Radar interference mitigation

Abstract

Examples described herein provide a method for radio detection and ranging (radar) interference mitigation for a vehicle. The method includes receiving radar data captured by a radar device of the vehicle and indicative of an environment in which the vehicle is operating, the radar data including interference. The method also includes performing a time signal reconstruction on the radar data to generate first filtered data prior to performing a fast Fourier transform (FFT) on the radar data, where the FFT generates ranging data using the first filtered data. The method further includes, after performing the FFT on the ranging data, performing spectral signal reconstruction on the ranging data to generate second filtered data. The method also includes detecting an object in the environment based at least in part on the second filtered data.

Description

Technical Field

[0001] This topic relates to vehicles, and in particular to the mitigation of radio detection and ranging (radar) interference.

[0002] Modern vehicles (e.g., cars, motorcycles, boats, or any other type of vehicle) can be equipped with sensors (such as radar devices) to perform perception tasks. Radar involves emitting radio waves and detecting the echoes that bounce back when the emitted radio waves encounter an object. By measuring the time it takes for the echo to return and the frequency shift of the wave, a radar system can determine the distance, speed, and direction of travel of the object.

[0003] Perception tasks can include one or more of object detection, classification, tracking, lane detection, road sign recognition, and obstacle avoidance. Perception tasks are particularly useful for autonomous or semi-autonomous vehicles, providing them with real-time awareness of their environment to make safe and informed driving decisions. For example, data collected by radar equipment can be used to perform perception tasks. Summary of the Invention

[0004] In one embodiment, a method for mitigating radio detection and ranging (radar) interference for a vehicle is provided. The method includes receiving radar data captured by the vehicle's radar equipment and indicating the environment in which the vehicle operates, the radar data including interference. The method further includes performing a time-signal reconstruction on the radar data to generate first filtered data before performing a Fast Fourier Transform (FFT) on the radar data, wherein the FFT uses the first filtered data to generate ranging data. The method further includes performing a spectral signal reconstruction on the ranging data after performing the FFT on the ranging data to generate second filtered data. The method further includes detecting objects in the environment based at least in part on the second filtered data.

[0005] Additional to one or more features described herein, or as an alternative, other embodiments of the method may include: the time signal reconstruction including performing a detection phase and a reconstruction phase to detect interference values ​​within the radar data and interpolating substitute values ​​to replace the interference values.

[0006] Attached to one or more features described herein, or as an alternative, other embodiments of the method may include: the detection phase comprising determining the median absolute value of a time sample for each of a plurality of chirps across the radar data, determining the third quartile of the median, determining the interquartile range (IQR) using a subtraction of the third quartile and the first quartile, and identifying outliers based on a first threshold.

[0007] Attached to one or more features described herein, or as an alternative, further embodiments of the method may include: the detection phase including a first detection phase, and wherein the time signal reconstruction further includes a second detection phase, wherein the second detection phase includes determining a third quartile of the absolute sample values ​​across the plurality of chirps for each time index, determining an IQR by subtraction of the third quartile of the absolute sample values ​​and the first quartile of the absolute sample values, and identifying outliers based on a second threshold.

[0008] Additional to one or more features described herein, or as an alternative, other embodiments of the method may include: the reconstruction phase comprising detecting which points in the radar data are greater than the first threshold, and interpolating the replacement value based on neighboring points to replace the points greater than the first threshold.

[0009] Additional to one or more features described herein, or as an alternative, other embodiments of the method may include: the time signal reconstruction comprising performing a first detection phase, a first recovery phase, a second detection phase, and a second reconstruction phase to detect interference values ​​within the radar data and interpolate values ​​to replace the interference values.

[0010] Additional to one or more features described herein, or as an alternative, other embodiments of the method may include: the spectral signal reconstruction includes performing a detection phase and a reconstruction phase to detect interference values ​​within the ranging data and interpolate values ​​to replace the interference values, wherein the detection phase includes determining the median absolute value of distance samples of each of a plurality of chirps in the ranging data, determining the third quartile of the median, determining the interquartile range (IQR) using a subtraction of the third quartile and the first quartile, and identifying outliers based on a first threshold.

