Radar signal processing in advanced driving assistance systems

Abstract

An advanced driving assistance system (ADAS) radar includes: at least one transmit antenna coupled with a vehicle, the at least one transmit antenna configured to transmit radar signals from the vehicle to a scene of interest; at least one receive antenna coupled with the vehicle, the at least one receive antenna configured to receive a reflected radar signal; and at least one processor. The processor is configured to execute the computer executable instructions to obtain a plurality of time samples of the reflected radar signal from the at least one receive antenna at specified periodic intervals, execute an autocorrelation algorithm on the obtained plurality of time samples, normalize a ratio of zero-order lag to first-order lag according to an output of the autocorrelation algorithm, and generate a normalized value of the zero-order lag to the first-order lag. And comparing the normalized ratio of the zero-order lag and the first-order lag to a specified threshold to determine whether the reflected radar signal includes the identified road clutter object.

Description

Cross-reference to related applications

[0001] This application claims priority to U.S. Patent Application No. 18 / 226,318, filed July 26, 2023. The entire disclosure of the above application is incorporated herein by reference. Technical Field

[0002] This disclosure relates to systems and methods for radar signal processing in advanced driver assistance systems (ADAS). Background Technology

[0003] For fixed radar, road or ground reflections (or ground clutter) occur at zero Doppler frequencies, so notch filters are typically used to filter them. Another approach (clutter mapping) can be performed, where static reflections are measured when no target is present. For airborne radar, ground clutter can be problematic, although the resolution volume is generally larger, and there may be both effective targets and clutter, so different approaches are usually employed. Furthermore, Advanced Driver Assistance Systems (ADAS) use radar to detect targets in front of the vehicle.

[0004] The background description provided herein is intended to give general context to this disclosure. It neither expressly nor implicitly acknowledges that the work of the inventors currently listed in the background section, and aspects that may not be described as prior art at the time of filing, are prior art to this disclosure. Summary of the Invention

[0005] An Advanced Driver Assistance System (ADAS) radar includes: at least one transmitting antenna coupled to a vehicle, the at least one transmitting antenna being configured to transmit radar signals from the vehicle toward a scene of interest; at least one receiving antenna coupled to the vehicle, the at least one receiving antenna being configured to receive reflected radar signals; and at least one processor. The processor is configured to execute computer-executable instructions to acquire a plurality of time samples of the reflected radar signals from the at least one receiving antenna at specified periodic intervals, perform an autocorrelation algorithm on the acquired plurality of time samples, normalize the ratio of zero-order hysteresis to first-order hysteresis based on the output of the autocorrelation algorithm, and compare the normalized ratio of zero-order hysteresis to first-order hysteresis with a specified threshold to determine whether the reflected radar signals include identified road clutter objects.

[0006] Among other features, the ADAS radar includes: a transmitting hardware chain coupled between a transmitting antenna and at least one processor; a receiving hardware chain coupled between a receiving antenna and at least one processor; and a local oscillator coupled between the transmitting hardware chain and the receiving hardware chain.

[0007] Among other features, the transmit hardware chain includes: a waveform generator; a mixer electrically coupled to the output of the waveform generator; a phase shifter electrically coupled to the output of the mixer; and a power amplifier electrically coupled to the output of the phase shifter.

[0008] Among other features, the receiver hardware chain includes: a low-noise amplifier; a mixer electrically coupled to the output of the low-noise amplifier; a filter electrically coupled to the output of the mixer; and an analog-to-digital converter electrically coupled to the output of the filter.

[0009] Among other features, the ADAS radar includes: at least one circulator or switch coupled to at least one of a transmitting antenna and a receiving antenna; a transmitting hardware chain coupled between at least one processor and at least one circulator or switch; a receiving hardware chain coupled between at least one processor and at least one circulator or switch; and a local oscillator coupled between the transmitting hardware chain and the receiving hardware chain.

[0010] Among other features, at least one processor is configured to process a reflected radar signal received, for example, in a range of 0.5 meters to 6 meters, or any other suitable height range. In other aspects, at least one processor is configured to determine that the reflected radar signal includes an identified road clutter object in response to a normalized ratio of zero-order hysteresis to first-order hysteresis exceeding a specified threshold.

[0011] Among other features, at least one processor is configured to determine that the identified road clutter object is not included in the reflected radar signal in response to a normalized ratio of zero-order hysteresis and first-order hysteresis being below a specified threshold.

