporal codes).

[0062] Radar systems can be used as sensors in a variety of applications, including but not limited to automotive radar sensors for road safety and vehicle control systems such as Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD) systems. In one or more other embodiments, radar systems can be used in robotic systems (e.g., for autonomous mobility), safety systems (e.g., for manufacturing systems), industrial process control, or other systems where the proximity of objects (including people) can be detected and used for hazard mitigation.

[0063] The following detailed description is illustrative in nature and is not intended to limit the use of the embodiments described herein and such embodiments. Furthermore, it is not intended to be construed as being bound by any explicit or implicit theory presented in the foregoing technical field, background art, or the following detailed description.

[0064] For the sake of simplicity and clarity, the figures illustrate general construction methods. Descriptions and details of well-known features and techniques may be omitted from the following detailed description to avoid unnecessarily obscuring this disclosure. For example, the dimensions of some elements or regions in the figures may be enlarged relative to other elements or regions to aid in understanding the embodiments described herein.

[0065] The terms “first,” “second,” “third,” “fourth,” etc. (if present) used in this specification and claims are used to distinguish similar elements and are not necessarily used to describe a particular sequence or chronological order. It should be understood that the terms thus used are interchangeable where appropriate, such that the embodiments described herein can be operated, for example, in a different order than that shown or described herein. Furthermore, the terms “comprise,” “include,” “have,” and any variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus comprising a list of elements is not necessarily limited to those elements, but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. As used herein, the terms “approximately,” “about,” “substantially,” and “basically” mean sufficient to achieve the stated purpose in a practical manner, and minor defects (if present) are not important to the stated purpose.

[0066] In accordance with these principles, when references are made to measurable quantities, including but not limited to dimensions, these terms mean that the quantity is equal to the stated value, subject to acceptable tolerances of any method or apparatus chosen for manufacturing the described structure or measuring the described quantity or dimension. Unless otherwise stated, directional references, such as “top,” “bottom,” “left,” “right,” “above,” “below,” etc., are not intended to require any preferred orientation, but are for illustrative purposes, referring to the orientation of one or more corresponding figures. As used herein, the terms “exemplary” and “example” mean “serving as an example, instance, or illustration.” Any embodiment described herein as exemplary or illustrative should not necessarily be construed as preferred or advantageous over other embodiments. Furthermore, certain terms may be used herein for reference only and are therefore not intended to be restrictive.

[0067] In this document, elements, nodes, or features are sometimes referred to as “connected” or “coupled” together. As used herein, unless explicitly stated otherwise, “connected” means that one element is directly engaged to (or directly connected to) another element in an electrical or non-electrical manner, and not necessarily mechanically. Similarly, unless explicitly stated otherwise, “coupled” means that one element is directly or indirectly engaged to (or directly or indirectly connected to) another element in an electrical or non-electrical manner, and not necessarily mechanically. Therefore, although the schematic diagrams shown depict exemplary arrangements of elements, additional intervening elements, devices, features, or components may be present in one or more embodiments of the depicted subject matter.

[0068] Millimeter-wave radar is one of the primary sensing methods in current driver assistance and autonomous driving systems. Multiple-input multiple-output (MIMO) radar systems can be configured to shape the beam at the transmitter and estimate the direction of arrival of the reflected beam at the receiver. In one or more embodiments, the transmitter of the radar system can utilize information about the sensed environment to shape the beam. In one or more embodiments, the information may include an occupancy grid map, which may comprise a grid of range-angle-Doppler cells, wherein the occupancy value in a cell indicates the probability that the real-world area represented by that cell may be occupied by an object. In one or more embodiments, the radar system can be configured to adjust the transmitted waveform of the radar system based on information contained in the occupancy map, for example, to direct the beam toward the real-world area represented by a cell with a relatively high probability of uncertainty (e.g., a cell with a probability close to 50%) indicated by the occupancy map.

[0069] Radar systems can utilize beamforming to enhance detection in cells with high uncertainty, thereby leveraging occupancy maps for beamforming to concentrate power on areas with high occupancy map uncertainty. Simultaneously, the radar system can encode time-domain codes into the beam to enhance target detection within areas of high occupancy map uncertainty at the output of the time-matched filter. The radar system can combine spatial domain data and time-domain code data to produce an improved occupancy map that outperforms standard quasi-omnidirectional radar techniques and directional beamforming methods, especially in the context of multiple targets within the same angular partition. The following section discusses... Figure 1 Describe examples of such radar systems.

[0070] Figure 1 A system 100 is depicted according to various embodiments, including a radar system 101 configured to perform interference suppression. The radar system 101 may include a radar device 102 (sometimes referred to herein as a “radar communication circuitry system” or “radar front-end circuitry system”) coupled to a radar microcontroller and processing unit (MCPU) 104, wherein the MCPU 104 may be configured to provide a occupancy map and other data to a transmitter 118, which may use the occupancy map and other data to generate one or more shaped beams, each shaped beam including an encoded time-domain code. The MCPU 104 may receive reflected signal data (including the time-domain code) from receiver circuitry 128 and may utilize the time-domain code to remove sidelobe interference and enhance multi-target detection.

[0071] In one or more embodiments, radar system 101 may be a multiple-input multiple-output (MIMO) radar system, such as a linear frequency modulation (LFM) MIMO radar system (e.g., an LFM automotive MIMO radar system). In one or more embodiments, radar device 102 may include radar front-end hardware. In one or more embodiments, radar device 102 may be embodied as a field-replaceable unit (LRU) or modular component designed for rapid replacement at an operating location. Similarly, radar MCPU 104 may be embodied as a field-replaceable unit (LRU) or modular component. Although a single or monostatic radar device is shown, it should be understood that additional distributed radar devices can be used to form a distributed or multistatic radar. Additionally, the depicted radar system 101 may be implemented as an integrated circuit, wherein radar device 102 and radar MCPU 104 are formed on a separate integrated circuit (chip) or a single chip, depending on the application.

[0072] According to various embodiments, radar system 101 may be implemented as part of an automotive system in conjunction with an advanced driver assistance system (ADAS) of a vehicle, such as vehicle 150. It should be understood that components of radar system 100 may be distributed at various locations on or within vehicle 150 (e.g., the antenna may be located at one or more front, rear, or side panels of vehicle 150, at the front or rear bumper of vehicle 150, or at other suitable locations on vehicle 150, or combinations thereof; wherein the processing circuitry, transmitter module, and receiver module are located at one or more locations within vehicle 150). In one or more other embodiments, radar system 101 may be implemented in different devices or systems, such as robotic systems, safety systems, or other systems using dynamic object (target) detection.