[0011] Attached to one or more features described herein, or as an alternative, further embodiments of the method may include: the detection phase including a first detection phase, and wherein the time signal reconstruction further includes a second detection phase, wherein the second detection phase includes determining a third quartile of the absolute sample values ​​across the plurality of chirps for each distance index, determining the IQR using a subtraction of the third quartile of the absolute sample values ​​and the first quartile of the absolute sample values, and identifying outliers based on a second threshold.

[0012] Additional to one or more features described herein, or as an alternative, other embodiments of the method may include: the reconstruction phase comprising detecting which points in the ranging data are greater than a first threshold, and interpolating replacement values ​​based on neighboring points to replace the points greater than the first threshold.

[0013] Additional to one or more features described herein, or as an alternative, other embodiments of the method may include: the spectral signal reconstruction comprising performing a first detection phase, a first recovery phase, a second detection phase, and a second reconstruction phase to detect interference values ​​within the ranging data and interpolate values ​​to replace the interference values.

[0014] In another embodiment, a vehicle is provided. The vehicle includes a radar device that emits radio waves and detects echoes that bounce back when the radio waves encounter an object. The vehicle also includes a processing system having a memory including computer-readable instructions and a processing device for executing the computer-readable instructions. The computer-readable instructions control the processing device to perform operations for radio detection and ranging (radar) interference mitigation. The operations include receiving radar data from the radar device, the radar data indicating the environment in which the vehicle operates, the radar data including interference. The operations include performing a time signal reconstruction on the radar data to generate first filtered data before performing a Fast Fourier Transform (FFT) on the radar data, wherein the FFT uses the first filtered data to generate ranging data. The operations include performing a spectral signal reconstruction on the ranging data to generate second filtered data after performing the FFT on the ranging data. The operations include detecting objects in the environment based at least in part on the second filtered data.

[0015] Attached to one or more features described herein, or as an alternative, another embodiment of the vehicle may include: the time signal reconstruction includes performing a detection phase and a reconstruction phase to detect interference values ​​within the radar data and interpolate substitute values ​​to replace the interference values.

[0016] Attached to one or more features described herein, or as an alternative, another embodiment of the vehicle may include: the detection phase comprising determining the median absolute value of a time sample for each of a plurality of chirps across the radar data, determining the third quartile of the median, determining the interquartile range (IQR) using a subtraction of the third quartile and the first quartile, and identifying outliers based on a threshold.

[0017] Attached to one or more features described herein, or as an alternative, another embodiment of the vehicle may include: the reconstruction phase comprising detecting which points in the radar data are greater than the threshold, and interpolating replacement values ​​based on neighboring points to replace the points greater than the threshold.

[0018] Attached to one or more features described herein, or as an alternative, another embodiment of the vehicle may include: the time signal reconstruction includes performing a first detection phase, a first recovery phase, a second detection phase, and a second reconstruction phase to detect interference values ​​within the radar data and interpolate values ​​to replace the interference values.

[0019] Attached to one or more features described herein, or as an alternative, another embodiment of the vehicle may include: the spectral signal reconstruction includes performing a detection phase and a reconstruction phase to detect interference values ​​within the ranging data and interpolate values ​​to replace the interference values.

[0020] Attached to one or more features described herein, or as an alternative, another embodiment of the vehicle may include: the detection phase comprising determining the median absolute value of distance samples across each of a plurality of chirps in the ranging data, determining the third quartile of the median, determining the interquartile range (IQR) using a subtraction of the third quartile and the first quartile, and identifying outliers based on a threshold.

[0021] Attached to one or more features described herein, or as an alternative, another embodiment of the vehicle may include: the reconstruction phase comprising detecting which points within the ranging data are greater than the threshold, and interpolating replacement values ​​based on neighboring points to replace the points greater than the threshold.

[0022] Attached to one or more features described herein, or as an alternative, another embodiment of the vehicle may include: the spectral signal reconstruction includes performing a first detection phase, a first recovery phase, a second detection phase, and a second reconstruction phase to detect interference values ​​within the ranging data and interpolate values ​​to replace the interference values.