[0012] Among other features, a threshold value including 1 is specified for the normalized ratio of zero-order hysteresis and first-order hysteresis. Among other features, the ADAS radar includes memory hardware configured to store one or more downlink algorithms that can generate clutter profiles based on clutter radar signal characteristics, perform radar signal processing using the clutter profiles, etc.

[0013] Among other features, the autocorrelation algorithm involves correlating the reflected radar signal with itself, and the reflected radar signal includes in-phase and quadrature components. The output of the autocorrelation algorithm can be used to identify the location of the maximum power of the identified road clutter object in the reflected radar signal.

[0014] Among other features, normalizing the ratio of zero-order hysteresis to first-order hysteresis includes calculating the product of the wavelength of the reflected radar signal and the sampling frequency of the reflected radar signal. Among other features, at least one processor is configured to: remove the identified road clutter object from image processing or assign a low-priority processing value to the identified road clutter object in response to determining that the identified road clutter object is present in the reflected radar signal.

[0015] Among other features, the autocorrelation algorithm may include convolution, Fourier transform, multiplication, inverse Fourier transform, or a combination thereof. Among other features, the duration of each of the specified periodic intervals used to obtain multiple time samples of the reflected radar signal is in the range of 100 microseconds to 150 microseconds, and at least one processor is configured to perform the autocorrelation algorithm on multiple time samples of a number in the range of 100 to 150 time samples. Among other features, the duration of each of the specified periodic intervals used to obtain multiple time samples of the reflected radar signal is 130 microseconds, and the number of multiple time samples used to perform the autocorrelation algorithm is 128 time samples.

[0016] A method for processing reflected radar signals includes: acquiring multiple time samples of the reflected radar signal from at least one receiving antenna at specified periodic intervals; performing an autocorrelation algorithm on the acquired multiple time samples; normalizing the ratio of zero-order hysteresis to first-order hysteresis based on the output of the autocorrelation algorithm; and comparing the normalized ratio of zero-order hysteresis to first-order hysteresis with a specified threshold to determine whether the reflected radar signal includes identified road clutter objects.

[0017] Among other features, the method includes: determining that the reflected radar signal includes the identified road clutter object in response to a normalized ratio of zero-order hysteresis to first-order hysteresis being higher than a specified threshold. Among other features, the method includes: determining that the reflected radar signal does not include the identified road clutter object in response to a normalized ratio of zero-order hysteresis to first-order hysteresis being lower than a specified threshold.

[0018] A computer program product for processing reflected radar signals includes a non-transitory computer-readable medium storing instructions executable by a processor to acquire multiple time samples of the reflected radar signal from at least one receiving antenna at specified periodic intervals, perform an autocorrelation algorithm on the acquired multiple time samples, normalize the ratio of zero-order hysteresis to first-order hysteresis based on the output of the autocorrelation algorithm, and compare the normalized ratio of zero-order hysteresis to first-order hysteresis with a specified threshold to determine whether the reflected radar signal includes identified road clutter objects.

[0019] Other areas of application of this disclosure will become apparent from the detailed description, claims, and accompanying drawings. The detailed description and specific examples are for illustrative purposes only and are not intended to limit the scope of this disclosure. Attached Figure Description

[0020] This disclosure will be more fully understood in light of the detailed description and accompanying drawings.

[0021] Figure 1 This is a functional block diagram of an example hardware configuration for radar signal processing in an Advanced Driver Assistance System (ADAS).

[0022] Figure 2 This is a functional block diagram of another example hardware configuration for radar signal processing in Advanced Driver Assistance Systems (ADAS).

[0023] Figure 3 yes Figure 1 or Figure 2 The following is a functional block diagram of an example launch hardware chain for the system.

[0024] Figure 4 yes Figure 1 or Figure 2 The following is a functional block diagram of the system's example receiving hardware chain.

[0025] Figure 5 This is a flowchart describing an example method for radar signal processing in an Advanced Driver Assistance System (ADAS).

[0026] In the accompanying drawings, reference numerals may be used repeatedly to identify similar and / or identical elements. Detailed Implementation

[0027] A radar illumination scene can include targets of interest as well as clutter objects that are less relevant to a given application. For example, in Advanced Driver Assistance Systems (ADAS) radar, road reflections can be classified as clutter objects. Road clutter reflections waste computation time, storage space, and transmission bandwidth of the radar processing system, and may lead to the loss or omission of valid targets.

[0028] In the various example embodiments described herein, clutter identification algorithms can identify road reflections and completely remove them from image processing analysis, or place road reflections with a lower priority, etc.