[0073] The radar device 102 includes one or more transmitting antenna elements 126 (sometimes referred to herein as “transmitting antennas”) and receiving antenna elements 142 (sometimes referred to herein as “receiving antennas”) connected to one or more radio frequency (RF) transmitter (TX) circuits 118 and receiver (RX) circuits 128, respectively. Each transmitting antenna 126 and TX circuit 118 may be connected to TX1, TX2, TX3, ... TX (as designated herein). M A corresponding transmit channel in a set of transmit channels is associated with M, where M is the total number of transmit (TX) channels. Each receive antenna 142 and RX circuit 128 can be associated with a corresponding transmit channel in this document, designated RX1, RX2, RX3, ... RX. N A set of corresponding receive channels are associated, where N is the number of receive (RX) channels. As a non-limiting example, radar device 102 may include individual antenna elements (e.g., antenna element 126) respectively connected to four transmitter modules (e.g., transmitter circuit 118) and sixteen receiver modules (e.g., receiver circuit 128). These quantities of transmitter and receiver antenna elements and modules are intended to be illustrative and not limiting, wherein other quantities of these elements are possible in one or more other embodiments, such as four transmitter circuits 118 and six receiver circuits 128, or a single transmitter circuit 118 and / or a single receiver circuit 128, and so on.

[0074] Radar device 102 may include a chirp generator 116 configured to supply a chirp input signal to transmitter circuit 118. For this purpose, chirp generator 116 may be configured to receive input program and control signals from MCPU 104 via digital-to-analog converter (DAC) 114. As a non-limiting example, the input program and control signals include a reference local oscillator (LO) signal, a chirp start trigger signal, and a program control signal. Chirp generator 116 may be configured to generate a chirp signal and transmit it to transmitter circuit 118 via DAC 114 for transmission via transmit antenna element 126.

[0075] In one or more embodiments, each transmitter circuit 118 may include an RF conditioning module 122 configured to filter the chirped signal. In one or more embodiments, the RF conditioning module 122 may include one or more frequency multipliers configured to increase the frequency of the chirped signal output by the chirped generator 116. In one or more embodiments, the RF conditioning module 122 of each transmitter circuit 118 may include a beamforming circuit system configured to perform beamforming operations in the beam domain to enhance the detection probability in the region where the target may be located, and may be combined with time-domain codes to further enhance target detection.

[0076] Each transmitter circuit 118 includes a power amplifier 124 configured to amplify the filtered chirped signal before it is provided to and transmitted via one or more corresponding transmit antenna elements 126. Hereinafter, the transmitted chirped signal is sometimes referred to as the “transmit signal.” The transmit signal may include a time-domain code that may be unique for each antenna element 126. Each transmitter element 126 may transmit a generated spatial domain beam including the time-domain code.

[0077] Radar signals transmitted by transmitter circuitry 118 and transmitting antenna 126 may be reflected by objects in the environment of radar device 102, and a portion of the reflected radar signals (sometimes referred to herein as “echo” or “reflection”) may be received by receiving antenna element 142 at radar device 102. In one or more embodiments, the reflected radar signals received via one of the receiving antenna elements 142 and the corresponding receiver circuit in receiver circuitry 128 correspond to chirped signals transmitted via one of the transmitting antenna elements 126 and the corresponding transmitter circuitry 118, and such received radar signals may be referred to herein as “chirp,” “chirped signal,” or “received chirped signal.” Such received chirped signals may include interference components attributable to one or more interference signals in the environment of radar system 101.

[0078] At each receiver circuit 128, the received (RF) antenna signal can be amplified by a low-noise amplifier (LNA) 140 and then fed to a mixer 138, where the received (RF) antenna signal can be mixed with a transmitted chirp signal generated by an RF conditioning module 122. The resulting intermediate frequency (IF) signal can be fed to a high-pass filter (HPF) 136. The resulting filtered signal can be provided to a variable gain amplifier 134, which amplifies the signal before feeding it to a low-pass filter (LPF) 132. This re-filtered signal can be fed to an analog-to-digital converter (ADC) 130 to generate a digital signal, which is output by each receiver circuit 128 to a signal processor 110 of the MCPU 104. In this way, the receiver circuit 128 can compress target echoes with various delays into multiple sinusoidal frequencies with frequencies corresponding to the round-trip delays of the echoes.

[0079] In radar system 101, radar MCPU 104 may be coupled to radar device 102. Radar MCPU 104 may be configured to supply input control signals to radar device 102 to cause transmitter element 126 to transmit signals, and may be configured to receive digital output signals generated by receiver circuitry 128 based on the reflection of the transmitted signals. In one or more embodiments, radar MCPU 104 may include radar controller 108 and signal processor 110, either or both of which may be embodied as a microcontroller unit or other processing unit. According to various embodiments, MCPU 104, radar controller 108, and signal processor 110 may each include or be implemented by a computer processing circuitry.

[0080] The radar controller 108 can be configured to receive data from the radar device 102 (e.g., from receiver circuitry 128) and can control radar parameters of the radar device 102, such as the bandwidth, length, etc. of each radar frame, via the DAC 114. To control the transmitter circuitry 118, the radar controller 108 can be configured, for example, to generate transmitter input signals, such as program, control trigger, reference local oscillator (LO) signal, calibration signal, spectrum shaping signal (e.g., ramp generation in the case of frequency modulated continuous wave (FMCW) radar). The radar controller 108 can be configured, for example, to receive data signals for RF (radio frequency) circuit enable sequences, sensor signals, and / or register programming or state machine signals.

[0081] Signal processor 110 may be configured and arranged for signal processing tasks, such as, but not limited to, target object identification, interference mitigation, calculating the distance or gap to a target object, calculating the radial velocity of a target object, and calculating the angle of arrival (AoA) of a signal reflected by a target object. Herein, the term "AoA" or "angle of arrival" refers to the angle of a reflected signal (e.g., a radar signal) incident on an antenna array. In one or more embodiments, signal processor 110 of MCPU 104 may be configured to generate occupancy map data based on a digital output signal received from receiver circuitry 128. Signal processor 110 may provide calculated values ​​associated with such calculations to storage device 112 (e.g., occupancy map data 146), to other systems via one or more input / output (I / O) interfaces 106, or any combination thereof.