[0023] In another embodiment, a method is provided. The method includes receiving radar data, captured by a vehicle's radar equipment and indicating the environment in which the vehicle operates, the radar data including interference. The method further includes performing initial filtering on the radar data using a low-pass filter to generate filtered radar data. The method further includes converting the filtered radar data from an analog signal to a digital form to generate digitally filtered radar data. The method further includes performing time signal reconstruction on the digitally filtered radar data to generate first filtered data. The method further includes performing a range fast Fourier transform (FFT) to convert the first filtered data from the time domain to the frequency domain to generate ranging data. The method further includes performing spatial signal reconstruction on the ranging data to generate second filtered data. The method further includes performing a Doppler FFT to analyze the frequency offset of the second filtered data. The method further includes performing digital beamforming after the Doppler FFT. The method further includes detecting objects in the environment, at least in part, based on the second filtered data, after performing the Doppler FFT and the digital beamforming.

[0024] This disclosure provides the following examples:

[0025] Example 1. A computer-implemented method for mitigating radio detection and ranging (radar) interference in vehicles, the method comprising:

[0026] Receive radar data, which is captured by the vehicle's radar equipment and indicates the environment in which the vehicle operates, including interference;

[0027] Before performing a Fast Fourier Transform (FFT) on the radar data, a time signal reconstruction is performed on the radar data to generate first filtered data, wherein the FFT uses the first filtered data to generate ranging data;

[0028] After performing the FFT on the ranging data, a spectral signal reconstruction is performed on the ranging data to generate second filtered data; and

[0029] Objects in the environment are detected based at least in part on the second filtered data.

[0030] Example 2. A computer-implemented method according to Example 1, wherein the time signal reconstruction includes performing a detection phase and a reconstruction phase to detect interference values ​​within the radar data and interpolate substitute values ​​to replace the interference values.

[0031] Example 3. A computer-implemented method according to Example 2, wherein the detection phase includes determining the median absolute value of a time sample for each of a plurality of chirps across the radar data, determining the third quartile of the median, determining the interquartile range (IQR) using a subtraction of the third quartile and the first quartile, and identifying outliers based on a first threshold.

[0032] Example 4. The computer-implemented method according to Example 2, wherein the detection phase includes a first detection phase, and wherein the time signal reconstruction further includes a second detection phase, wherein the second detection phase includes determining a third quartile of absolute sample values ​​across the plurality of chirps for each time index, determining an interquartile range (IQR) using a subtraction of the third quartile of the absolute sample values ​​and the first quartile of the absolute sample values, and identifying outliers based on a second threshold.

[0033] Example 5. A computer-implemented method according to Example 3, wherein the reconstruction phase includes detecting which points in the radar data are greater than the first threshold, and interpolating the replacement value based on neighboring points to replace the points greater than the first threshold.

[0034] Example 6. A computer-implemented method according to Example 1, wherein the time signal reconstruction includes performing a first detection phase, a first recovery phase, a second detection phase, and a second reconstruction phase to detect interference values ​​within the radar data and interpolate values ​​to replace the interference values.

[0035] Example 7. A computer-implemented method according to Example 1, wherein the spectral signal reconstruction includes performing a detection phase and a reconstruction phase to detect interference values ​​within the ranging data and interpolate values ​​to replace the interference values, wherein the detection phase includes determining the median absolute value of distance samples of each of a plurality of chirps in the ranging data, determining the third quartile of the median, determining the interquartile range (IQR) using a subtraction of the third quartile and the first quartile, and identifying outliers based on a first threshold.

[0036] Example 8. A computer-implemented method according to Example 7, wherein the detection phase includes a first detection phase, and wherein the time signal reconstruction further includes a second detection phase, wherein the second detection phase includes determining a third quartile of absolute sample values ​​across the plurality of chirps for each distance index, determining the IQR using a subtraction of the third quartile of the absolute sample values ​​and the first quartile of the absolute sample values, and identifying outliers based on a second threshold.

[0037] Example 9. A computer-implemented method according to Example 7, wherein the reconstruction phase includes detecting which points in the ranging data are greater than a first threshold, and interpolating replacement values ​​based on neighboring points to replace the points greater than the first threshold.

[0038] Example 10. A computer-implemented method according to Example 1, wherein the spectrum signal reconstruction includes performing a first detection phase, a first recovery phase, a second detection phase, and a second reconstruction phase to detect interference values ​​within the ranging data and interpolate values ​​to replace the interference values.