[0029] An ADAS radar system includes a transmitting hardware chain. This chain may include, for example, oscillators, frequency multipliers, mixers, power amplifiers, and power dividers. An ADAS radar system also includes a receiving hardware chain. This chain may include, for example, power amplifiers, mixers, and frequency filters.

[0030] In some example embodiments, the ADAS radar system may include an antenna system configured to transmit and receive electromagnetic waves, such as laser signals, optical signals (e.g., a lidar system), etc. In various embodiments, the system may include one or more transmitting antennas, one or more receiving antennas, a bidirectional antenna operating as both a transmitting and receiving antenna, etc. An oscillator may be configured to provide a phase-coherent reference for the transmitted and received signals.

[0031] The system may include one or more processors for performing mathematical operations, autocorrelation algorithms, normalization, etc. For example, one or more processors (e.g., processor modules or processor hardware) may perform "integer arithmetic" or "floating-point arithmetic" and have the capability to perform mathematical operations such as correlation, addition, subtraction, multiplication, division, comparison, etc. The system may include memory hardware for storing algorithms that use the output of autocorrelation algorithms to generate clutter profiles, clutter detection thresholds, etc., related to radar signal characteristics of road clutter objects.

[0032] In some example embodiments, the processor can be configured to estimate whether the received radar reflection signal originates from the road surface. For example, algorithms can be used directly to estimate or identify whether the received radar reflection signal originates from the road surface (indicating less interesting road clutter objects) or from other more interesting targets (e.g., larger objects such as other vehicles or pedestrians). Detected road reflection data can be completely removed from image processing, given lower priority in image processing, etc.

[0033] As described above, some example embodiments may include any suitable configuration of transmit chain hardware, receive chain hardware, antennas with phase coherence (e.g., a fixed relationship between the transmitted signal and the reference signal), etc. In some example software implementations, various mathematical operations can be implemented to achieve effects similar to those of alternative or combined hardware methods.

[0034] An ADAS radar mounted at the front of a vehicle can be configured to detect oncoming traffic, but it can also continuously detect road surface reflections (e.g., in the z-direction, for example, at the radar mounting height (e.g., 50 cm or below the radar)). In some example embodiments, the processor can be configured to determine whether the radar reflection signal originates from a single large target (e.g., a person or vehicle 10 cm or larger) or from a larger number of smaller targets (e.g., multiple small targets on the road less than one millimeter in size). For example, defects in the road can scatter the reflected radar signal and provide minute variations from one radar transmission to the next.

[0035] Example implementations can use road clutter detection algorithms to free up image processing bandwidth and storage, avoid false object identification, and prevent missing true target objects when limited processing is available. For example, alternative methods do not provide detection of any signals below the radar height to avoid road clutter, which may miss true target objects below, for example, a height level of 50 cm (or other suitable height cutoff), such as in a downhill radar scenario.

[0036] In various implementations, targets identified in the reflected radar signals are prioritized for processing. Identified road clutter objects can be assigned low priority. The processor can focus on identifying road clutter objects before applying filtering, as filtering in multiple dimensions (e.g., x, y, and z directions) can be difficult or require significant processing. Multiple pulses transmitted and received by the radar signal can be used to infer whether some reflected radar signals contain road clutter objects. For example, in some existing methods, road objects can be identified by processing information about the height of detected objects. In contrast, in some example embodiments, the algorithm can determine road clutter objects earlier in the processing to avoid wasting bandwidth, storage, computation, etc.

[0037] Radar signal processing system

[0038] Figure 1 This is a functional block diagram of an example hardware configuration 100 for radar signal processing in an Advanced Driver Assistance System (ADAS). Figure 1 As shown, the hardware configuration 100 includes a transmitting antenna 102, a receiving antenna 104, and a processing module 106.

[0039] The processing module 106 includes at least one processor 108 and a memory 110. The memory 110 may include, for example, one or more clutter thresholds 112, which can be used to identify detected road clutter objects in the reflected radar signal.

[0040] Hardware configuration 100 includes a transmitting hardware chain 114 electrically coupled to transmitting antenna 102. Transmitting antenna 102 may be coupled to a vehicle (e.g., mounted near the front of the vehicle) and may be configured to transmit radar signals from the vehicle toward a scene of interest (e.g., the radar may be on the vehicle facing forward, backward, or sideways). For example, the scene of interest may be a field of view in front of the vehicle, a field of view behind the vehicle, or a field of view to the side of the vehicle, etc. Examples of transmitting hardware chain 114 are referenced below. Figure 3 Further description.