[0082] One or more I / O interfaces 106 enable the MCPU 104 to communicate with other systems via local area networks and wide area networks, the Internet, automotive communication buses, other devices, or any combination thereof. In one or more embodiments, the I / O interface 106 may include or be coupled to a network communication interface, such as a wired communication interface (e.g., an RJ 45 port, Ethernet cabling, coaxial connector, coaxial cabling, fiber optic connector, fiber optic cabling, other ports, other cabling types, or any combination thereof) or a wireless RF communication interface (e.g., an 802.11x RF transceiver, Bluetooth transceiver, other RF transceivers, or any combination thereof). In one or more embodiments, the MCPU 104 may provide calculated values ​​to other systems via interface 106, such as a radar-camera-liDAR fusion system; an autonomous driving assistance system including parking, braking, or lane change assist features; and so on. The memory 112 may be used to store instructions for the MCPU 104, received data from the radar device 102, calculated values ​​from the signal processor 110 (including occupancy map data 146), other data, or any combination thereof. Storage device 112 can be any suitable storage device, such as volatile or non-volatile computer-readable memory.

[0083] At each receiver circuit 128, a digital output signal is generated from the target echo signal for digital processing by the signal processor 110 to construct and accumulate a multiple-input multiple-output (MIMO) array vector output, thereby forming a MIMO aperture for calculating the AoA estimate and a plot or mapping of the target object trajectory. Specifically, the signal processor 110 may use one or more Fast Fourier Transform (FFT) modules or Discrete Fourier Transform (DFT) modules, such as a fast time (distance) FFT module, to perform one or more interference suppression processes on the digital output signal before processing the resulting interference-suppressed samples (e.g., the processes may include one or more recursive thresholding processes described herein).

[0084] The processing performed by these modules of signal processor 110 generates a range-chilled antenna cube (RCAC), and a slow-time (Doppler) FFT module generates a range-Doppler antenna cube (RDAC) (e.g., including a range-Doppler response map for each RX antenna). Signal processor 110 can then perform constant false alarm rate (CFAR) detection on the range-Doppler antenna cube to detect peaks in the RDAC. Signal processor 110 can further process the RDAC based on the detected peaks to construct a MIMO array vector, which is then processed to perform AoA estimation and target tracking. MCPU 104 can then output the resulting target trajectory (e.g., via interface 106) to other automotive computing devices or user interface devices for further processing or display.

[0085] In the illustrated example, radar device 102 may include an automotive radar with co-located transmitter circuitry 118 and receiver circuitry 128. In one or more embodiments, antenna elements 126 and 142 may be a linear array of uniformly spaced antenna elements. In one or more embodiments, the antenna elements may be spaced apart from each other by a half-wavelength distance or another spacing. Transmitter circuitry 118 may be implemented with a fully digital architecture that may include N isotropic transmitter elements 126, and receiver circuitry 128 may include a digital array with N isotropic antenna elements 142. Transmitter circuitry 118 may periodically transmit bursts of M pulses in one radar coherent processing interval (CPI). Transmitter circuitry 118 may be configured to radiate different waveforms from each transmitter element 126. The transmitted pulses may strike K point targets within the field of view of radar device 102.

[0086] In one or more embodiments, one or more of the signal processor 110 or radar controller 108 may determine a space-time waveform (encoding matrix) W 144 that may include beamforming weights at each fast-time sampling moment at transmitter circuitry 118. Signal processor 110 or radar controller 108 may be configured to generate the space-time waveform (encoding matrix) W to reliably detect targets within drivable space by utilizing occupancy map data 146. Transmitter circuitry 118 may use the space-time waveform W 144 to generate different waveforms for radiation by transmitter element 126.

[0087] In one or more embodiments, transmitter circuitry 118 can perform beamforming operations by determining a set of weights (columns arranged as W), which can be determined by waveform module 121, which can be part of transmitter circuitry 118 or MCPU 104. Waveform module 121 can be configured to receive predetermined information from MCPU 104 or another source, which may include data related to objects or targets in the observation area of ​​radar system 101. Waveform module 121 can be configured to determine occupancy data corresponding to the observation area based on the predetermined information and use this information to dynamically design space-time codes that can be used to generate space-time waveforms that can be transmitted by antenna element 126. Specifically, waveform module 121 can determine spatial domain data that can be used to generate beamforming weight matrix W and includes time-domain codes, which can be used to reduce sidelobe interference and improve signal reception.

[0088] In one or more embodiments, transmitter circuit 118 may apply a space-time waveform to control the magnitude of a signal generated by a combination of various transmitted signals directed in different directions. A weighting matrix W stores values ​​that determine the configuration of various hardware components of transmitter circuit 118 when the space-time waveform is transmitted. Thus, the beamforming weighting matrix W can determine the physical configuration of elements such as power amplifiers, amplitude controllers, and / or adjustable phase shifters in a manner that enables a specific beamforming configuration of the transmitted signal. In one or more embodiments, the beamforming weighting matrix W may be a one-dimensional array comprising a plurality of values ​​equal to the number of transmitters used for beamforming within the radar system. The i-th row of the weighting matrix W (i.e., W...) i The weights defined by the weight matrix W can represent the weights applied at the i-th transmitter circuit 118. The weights can be applied digitally in a MIMO radar system (e.g., via control signals sent by the MCPU 104 or by the waveform module 121 to components (e.g., power amplifiers, phase shifters, other circuit elements, or any combination thereof) within the signal path of the transmitter circuit 118 of the radar system 101). In one or more embodiments, the transmitter circuit 118 applies beamforming weights from the beamforming weight matrix W to the transmitting antenna array, such that the outputs from multiple antenna elements 126 are combined to enhance the overall signal strength along certain directions (selected directions or angles). Therefore, a beamforming-based transmitter can electronically steer the radar signal beam without requiring physical movement of the antenna elements 126. The use of transmitting beamforming allows for better interference recovery and better power management in the radar system 101. Similarly, the beamforming weight matrix W generated by the waveform module 121 enables the radar system 101 to properly receive and process signals at the receiving antenna element RX. 1,1 -RX 1,NThe received radar reflection signal is the reflection of the transmitted signal. The received radar reflection signal can be processed to identify potential target objects indicated by the reflection signal, as well as the various target object attributes (e.g., distance or spacing, speed, angle) that are subsequently transmitted to the vehicle's ADAS or other vehicle systems.

[0089] The field of view (FOV) or observation area of ​​radar system 101 can be subdivided into multiple distinct zones or sectors, referred to herein as angular partitions. A beamforming weight matrix W can be configured such that transmitter circuitry 118 sends radar signals to each zone or sector to identify the attributes of potential target objects that may exist within each zone or sector. In a typical radar system, the radar signal sent to each zone or sector is transmitted at full power to achieve the maximum possible range for target object detection in each zone or sector. Because in conventional radar systems, radar signals are transmitted at maximum signal power to always provide target object detection at the longest range, this operating mode can lead to a significant level of signal interference within the radar system and inefficient radar system operation in terms of power consumption.

[0090] To remedy these problems (and others), radar system 101 can be configured to utilize beamforming operations by generating appropriate beamforming weight vectors within waveform module 121 to control or optimize radar signal transmission power levels based on predetermined information (e.g., occupied map data 146) retrieved from MCPU 104 or memory 112.