[0041] like Figure 1As shown, hardware configuration 100 includes a receiver hardware chain 116 electrically coupled to receiver antenna 104. Receiver antenna 104 may be coupled to a vehicle (e.g., mounted near the front of the vehicle) and may be configured to receive reflected radar signals, such as reflections of radar signals emitted by transmitter antenna 102. An example of receiver hardware chain 116 is referenced below. Figure 3 Further description.

[0042] A local oscillator 118 is coupled between the transmitting hardware chain 114 and the receiving hardware chain 116. The local oscillator 118 can be configured to provide a phase-consistent reference for the received signal from the receiving hardware chain 116. Although Figure 1 The receiving hardware chain 116 is shown to be electrically coupled to the processing module 106, but in other embodiments, the transmitting hardware chain 114 may also be electrically coupled to the processing module 106 in addition to or independently of the receiving hardware chain 116.

[0043] Figure 2 This is another example hardware configuration 200 for radar signal processing in an Advanced Driver Assistance System (ADAS). (See diagram 200.) Figure 2 As shown, the hardware configuration 200 includes an antenna 203 and a processing module 206.

[0044] The processing module 206 includes at least one processor 208 and a memory 210. The memory 210 may include, for example, one or more clutter profiles 212, which can be used to identify detected road clutter objects in the reflected radar signal.

[0045] Antenna 203 may include a transmitting antenna, a receiving antenna, or a bidirectional antenna that includes both a transmitting antenna and a receiving antenna. Antenna 203 may be coupled to a vehicle, for example, mounted at the front of the vehicle.

[0046] At least one circulator and / or switch 220 is coupled to antenna 203. For example, antenna 203 may be configured to transmit radar signals in front of the vehicle and / or receive reflected radar signals, such as reflections of radar signals transmitted by antenna 203. Circulator and / or switch 220 may be configured to switch control of antenna 203 between a radar signal transmission operation mode and a reflected radar signal reception operation mode.

[0047] Hardware configuration 200 includes a transmitter hardware chain 214 electrically coupled to the circulator and / or switch 220. An example of the transmitter hardware chain 214 is referenced below. Figure 3 Further description. For example... Figure 2 As shown, hardware configuration 200 also includes a receiving hardware chain 216 electrically coupled to the circulator and / or switch 220. An example of the receiving hardware chain 216 is referenced below. Figure 3 Further description.

[0048] A local oscillator 218 is coupled between the transmitting hardware chain 214 and the receiving hardware chain 216. The local oscillator 218 can be configured to provide a phase-coherent reference for the received signal from the receiving hardware chain 216. Although Figure 2 The receiving hardware chain 216 is shown to be electrically coupled to the processing module 206, but in other embodiments, the transmitting hardware chain 214 may also be electrically coupled to the processing module 206 in addition to or independently of the receiving hardware chain 216.

[0049] Figure 3 This is a functional block diagram of an example transmitter hardware chain 300, which can be similar to... Figure 1 The launch hardware chain 114 or Figure 2 The launch hardware chain 214. For example... Figure 3 As shown, the processing module 306 controls the waveform generator 322 to generate radar signal waveforms.

[0050] The output of waveform generator 322 is electrically coupled to mixer 323. Mixer 323 can be configured to mix signals, maintain a fixed frequency, etc. The output of mixer 323 is electrically coupled to phase shifter 324. Phase shifter 324 can be configured to shift the phase of the radar signal waveform generated by waveform generator 322. The output of phase shifter 324 is electrically coupled to power amplifier 326.

[0051] Power amplifier 326 can be configured to amplify the phase-shifted waveform from phase shifter 324 and provide the amplified signal to transmitting antenna 302 (e.g., for transmitting radar signals in front of a vehicle). Although Figure 3 An example embodiment of the transmission hardware chain is shown, but other embodiments may include more or fewer components, electrically coupled hardware components in different suitable arrangements, for generating radar transmission signals, etc.

[0052] Figure 4 This is a functional block diagram of an example receive hardware chain 400, which can be similar to... Figure 1 The receiving hardware chain 116 or Figure 2 The receiving hardware chain 216. For example... Figure 4 As shown, the receiving antenna 404 is configured to provide the received radar reflection signal to the low-noise amplifier 428.

[0053] A low-noise amplifier 428 is configured to amplify the radar reflection signal received by the receiving antenna 404 and provide the amplified signal to a mixer 430. The mixer 430 is configured to mix the amplified signal and provide the mixed signal to a filter 432.

[0054] like Figure 4As shown, filter 432 is configured to filter the mixed signal received from mixer 430 and provide the filtered signal to analog-to-digital converter 434. Analog-to-digital converter 434 is configured to convert the analog filtered signal received from filter 432 into a digital signal and provide the digital signal to processing module 406. Although Figure 4 An example embodiment of the receiving hardware chain is shown, but other embodiments may include more or fewer components, electrically coupled hardware components in different suitable arrangements, for receiving reflected radar signals, etc.

[0055] Radar signal processing methods

[0056] Figure 5 This is a flowchart illustrating an example method for radar signal processing in an Advanced Driver Assistance System (ADAS). This method can be, for example... Figure 1 Processing module 106 or Figure 2 The processing module 206 executes.

[0057] The process begins at 504, via a transmitting antenna coupled to the vehicle (e.g., Figure 1 The transmitting antenna 102 or Figure 2 The transmitting antenna 202 transmits radar signals in front of the vehicle. At 508, the process includes: via a receiving antenna coupled to the vehicle (e.g., Figure 1 Receiving antenna 104 or Figure 2 The receiving antenna 204 receives reflected radar signals.

[0058] At point 512, the processing module can be configured to acquire multiple time samples of the reflected radar signal from the receiving antenna at specified periodic intervals. For example, from a physics perspective, receiving multiple samples at periodic intervals allows the processing module to determine the phase distribution of the reflected radar signal.

[0059] Any suitable periodic interval can be used, such as a periodic interval with a duration in the range of 100 to 150 microseconds (e.g., about 130 microseconds). Any suitable number of time samples of the reflected radar signal can be obtained for further processing as described below, such as multiple time samples in the range of 100 to 150 time samples (e.g., about 128 time samples).

[0060] At position 516, the processing module is configured to perform an autocorrelation algorithm on the acquired multiple time samples. Any suitable autocorrelation method can be used, such as convolution, Fourier transform, multiplication, inverse Fourier transform, or a combination thereof.

[0061] The final result of an autocorrelation algorithm can include the ratio of zero-order hysteresis to first-order hysteresis. For example, an autocorrelation algorithm can correlate a cell where one signal overlaps with another (e.g., using the same reflective radar signal twice, multiplying the signals and summing them, then shifting by one unit).

[0062] If the length of the reflected radar signal is L, the autocorrelation algorithm can perform an L-1 shift, then a factor of 1 shift, and overlap the shifted signals to perform multiplication and calculate the sum. This process can be repeated until overlap occurs (e.g., zero-order hysteresis). Shifting can continue, but this may not be necessary if the overlapping signals are the same reflected radar signal.

[0063] Zero-order hysteresis can refer to completely overlapping reflected radar signals, while first-order hysteresis can refer to overlapping reflected radar signals with one shift. For example, zero-order hysteresis can be calculated by multiplying each of the 128 samples by itself and then adding the results. In first-order hysteresis, sample 1 can be multiplied by sample 2 and then added, and so on.

[0064] At position 520, the processing module is configured to normalize the ratio of the zero-order hysteresis to the first-order hysteresis based on the output of the autocorrelation algorithm. For example, the sampling frequency can be considered as the reciprocal of the time interval between samples of the reflected radar signal. To eliminate the influence of the time interval between samples, the zero-order hysteresis and the first-order hysteresis can be normalized.

[0065] In this way, the same or similar thresholds for identifying road clutter can be used for different systems with different wavelengths or sampling parameters. For example, if the only parameter that changes between systems is the sampling frequency, the same or similar thresholds can be used. Normalization may include normalizing the ratio of zero-order hysteresis to first-order hysteresis using an exponential function, and may include the product of the radar signal wavelength and the sampling frequency.

[0066] At point 524, the processing module is configured to compare the normalized ratio of the zero-order lag to the first-order lag with a specified threshold. For example, if A is a zero-order lag and B is a first-order lag, the ratio of A / B can be compared with the specified threshold. For example, in the case where the ratio of the zero-order lag to the first-order lag is normalized, the example threshold can be 1. In an example embodiment where the ratio is not normalized, the specified threshold can be, for example, about 0.18.

[0067] If the ratio of zero-order hysteresis to first-order hysteresis is greater than a specified threshold, the processing module can determine that the reflected radar signal includes detected road clutter objects. If the ratio of zero-order hysteresis to first-order hysteresis is less than a specified threshold, the processing module can determine that the reflected radar signal includes real target objects (e.g., the reflected radar signal does not include road clutter objects).