[0091] In the implementation plan, such as Figure 1As shown, occupancy map data 146 can be retrieved from memory 112 or from another source. Occupancy map data may include information describing known structures or objects (typically static, but may also include dynamic objects) near vehicle 150, including static map information and object data determined by detection performed from radar system 101. For example, on a particular road, occupancy map data may provide information about the location of road guardrails extending along the road edge, buildings or other permanent structures (e.g., bridges, tunnels, large geological formations (e.g., hillsides or cliffs), large vegetation (e.g., large trees), large road construction equipment, or other street obstacles). More generally, occupancy map data may include data structures describing the location of radar signal blocking objects near radar system 101. Thus, the occupancy map can be considered to define the space around vehicle 150 into which vehicle 150 can drive or maneuver (i.e., it is invalid for a vehicle to enter or pass through an area designated by the occupancy map as containing radar signal blocking objects, but vehicle 150 can enter an area that does not contain such objects). In some cases, for multiple sectors radiating from a radar system (e.g., angular partitions), the occupancy map defines the spacing or distance to the nearest radar signal blocking object. In other cases, the occupancy map may define the probability or likelihood that a radar blocking object is located at a specific location near the radar system.

[0092] In one or more embodiments, the signal generated by the transmitting antenna element 126 may generate sidelobes, which can cause noise in the received reflected waveform. To reduce the effects of sidelobes, the waveform module 121 may be configured to select one or more time-domain codes, which may be combined with beamforming operations to include time-code data in the resulting waveform, thereby producing a space-time waveform that can be transmitted by the transmitter circuitry 118. In one or more embodiments, the time-domain codes may be selected to provide reduced correlation relative to the reflected signal. The time-domain code information and beamforming spatial domain information may be provided to the receiver circuitry 128 and used for spatial domain (angle domain) matched filters and time-domain matched filters to extract direction-of-arrival and distance data from the reflected signal and to perform fast autocorrelation of the distance data to identify objects in the observation area.

[0093] For reference Figure 2According to a conceptual diagram 200 of a radar system 101 according to various embodiments, the radar system includes a receiver for receiving inputs of an occupancy grid map 220 and a lane topology map 230, and a receiver for receiving time code information of reflections to reduce sidelobe interference. In the illustrated example, the radar system 101 of vehicle 150 can transmit multiple transmit TX signals in the observation area. In this example, an empty road 202 including guardrails is shown. Vehicle 150 may include radar system 101, which includes a MIMO radar that uses a space-time coding matrix to control transmitter circuitry 118 to perform beamforming (spatial domain) and data coding (temporal domain) to generate a beam 242 that can be transmitted in the observation area to utilize occupancy map data 146 ( Figure 1 (In the middle) to detect targets within the drivable space.

[0094] As discussed above, predetermined information, such as occupancy grid 220 or occupancy data map 230, can be received by waveform module 121. Waveform module 121 can be part of transmitter circuit 118, MCPU 104, or another circuit. Waveform module 121 can be configured to determine beamforming weight vectors and time-domain codes that can be combined to form a space-time waveform matrix W. Transmitter circuit 118 can cause antenna element 126 to radiate a signal in a slow time slot according to the determined space-time waveform to estimate angular and range parameters related to a target (object) in the observation area.

[0095] In one or more embodiments, the signal processor 110 may receive a digital output signal from the receiver circuit 128 and may determine the probability that a cell indexed according to its distance partition i, angle partition j, and Doppler partition k is occupied. The entropy H of probability can be determined as follows:

[0096] Entropy H can be used to determine the weighted detection probability as follows:

[0097]

[0098] Subject to

[0099] In Equation 2, Ni represents the number of distance partitions along direction i in the drivable space, N represents the number of angle partitions, Nj represents the maximum drivable space along direction j, Nd represents the number of Doppler partitions for each distance-angle cell, and term P d (i,j,k;W) corresponds to the probability of detecting target (i,j,k) in cell and follows a Gaussian distribution.

[0100] The resulting grid map occupies 220 (which can be) Figure 1An example of occupancy map data 146 may include multiple cells 222 depicted herein as data cubes, the data cubes representing Doppler data V, distance data R, and angle data θ. The occupancy grid map 220 may be further processed to produce a lane topology map 230 depicting the distance-angle index relationship to objects. In Equation 2, the weights for scaling the detection probability are functions of distance, angle, and Doppler partitioning, subject to the fact that the space-time waveform W 123 for each beam m 244 is less than the transmission power quantized for each fast-time beam 244.

[0101] In one or more embodiments, the input to the radar device may include a map comprising one or more of a drivable area with lane information and a grid with target occupancy. Transmitter circuitry 118 may generate beam 244 in the spatial domain using time-domain codes for transmission via antenna element 126.

[0102] The transmitted signal can impact K point targets within the radar's field of view. The launching direction of the beam 244 impacting the i-th target can be defined as θ. i Considering the TX with elements spaced at half wavelengths, the transmitter circuit at 118 is oriented towards direction θ. j The array response vector can be constrained as follows:

[0103]

[0104] Where 'a' represents the array response vector of the array of transmitter elements 126. Each beam 242 has a response vector along direction β. i The beamforming gain, and x i This represents an NF×1 unit modulo time code transmitted along direction i. The space-time code W can be determined as follows:

[0105]

[0106] Matched filter 250 may include a range-domain matched filter that can determine the distances to K targets using a set of correlators. It can be executed with X. i The correlation is used to determine the target along direction i. Assuming the target lies on a range-angle 2D grid, Equation 5 can be rewritten as follows:

[0107]

[0108] in

[0109] Where μ1 can represent the l-th column of the N×N Discrete Fourier Transform (DFT) matrix, and x i It can represent time-domain codes.

[0110] In the illustrated example, cells 246 and 248 are shown. Cell 246 can be indexed as i,j, and cell 248 can be indexed as k,j. At radar receiver circuit 128, the reflected radar echo (reflection) can be down-converted and sampled. Receiver circuit 128 may apply one or more matched filters 250. In one or more embodiments, matched filter 250 may include a two-dimensional matched filter that filters for range and angle to detect one or more targets. Matched filter 250 may include an angle-domain matched filter 252 that can be configured for beamforming directions α(θ1), α(θ2), ..., α(θ... N Each of the following is implemented to determine the direction of arrival (DoA). Receiver circuitry 128 can be configured to estimate the DoA using a Discrete Fourier Transform (DFT), which can process a discrete grid of N angular partitions. In one or more embodiments, an N-sized DFT can be applied to the sampled signal measured by the array of antenna elements 142.