[0068] For example, the processing module can use this ratio to determine whether there is an identified target (e.g., indicating a real target object) or whether there are many scattering objects (e.g., indicating road clutter objects of no interest). From a physics perspective, a wider phase distribution indicates more scattering targets, while a narrower phase distribution indicates a single target in the reflected radar signal.

[0069] The ratio of zero-order hysteresis to first-order hysteresis can be considered as an indication of the degree of phase change from one pulse / chirp of a radar signal to the next. A larger ratio indicates a greater difference between pulses, which may occur when multiple small road clutter targets are present. In contrast, larger real targets can provide a more stable reflection, with smaller changes between pulses, resulting in a smaller ratio below a specified threshold.

[0070] Refer again Figure 5 If the processing module determines at 528 that the normalized ratio of the zero-order hysteresis to the first-order hysteresis is greater than a specified threshold, control proceeds to 532 to determine that the reflected radar signal includes the identified road clutter object. Then, at 536, control assigns a lower image processing priority to the identified road clutter object.

[0071] If the processing module determines at 528 that the ratio of zero-order hysteresis to first-order hysteresis is less than a specified threshold, control proceeds to 540 to determine that the reflected radar signal does not include the identified road clutter object.

[0072] in conclusion

[0073] The foregoing description is illustrative in nature and is in no way intended to limit this disclosure, its application, or its use. The broad teachings of this disclosure can be implemented in various forms. Therefore, while this disclosure includes specific examples, its true scope should not be so limited, as other modifications will become apparent upon examination of the drawings, description, and appended claims. In the written description and claims, one or more steps in the method may be performed in a different order (or simultaneously) without altering the principles of this disclosure. Similarly, one or more instructions stored in a non-transitory computer-readable medium may be performed in a different order (or simultaneously) without altering the principles of this disclosure. Unless otherwise stated, the numbering or other designations of instructions or method steps are for convenience of reference only and do not indicate a fixed order.

[0074] Furthermore, although each embodiment is described above as having certain features, any one or more of those features described with respect to any embodiment of this disclosure may be implemented in and / or combined with features of any other embodiment, even if such combination is not explicitly described. In other words, the described embodiments are not mutually exclusive, and the arrangement of one or more embodiments with each other remains within the scope of this disclosure.

[0075] Spatial and functional relationships between components (e.g., between modules) are described using various terms, including “connection,” “joint,” “interface connection,” and “coupling.” Unless explicitly described as “direct,” when describing the relationship between the first and second components in the above disclosure, the relationship encompasses a direct relationship in which there are no other intermediate components between the first and second components, and also encompasses an indirect relationship in which there are one or more intermediate components (spatially or functionally) between the first and second components.

[0076] The phrase "at least one of A, B, and C" should be interpreted as using the non-exclusive logic "OR" to represent the logic (A or B or C), and should not be interpreted as meaning "at least one of A, at least one of B, and at least one of C". The term "set" does not necessarily exclude the empty set. The term "non-empty set" can be used to indicate the exclusion of the empty set. The term "subset" does not necessarily require a proper subset. In other words, a first subset of a first set can be exactly the same (equal to) the first set.

[0077] In the accompanying drawings, the direction of arrows, as indicated by the arrows, typically illustrates the flow of information of interest (e.g., data or instructions). For example, when components A and B exchange various types of information, but the information sent from component A to component B is relevant to the illustration, the arrow can point from component A to component B. This unidirectional arrow does not imply that no other information is being sent from component B to component A. Furthermore, for information sent from component A to component B, component B may send a request for that information or an acknowledgment of receipt of that information to component A.

[0078] In this application, including the following definitions, the term "module" or "controller" may be replaced by the term "circuit". The term "module" may refer to, be part of, or may include the following: processor hardware (shared, dedicated, or group) that executes code, and memory hardware (shared, dedicated, or group) that stores the code executed by the processor hardware.

[0079] This module may include one or more interface circuits. In some examples, the interface circuits may implement wired or wireless interfaces for connecting to a local area network (LAN) or a wireless personal area network (WPAN). Examples of LANs are IEEE Standard 802.11-2016 (also known as the Wi-Fi wireless network standard) and IEEE Standard 802.3-2015 (also known as the Ethernet wired network standard). Examples of WPANs are IEEE Standard 802.15.4 (including the ZIGBEE standard from the ZigBee Alliance) and the BLUETOOTH wireless network standard from the Bluetooth Special Interest Group (SIG) (including core specification versions 3.0, 4.0, 4.1, 4.2, 5.0, and 5.1 from the Bluetooth SIG).

[0080] Modules can communicate with other modules using interface circuitry. Although modules may be described in this disclosure as logically communicating directly with other modules, in various embodiments, modules may actually communicate via a communication system. Communication systems include physical and / or virtual network devices such as hubs, switches, routers, and gateways. In some embodiments, the communication system is connected to or spans a wide area network (WAN), such as the Internet. For example, the communication system may include multiple LANs interconnected via the Internet or peer-to-peer leased lines using technologies including Multiprotocol Label Switching (MPLS) and Virtual Private Networks (VPNs).

[0081] In various implementations, the functionality of a module can be distributed among multiple modules connected via a communication system. For example, multiple modules can implement the same functionality distributed by a load balancing system. In another example, the functionality of a module can be partitioned between a server (also known as a remote or cloud) module and a client (or user) module. For example, a client module can include a local application or a web application that executes on a client device and communicates with the server module over the network.

[0082] The terminology used above can include software, firmware, and / or microcode, and can refer to programs, routines, functions, classes, data structures, and / or objects. Shared processor hardware encompasses a single microprocessor that executes some or all of the code from multiple modules. Group processor hardware encompasses a microprocessor that, in conjunction with additional microprocessors, executes some or all of the code from one or more modules. References to multiple microprocessors encompass multiple microprocessors on discrete dies, multiple microprocessors on a single die, multiple cores of a single microprocessor, multiple threads of a single microprocessor, or a combination of the above.

[0083] Shared memory hardware refers to a single memory device that stores some or all of the code from multiple modules. Group memory hardware refers to a memory device that, in combination with other memory devices, stores some or all of the code from one or more modules.

[0084] The term memory hardware is a subset of the term computer-readable medium. As used herein, the term computer-readable medium does not cover transient electrical or electromagnetic signals propagating through a medium (e.g., on a carrier wave); therefore, the term computer-readable medium is considered tangible and non-transitory. Non-limiting examples of non-transitory computer-readable media are non-volatile memory devices (e.g., flash memory devices, erasable programmable read-only memory devices, or mask read-only memory devices), volatile memory devices (e.g., static random access memory devices or dynamic random access memory devices), magnetic storage media (e.g., analog or digital magnetic tape or hard disk drives), and optical storage media (e.g., CDs, DVDs, or Blu-ray discs).

[0085] The apparatus and methods described in this application can be implemented, partially or entirely, by a special-purpose computer created by configuring a general-purpose computer to perform one or more specific functions embodied in a computer program. Such apparatus and methods can be described as computerized apparatus and computerized methods. The aforementioned functional blocks and flowchart elements can serve as software specifications, which can be converted into computer programs through the routine work of skilled technicians or programmers.

[0086] A computer program includes processor-executable instructions stored on at least one non-transitory computer-readable medium. A computer program may also include or depend on stored data. A computer program may encompass a basic input / output system (BIOS) that interacts with the hardware of a special-purpose computer, device drivers that interact with specific devices of the special-purpose computer, one or more operating systems, user applications, background services, background applications, etc.

[0087] Computer programs may include: (i) descriptive text to be parsed, such as HTML (Hypertext Markup Language), XML (Extensible Markup Language), or JSON (JavaScript Object Notation); (ii) assembly code; (iii) object code generated by a compiler from source code; (iv) source code executed by an interpreter; (v) source code compiled and executed by a just-in-time (JIT) compiler; and so on. As an example only, source code may be written using syntax from languages ​​including: C, C++, C#, Object C, Swift, Haskell, Go, SQL, R, Lisp, Java®, Fortran, Perl, Pascal, Curl, OCaml, JavaScript®, HTML5 (Hypertext Markup Language, Fifth Revision), Ada, ASP (Active Server Pages), PHP (PHP: Hypertext Preprocessor), Scala, Eiffel, Smalltalk, Erlang, Ruby, Flash®, Visual Basic®, Lua, MATLAB, SIMULINK, and Python®.

Claims

1. An advanced driver assistance system (ADAS) radar comprising: at least one transmit antenna coupled with a vehicle, the at least one transmit antenna configured to transmit radar signals from the vehicle toward a scene of interest; at least one receive antenna coupled with the vehicle, the at least one receive antenna configured to receive reflected radar signals; and at least one processor configured to execute computer-executable instructions to perform operations of: obtaining a plurality of time samples of the reflected radar signals from the at least one receive antenna at specified periodic intervals; performing an autocorrelation algorithm on the obtained plurality of time samples; normalizing a ratio of a zero-lag and a first-lag according to an output of the autocorrelation algorithm; and comparing the normalized ratio of the zero-lag and the first-lag to a specified threshold to determine whether the reflected radar signals include an identified road clutter object.