[0111] Assuming K targets are located on a discrete grid described by the columns of a DFT matrix, then the angle θ k Make πsin(θ) k ) is 2π / N tx Integer multiples of θ. For direction θ j where j = 1, 2, ..., N tx The output of the angle-domain matched filter 252 can be expressed as follows:

[0112]

[0113] Where y(i,j) represents the output of the two-dimensional matched filter, and the term The first term represents the response from the cell of interest, the second term corresponds to the response from other cells along the partition at angle j, and the term v(i,j) represents the filtered noise. Term β j Let x represent the beamforming gain along direction j, and x i This indicates the time domain code.

[0114] The second term in Equation 7 can represent the contribution of different targets within the same angular partition to the output of the matched filter, which may lead to false alarms and reduce the detection capability of the system. However, false alarms can be reduced by using a time-domain code with a low correlation level. In one or more embodiments, the output of the angle-domain matched filter 252 may be separable in the angle domain, such that each row of the matrix of the angle-domain matched filter 252 may include data from the corresponding time-domain waveform x. iThe transmitted echo. After angle-domain processing by angle-domain matched filter 252, matched filtering can be performed for distance estimation by applying time-domain matched filter 254 of each time-domain waveform to the corresponding row of the matrix output of angle-domain matched filter 252 to retrieve distance information along each angle grid direction.

[0115] For this distance estimation, when the (i,j)th angular distance partition contains a target with index k, the autocorrelation vector r in the output y(i,j) of the angular-distance matched filter in Equation 7 is... x The following limitations may be imposed:

[0116]

[0117] Where L represents the sample length of each baseband waveform transmitted at each transmitter element 126, and n represents the selected transmitter element 126.

[0118] It should be understood that the space-time code matrix W is spatially and temporally separable and can be used individually to perform temporal matched filtering on each direction of the angular grid using one or more temporal matched filters 254. When the number of receivers N... rx Equal to the number of transmitters N tx At that time, the time-domain components become separable along different directions of the angular grid.

[0119] Figure 3 Images, generally indicated at 300, are depicted according to various embodiments, including a lane topology map 302 and a drivable space map 320 determined by a system including radar system 101. In the illustrated example, the radar device 102 of the vehicle 150 can emit radar signals (generally indicated at 242) and receive reflected signals in response thereto. Radar system 101 can determine distance, angle, and Doppler information associated with the reflected signals and can correlate the data to determine the drivable space map 320.

[0120] In the drivable space map 320, the distance z j This represents the drivable space in direction i up to the first obstacle. The drivable space map 320 can indicate the drivable distance in terms of distance partitioning, where distance represents the space between the vehicle and the nearest boundary (e.g., building, guardrail, etc.) along each angular grid direction. The spatiotemporal code W is designed to maximize the detection probability at each (i,j) cell within the drivable space with an uncertain target occupancy rate.

[0121] Assume α k The probability of detecting target k in the (i,j) partition, which is proportional to the target's radar cross-section (RCS) and follows a complex Gaussian distribution with a single variance (for simplicity), can be determined as follows:

[0122]

[0123] The term below the square root represents the ratio between the signal power at the output of the matched filter and the noise power plus the power of the shadows from other targets in the same angular partition. Since Q(·) is an increasing function, the detection probability increases with the ratio of signal power to noise plus the shadows between targets. Additionally, the term d... p Let represent the distance to the p-th target, and ki represent the number of targets along direction i.

[0124] To determine the weighted detection probability at each cell, the weights in Equation 7 can be selected based on the information entropy of the occupancy probability at each cell. The information entropy of the occupancy probability measures the uncertainty of the target's presence in the cell of interest. Since the transmitted signal includes a time-domain code, the entropy of the weighted detection probability is a function of both the spatial and time-domain codes. Considering a single Doppler partition (N... d =1), the maximization of the weighted detection probability can be written as follows:

[0125] Subject to

[0126] Where H() represents the information entropy function. The constraints in Equation 10 ensure that the radiated power is limited, that is, For waveforms with a structure according to Equation 7 above, the constraints can be determined as follows:

[0127]

[0128] The last equation stems from the orthogonality of the DFT matrices. Maximizing equation 10 is a non-concave problem with non-convex constraints. Considering only the effect of noise, the probability function Pd in ​​equation 10 depends only on the signal-to-noise ratio, making maximization dependent on the design of the time-domain code.

[0129] In order to connect the constraints with the time-domain code x i The design decoupling allows the time-domain code to be implemented as a vector with length N. rx A vector of all 1s. Then, the power constraint simplifies to the following inequality:

[0130]

[0131] This controls the total beamforming gain of the array of transmitter elements 126. Equation 10 can then be solved independently of the time-domain code.

[0132] To determine distance data, a time-domain waveform x can be selected. iThis is to reduce the contribution to the output of the angle-domain matched filter 252 due to different targets existing within the same angular partition. It should be recognized that, in a given direction i, a target may be at up to a drivable distance z. i The distance exists. To reduce the contribution from different targets within the interest angle partition, we can target values ​​smaller than z. i Minimize the hysteresis of the i-th time-domain code r xi The autocorrelation. Minimizing the autocorrelation can be determined as follows:

[0133]

[0134] Make |x i | = 1 and

[0135] Assume that static clutter removal techniques can be used to mitigate reflections from targets originating from the boundary or outside the drivable space. Solving the minimization problem yields a sequence that reduces unwanted contributions to the matched filter output due to targets located within the road boundary and along the same direction as the target of interest. This is done in calculating the beam gain β. i and time domain code x i Then, the spacetime code can be easily obtained using Equation 6.

[0136] The drivable space map 320 is depicted as a bar chart, where various bars can represent data determined from various angular (orientation) partitions indexed i. For example, partition corresponding to partition 0 can be indicated at 422, while partition k can be indicated at 424. In one or more embodiments, the radar system 101 can be configured to determine a fast timecode in the time domain, such that d j The sidelobe level of the autocorrelation function within the cell is minimized according to the following equation:

[0137]

[0138] Make

[0139] In one or more embodiments, radar system 101 may be a multiple-input multiple-output (MIMO) radar capable of beamforming at transmitter circuitry 118 and estimating the direction of arrival of reflected signals at receiver circuitry 126. The beam at radar transmitter circuitry 118 may utilize available side information about the sensed environment (e.g., drivable space map 320, occupancy grid map 220, etc.). Figure 2 The radar system 101 can be configured to adjust the waveform it transmits based on information provided by the side information (including other data, or any combination thereof).

[0140] The all-digital antenna element 126 allows for the transmission of individual time-domain waveforms at each antenna element 126, which can be used to increase the detection capability of the radar system 101. When occupancy information about the environment is available, the space-time waveforms generated by the radar system 101 can be optimized to enhance detection in areas where the presence of a target is uncertain.

[0141] In one or more embodiments, transmitter circuitry 118 may be configured to transmit space-time codes that are separable in the time and spatial domains. The spatial domain beam may be configured to focus transmission power toward regions of high occupancy uncertainty, while the time domain codes may be configured to enhance target detection at the output of the time-matched filter for targets within regions of high occupancy uncertainty.

[0142] variable α i,j It is proportional to the target's radar cross-section (RCS). Referring to the maximized entropy-weighted detection probability in Equation 2 above, the target detection probability P d This can be understood as follows:

[0143]

[0144] Where Q represents the Q-function, P fa SINR represents the false alarm probability, and SINR represents the signal-to-interference-plus-noise ratio of a cell.

[0145] The signal-to-interference-plus-noise ratio (SINR) can be determined using the following equation:

[0146]

[0147] The numerator represents the signal power, while the denominator represents the power response from other cells along angle partition j plus the noise factor σ. 2 .

[0148] Maximum entropy equation 2 can be rewritten to include beamforming gain, as follows: Subject to

[0149] To design the space-time code W at transmitter circuit 118 (or radar controller 108), a two-dimensional occupancy map defined in range-angle partitions is determined. In the example, item It represents the probability that the target exists in the (i,j)th partition. This can be achieved by assuming ideal fast time codes x1, x2, ..., xj. N To optimize beamforming gain. For each partition, the distance r to the target or object can be determined as follows:

[0150]

[0151] It can be observed that the Gaussian distributed response from other cells increases monotonically with SINR. Therefore, SINR increases by minimizing the power response from other cells along each direction j, as follows:

[0152] minimize in

[0153]

[0154] In one or more embodiments, transmitter circuit 118 can periodically transmit bursts of M pulses within a radar coherent processing interval (CPI). The transmission power can be determined by P. tx Instructions. The transmitted signal can impact K point targets within the radar's field of view. The departure direction associated with the k-th target can be defined as θ. k .

[0155] The radar beam emitted by the antenna element 126 of transmitter 118 can generate sidelobes 244 that can introduce interference. To reduce the effect of such sidelobes 244, receiver circuitry 128 or signal processor 108 can process the received data according to the following equation to minimize the weighted integral sidelobe level of fast-time autocorrection:

[0156]

[0157] Make

[0158] Each transmitted beam from radar system 101 may include a time-domain code. Where T represents time and j represents the angle partition index. The weight w can be selected as follows:

[0159]

[0160] Where N j This represents the distance partition index associated with the maximum drivable distance along direction j.

[0161] Figure 4A Figure 400 depicts the relationship between the autocorrelation level and autocorrelation hysteresis of the Zadoff-Chu waveform determined by a conventional radar system. In this example, the autocorrelation function is shown for a selected range. In this example, the maximum range at which the target may be located is approximately 40 meters, which corresponds to approximately 200 range zones. The autocorrelation of the Zadoff-Chu function can be approximately -45 dB in the area of ​​interest.

[0162] Figure 4B Depicting various embodiments Figure 1-2Figure 420 shows the relationship between the autocorrelation level and autocorrelation hysteresis of the radar system. In this example, the spatiotemporal code implementation is used in conjunction with an autocorrelation function for the region of interest. In this example, with... Figure 4A Compared to the autocorrelation map 400 in the previous version, using prior information (a drivable space map or occupancy grid) and spatial and temporal processing of the reflected signal can produce an autocorrelation level that is up to 125 dB smaller.

[0163] This reduction in the autocorrelation plot ensures that echoes from targets within the same angular partition as the target cell of interest are minimized at the output of the time-domain matched filter 254. Outside the region of interest, the designed waveform exhibits higher correlation than the Zadoff-Chu sequence. However, prior information (drivable space map or occupancy grid) ensures that known correlated targets do not occupy those areas, so the higher correlation outside the region of interest does not affect performance within the drivable range. Static clutter removal techniques can be used to mitigate echoes from static targets appearing outside the drivable range.

[0164] Space-time waveform design can significantly improve the probability of correct object detection, even when the probability of false alarms increases. The following section discusses... Figure 5A and 5B Examples describing performance results.

[0165] Figure 5A Depicting Zadoff-Chu waveforms (sequences) according to various embodiments and Figure 1-2 Figure 500 shows the relationship between the detection probability and the false alarm probability of a radar system with a signal-to-noise ratio of 10 dB. The waveform depicts the receiver operating characteristic (ROC) curve of the receiver circuit 128 used for target detection. Assuming that twenty (20) targets are located at random distances from the radar along each grid direction, the targets have random radar cross sections (RCS) following a Gaussian distribution with a single variance. The noise is scaled so that the signal-to-noise ratio (SNR) of a single RCS target is 10 dB. In this example, the number of samples N is 1024, and the drivable space N in the range partition is N. j The number is 300, the number of targets is fifty, and the signal power of each target is zero dB. The technology described above regarding radar system 101 is approximately 10 -4 It outperforms the Zadoff-Chu algorithm by approximately 0.37 dB at false alarm probabilities, and continues to outperform the Zadoff-Chu algorithm until the false alarm probability is greater than 10. -2 .

[0166] Figure 5B Depicting Zadoff-Chu waveforms (sequences) according to various embodiments and Figure 1-2Figure 520 shows the relationship between the detection probability and the false alarm probability of a radar system with a signal-to-noise ratio of 0 dB. In this example, the number of samples N is 1024, and the drivable space N in the distance partition is... j The number is 300, the number of targets is fifty, and the signal power of each target is zero dB. The technology described above regarding radar system 101 is approximately 10 -4 It outperforms the Zadoff-Chu algorithm by approximately 0.30 dB at a false alarm probability, and continues to outperform the Zadoff-Chu algorithm until the false alarm probability is approximately 10. -2 .

[0167] exist Figure 5A and 5B In the figure, radar system 101 is shown to achieve a higher detection probability than systems using Zadoff-Chu waveforms. In another embodiment, for 10... -4 The PFA of radar system 101 outperforms systems using Zadoff-Chu waveforms by up to 0.5 dB. This is achieved by minimizing z... i By analyzing the time-domain autocorrelation function within the time domain, the proposed method can more reliably detect multiple targets within the same angular partition.

[0168] Figure 6A Figure 600 depicts the relationship between the matched filter output and time lag / distance partition for the Zadoff-Chu sequence. Figure 600 is shown for a system with an SNR of 10 dB and a threshold fixed with a false alarm probability of 0.005. In this example, the detection probability is approximately 0.78 (78%).