2. The ADAS radar of claim 1, further comprising: a transmit hardware chain coupled between the transmit antenna and the at least one processor; a receive hardware chain coupled between the receive antenna and the at least one processor; and a local oscillator coupled between the transmit hardware chain and the receive hardware chain. the transmit hardware chain includes: a waveform generator; 3. The ADAS radar of claim 2, wherein, a mixer electrically coupled with an output of the waveform generator; a phase shifter electrically coupled with an output of the mixer; and a power amplifier electrically coupled with an output of the phase shifter. the receive hardware chain includes: a low noise amplifier; 4. The ADAS radar of claim 2, wherein, a mixer electrically coupled with an output of the low noise amplifier; a filter electrically coupled with an output of the mixer; and an analog-to-digital converter electrically coupled with an output of the filter.

5. The ADAS radar of claim 1, further comprising: at least one of a circulator or a switch coupled with at least one of the transmit antenna and the receive antenna; a transmit hardware chain coupled between the at least one of the circulator or the switch and the at least one processor; a receive hardware chain coupled between the at least one of the circulator or the switch and the at least one processor; and a local oscillator coupled between the transmit hardware chain and the receive hardware chain. the at least one processor is configured to process the reflected radar signals received from a radar field of view. the at least one processor is configured to determine that the identified road clutter object is included in the reflected radar signals in response to the normalized ratio of the zero-lag and the first-lag being above the specified threshold. the at least one processor is configured to determine that the identified road clutter object is not included in the reflected radar signals in response to the normalized ratio of the zero-lag and the first-lag being below the specified threshold.

6. The ADAS radar of claim 1, wherein, the specified threshold includes a value of 1 for the normalized ratio of the zero-lag and the first-lag.

7. The ADAS radar of claim 1, wherein, a memory hardware configured to store one or more downlink algorithms that generate a clutter profile based on a clutter radar signal characteristic or use a stored clutter profile for radar signal processing.

8. The ADAS radar of claim 7, wherein, ​ 9. The ADAS radar of claim 8, wherein, ​ 10. The ADAS radar of claim 1, further comprising: ​ 11. The ADAS radar of claim 1, wherein, The autocorrelation algorithm includes at least one of a convolution, a Fourier transform, a multiplication, and an inverse Fourier transform.

12. The ADAS radar of claim 1, wherein, 15. The ADAS radar of claim 1, wherein:

13. The ADAS radar of claim 1, wherein, each of the specified periodic intervals for obtaining the plurality of time samples of the reflected radar signal has a duration in a range of 100 microseconds to 150 microseconds; and 14. The ADAS radar of claim 1, wherein, the at least one processor is configured to perform the autocorrelation algorithm on the plurality of time samples in a quantity in a range of 100 time samples to 150 time samples.

16. The ADAS radar of claim 15, wherein: each of the specified periodic intervals for obtaining the plurality of time samples of the reflected radar signal has a duration of 130 microseconds; and the quantity of the plurality of time samples for performing the autocorrelation algorithm is 128 time samples.

17. A method of processing a reflected radar signal, the method comprising: obtaining a plurality of time samples of the reflected radar signal from at least one receive antenna at specified periodic intervals; performing an autocorrelation algorithm on the obtained plurality of time samples; normalizing a ratio of a zeroth lag to a first lag in accordance with an output of the autocorrelation algorithm; and comparing the normalized ratio of the zeroth lag to the first lag to a specified threshold to determine whether the reflected radar signal includes an identified road clutter object. determining that the reflected radar signal includes the identified road clutter object in response to the normalized ratio of the zeroth lag to the first lag being above the specified threshold. determining that the reflected radar signal does not include the identified road clutter object in response to the normalized ratio of the zeroth lag to the first lag being below the specified threshold.

20. A computer program product for processing a reflected radar signal, the computer program product comprising a non-transitory computer-readable medium storing instructions executable by a processor to perform operations of:

18. The method of claim 17, further comprising: obtaining a plurality of time samples of the reflected radar signal from at least one receive antenna at specified periodic intervals; 19. The method of claim 18, further comprising: performing an autocorrelation algorithm on the obtained plurality of time samples; normalizing a ratio of a zeroth lag to a first lag in accordance with an output of the autocorrelation algorithm; and comparing the normalized ratio of the zeroth lag to the first lag to a specified threshold to determine whether the reflected radar signal includes an identified road clutter object. ​ ​ ​

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