[0169] Figure 6B Depicting various embodiments for Figure 1-2 Figure 620 shows the matched filter output of the label sequence of the radar system 101. Figure 620 is shown for a system with an SNR of 10 dB and a threshold fixed with a false alarm probability of 0.005. In this example, the detection probability is approximately 0.98 (98%). Due to the reduction in sidelobe levels within the range zone corresponding to the drivable distance, the radar system 101 can achieve a higher detection probability for a fixed false alarm probability.

[0170] Figure 7 A flowchart depicts a method 700 for generating an occupancy map based on spatial code data and time code data according to various embodiments. At 702, method 700 may include determining an occupancy grid map using processing circuitry of a radar system.

[0171] At 704, method 700 may include using processing circuitry to determine a beamforming weight vector based on an occupancy map. In one or more embodiments, the beamforming weight vector may include multiple weight vectors forming a matrix.

[0172] At 706, method 700 may include determining a time-domain code using processing circuitry. The time-domain code may be determined for each angle or each beam of the transmitter circuitry.

[0173] At 708, method 700 may include transmitting one or more radar signals using transmitter circuitry based on a beamforming weight vector and a time-domain code. In one or more embodiments, the time-domain code may be combined with beamforming weight vector information to generate multiple radar beams including the time-domain code.

[0174] At 710, method 700 may include receiving a reflected signal based on the transmitted radar signal at a receiver circuit. The reflected signal may indicate an object or target within the observation area of ​​radar system 101.

[0175] At 712, method 700 may include filtering the received reflected signal using an angle-domain matched filter to determine the direction of arrival and distance data of one or more targets. The angle-domain matched filter can be used to determine data for multiple angle partitions.

[0176] At 714, method 700 may include filtering the received reflected signal for each direction using a time-domain matched filter to determine a time-domain waveform. The time-domain matched filter can recover the time-domain code from the waveform, and the time-domain code can be used to autocorrelate the data from the reflected signal.

[0177] At 716, method 700 may include determining the probability of detecting a target based on the signal-to-noise ratio at each angle. In one or more embodiments, the probability of detecting a target may be determined by receiver circuitry 126 or by radar processing.

[0178] At 718, method 700 may include using time-domain waveforms to process probabilistic data to reduce the contributions from different targets within the same orientation partition. In one or more embodiments, time-domain codes may be used to autocorrelate the data, thereby reducing sidelobe interference.

[0179] At 720, method 700 may include generating an occupancy map based on the processed probability data.

[0180] In conjunction with the above text about Figure 1-7The described systems, methods, apparatus, and figures disclose a radar system 101 including one or more transmitter circuits 118 coupled to a plurality of antenna elements 126. The transmitter circuits 118 are configured to determine prior information about an observation area of ​​the radar, determine a time-domain code, and perform beamforming to selectively transmit one or more beams including the time-domain code toward the observation area. The radar system 101 may include one or more receiver circuits 128 coupled to a plurality of antenna elements 142. The receiver circuits 128 are configured to determine prior information about the observation area, receive reflected signals from the observation area, determine spatial domain data based on the reflected signals, determine time-domain data based on the reflected signals, and determine one or more of an occupancy grid or driving lane map corresponding to the observation area based on the spatial domain data and the time-domain data.

[0181] While the foregoing discussion has focused primarily on MIMO spacetime radar systems, it should be understood that the methods described can be used in conjunction with other active sensing circuits, such as LiDAR (Light Detection and Ranging) circuits, ultrasonic circuits, and other active sensing circuits. One or more embodiments can be further understood based on the examples presented below.

[0182] Example 1: A method may include: receiving predetermined information about an observation area of ​​a radar system using a radar system; determining a beamforming weight vector based on the predetermined information by at least one transmitter circuit of the radar system, the beamforming weight vector defining a spatial domain beam; determining one or more time-domain codes by the at least one transmitter circuit based at least in part on the predetermined information; combining the spatial domain beam and the one or more time-domain codes using the at least one transmitter circuit to form a space-time waveform; and transmitting the space-time waveform at a selected angle toward the observation area of ​​the radar system using at least one transmitter circuit of the radar system.

[0183] Example 2: According to the method of Example 1, the predetermined information includes one or more of the following: distance data, angle data, or Doppler data corresponding to one or more objects within the observation area.

[0184] Example 3: The method according to either Example 1 or 2, wherein the predetermined information includes one or more of the following: an occupancy map, driving lane topology information including drivable areas with lane information, or an occupancy grid.

[0185] Example 4: The method according to any of Examples 1-3, wherein determining the predetermined information includes retrieving the predetermined information from a memory.

[0186] Example 5: The method according to any of Examples 1-4, wherein determining the beamforming weight vector may include: determining one or more occupancy probabilities based on the predetermined information at the at least one transmitter circuit; and determining the beamforming weight vector based on the one or more occupancy probabilities at the at least one transmitter circuit.

[0187] Example 6: The method according to any of Examples 1-5, wherein determining the one or more time-domain codes includes determining that one or more time-domain waveforms have reduced correlation with each other.

[0188] Example 7: The method described in any of Examples 1-6, wherein determining the one or more time-domain codes includes determining a time-domain waveform for each selected angle.

[0189] Example 8: The method according to any of Examples 1-7 further includes: receiving a reflected signal from the observation area of ​​the radar system using at least one receiver circuit of the radar system, the reflected signal being correlated with the space-time waveform; determining spatial domain data based on the reflected signal at the at least one receiver circuit, the spatial domain data including probability data indicating the probability of the presence of one or more objects in the observation area for a selected angle; determining time domain data corresponding to the time domain code from one or more of the reflected signal or the spatial domain data at the at least one receiver circuit; and determining, for each of the one or more selected angles, the probability that an object is within a selected area of ​​the observation area using the at least one receiver circuit based on the spatial domain data and the time domain data.

[0190] Example 9: According to the method of Example 8, determining the spatial domain data includes applying an angle domain matched filter to determine the direction of arrival and distance data for each of the selected angles.

[0191] Example 10: According to the method of Example 8, determining the time-domain data includes applying a time-domain matched filter to determine the time-domain data corresponding to the time-domain code of the space-time waveform.

[0192] Example 11: According to the method of Example 8, determining the time-domain data includes correlating distance information based on the time-domain data to determine one or more targets in the direction of the selected angle.

[0193] Example 12: According to the method of Example 11, making the distance information correlated includes reducing weighted sidelobe data based on the time-domain data.

[0194] Example 13: The method according to any of Examples 1-12, wherein the radar system is coupled to one of a vehicle or a mobile robot system.

[0195] Example 14: The method according to any of Examples 1-13, wherein sending the space-time waveform toward the observation area may include sending a plurality of shaped beams toward the observation area, and wherein the beamforming gain or beam pattern varies at different locations within the observation area.

[0196] Example 15: The method according to any of Examples 1-14, wherein sending the space-time waveform toward the observation area includes sending a plurality of shaped beams toward the observation area, each shaped beam including a selected time-domain code.

[0197] Example 16: A radar system may include: one or more transmitter circuits configured to transmit a space-time waveform toward an observation area, the space-time waveform including one or more shaped beams, the one or more shaped beams including time-domain codes; one or more receiver circuits configured to receive reflected signals associated with the space-time waveform; and a radar processor configured to: retrieve predetermined occupancy data of the position of an identified object relative to the radar system; determine a beamforming weight vector using the predetermined occupancy data; determine one or more time-domain codes using the predetermined occupancy data; generate the space-time waveform including one or more shaped beams, the one or more shaped beams including the one or more time-domain codes and based on the beamforming weight vector; and transmit the space-time waveform toward the observation area using the one or more transmitter circuits.

[0198] Example 17: In the radar system described in Example 16, the one or more time-domain codes are determined to reduce the autocorrelation of sidelobe information in the reflected signals received by the one or more receiver circuits.

[0199] Example 18: A radar system according to any of Examples 16 or 17, wherein one or more of the beamforming gain, beam pattern, or time-domain code varies relative to the position within the observation area.

[0200] Example 19: A radar system according to any of Examples 16-18, wherein each of the one or more receiver circuits may include: an angle-domain matched filter that determines direction-of-arrival data associated with one or more angles based on the space-time waveform; and a time-domain matched filter that correlates time-domain code data based on the space-time waveform to determine range information with reduced sidelobe interference.

[0201] Example 20: According to the radar system described in Example 19, the radar processor is configured to determine one or more of an updated occupancy grid or occupancy map based on determined direction-of-arrival data and determined distance information.

[0202] The foregoing detailed description is illustrative in nature only and is not intended to limit the embodiments of the subject matter or the application and use of such embodiments. As used herein, the word "exemplary" means "serving as an example, instance, or illustration." Any embodiment described herein as exemplary should not be construed as preferred or advantageous over other embodiments. Furthermore, there is no intention to be bound by any express or implied theory presented in the foregoing technical field, background art, or specific embodiments.

[0203] The connecting lines shown in the figures contained herein are intended to represent exemplary functional relationships and / or physical couplings between various elements. It should be noted that many alternative or additional functional relationships or physical connections may exist in embodiments of the subject matter. Furthermore, certain terms may be used herein for reference only and are therefore not intended to be limiting, and unless the context clearly indicates otherwise, the terms “first,” “second,” and other such numerical terms referring to structures do not imply order or sequence.

[0204] The foregoing descriptions refer to elements or features being "connected" or "coupled" together. As used herein, unless otherwise explicitly stated, "connected" means that one element is directly connected to (or directly communicated with) another element, and not necessarily mechanically. Similarly, unless otherwise explicitly stated, "coupled" means that one element is directly or indirectly connected to (or directly or indirectly communicated with, electrically or otherwise) another element, and not necessarily mechanically. Therefore, while the schematic diagrams shown depict an exemplary arrangement of elements, additional intervening elements, devices, features, or components may be present in embodiments of the depicted subject matter.

[0205] While at least one exemplary embodiment has been presented in the foregoing detailed description, it should be understood that numerous variations exist. It should also be understood that the one or more exemplary embodiments described herein are not intended to limit the scope, applicability, or configuration of the claimed subject matter in any way. In fact, the foregoing detailed description will provide those skilled in the art with a convenient guide for implementing the described embodiments or embodiments. It should be understood that various changes may be made to the function and arrangement of elements without departing from the scope defined by the claims.

Claims

1. A method characterized by, comprising: receiving, using a radar system, predetermined information about an observation region of the radar system; determining, by at least one transmitter circuit of the radar system, a beamforming weight vector based on the predetermined information, the beamforming weight vector defining a spatial domain beam; determining, by the at least one transmitter circuit, one or more time domain codes based at least in part on the predetermined information; combining, using the at least one transmitter circuit, the spatial domain beam and the one or more time domain codes to form a space-time waveform; and transmitting, using the at least one transmitter circuit of the radar system, the space-time waveform toward the observation region of the radar system at a selected angle.

2. The method of claim 1, wherein, the predetermined information includes one or more of range data, angle data, or Doppler data corresponding to one or more objects within the observation region.

3. The method of claim 1, wherein, the predetermined information includes one or more of an occupancy map, drivable lane topology information including lane with carriageway information, or an occupancy grid.

4. The method of claim 1, wherein, receiving the predetermined information includes retrieving the predetermined information from a memory.

5. The method of claim 1, wherein, determining the beamforming weight vector includes: determining, at the at least one transmitter circuit, one or more occupancy probabilities based on the predetermined information; and determining, at the at least one transmitter circuit, the beamforming weight vector based on the one or more occupancy probabilities.

6. The method of claim 1, wherein, determining the one or more time domain codes includes determining one or more time domain waveforms to have reduced correlation with respect to each other.

7. The method of claim 1, wherein, determining the one or more time domain codes includes determining a time domain waveform for each selected angle.

8. The method of claim 1, wherein, further comprising: receiving, using at least one receiver circuit of the radar system, reflected signals from the observation region of the radar system, the reflected signals being related to the space-time waveform; determining, at the at least one receiver circuit, spatial domain data based on the reflected signals, the spatial domain data including probability data indicating a probability of presence of one or more objects within the observation region for the selected angle; determining, at the at least one receiver circuit, time domain data corresponding to the time domain codes from one or more of the reflected signals or the spatial domain data; and and for each of one or more selected angles, determining, using the at least one receiver circuit, a probability of an object being within a selected region of the observation region based on the spatial domain data and the time domain data.

9. The method of claim 1, wherein, transmitting the space-time waveform toward the observation region includes: transmitting a plurality of shaped beams toward the observation region, and wherein a beamforming gain or a beam pattern varies at different locations within the observation region.

10. A radar system, characterized by comprising: one or more transmitter circuits configured to transmit a space-time waveform toward an observation region, the space-time waveform including one or more shaped beams, the one or more shaped beams including a time domain code; one or more receiver circuits configured to receive reflected signals related to the space-time waveform; and a radar processor configured to: retrieve predetermined occupancy data identifying locations of objects relative to the radar system; determine a beamforming weight vector using the predetermined occupancy data; determining one or more time domain codes using the predetermined occupancy data; generating the space-time waveform including one or more shaped beams, the one or more shaped beams including the one or more time domain codes and based on the beamforming weight vector; and transmitting the space-time waveform using the one or more transmitter circuits toward the observation region.

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