[0039] Example 11. A vehicle comprising:

[0040] A radar device that emits radio waves and detects the echoes that bounce back when the radio waves encounter an object;

[0041] Processing system, the processing system comprising:

[0042] Memory, including computer-readable instructions; and

[0043] Processing device for executing the computer-readable instructions, the computer-readable instructions controlling the processing device to perform operations for radio detection and ranging (radar) interference mitigation, the operations including:

[0044] Receive radar data from the radar device, the radar data indicating the operating environment of the vehicle, the radar data including interference;

[0045] Before performing a Fast Fourier Transform (FFT) on the radar data, a time signal reconstruction is performed on the radar data to generate first filtered data, wherein the FFT uses the first filtered data to generate ranging data;

[0046] After performing the FFT on the ranging data, a spectral signal reconstruction is performed on the ranging data to generate second filtered data; and

[0047] Objects in the environment are detected at least in part based on the second filtered data.

[0048] Example 12. The vehicle according to Example 11, wherein the time signal reconstruction includes performing a detection phase and a reconstruction phase to detect interference values ​​within the radar data and interpolate substitute values ​​to replace the interference values.

[0049] Example 13. The vehicle according to Example 12, wherein the detection phase includes determining the median absolute value of a time sample for each of a plurality of chirps across the radar data, determining the third quartile of the median, determining the interquartile range (IQR) using a subtraction of the third quartile and the first quartile, and identifying outliers based on a first threshold.

[0050] Example 14. The vehicle according to Example 13, wherein the reconstruction phase includes detecting which points in the radar data are greater than the threshold, and interpolating replacement values ​​based on neighboring points to replace the points greater than the threshold.

[0051] Example 15. The vehicle according to Example 11, wherein the time signal reconstruction includes performing a first detection phase, a first recovery phase, a second detection phase, and a second reconstruction phase to detect interference values ​​within the radar data and interpolate values ​​to replace the interference values.

[0052] Example 16. The vehicle according to Example 11, wherein the spectrum signal reconstruction includes performing a detection phase and a reconstruction phase to detect interference values ​​within the ranging data and interpolate values ​​to replace the interference values.

[0053] Example 17. The vehicle according to Example 16, wherein the detection phase includes determining the median absolute value of distance samples across each of a plurality of chirps of the ranging data, determining the third quartile of the median, determining the interquartile range (IQR) using the subtraction of the third quartile and the first quartile, and identifying outliers based on a threshold.

[0054] Example 18. The vehicle according to Example 17, wherein the reconstruction phase includes detecting which points in the ranging data are greater than the threshold, and interpolating replacement values ​​based on neighboring points to replace the points greater than the threshold.

[0055] Example 19. The vehicle according to Example 11, wherein the spectrum signal reconstruction includes performing a first detection phase, a first recovery phase, a second detection phase, and a second reconstruction phase to detect interference values ​​within the ranging data and interpolate values ​​to replace the interference values.

[0056] Example 20. A method comprising:

[0057] Receive radar data, which is captured by the vehicle's radar equipment and indicates the environment in which the vehicle operates, including interference;

[0058] The radar data is initially filtered using a low-pass filter to generate filtered radar data.

[0059] The filtered radar data is converted from analog signals to digital form to generate digitally filtered radar data;

[0060] The digitally filtered radar data is reconstructed using a time signal to generate first filtered data;

[0061] Perform a distance fast Fourier transform (FFT) to transform the first filtered data from the time domain to the frequency domain to generate ranging data;

[0062] Spatial signal reconstruction is performed on the ranging data to generate second filtered data;

[0063] Perform a Doppler FFT to analyze the frequency shift of the second filtered data;

[0064] Digital beamforming is performed after the Doppler FFT; and

[0065] After performing the Doppler FFT and the digital beamforming, objects in the environment are detected at least in part based on the second filtered data.

[0066] The above features and advantages, as well as other features and advantages of this disclosure, will become apparent when considered in conjunction with the accompanying drawings and the following detailed description. Attached Figure Description

[0067] Other features, advantages, and details appear only by way of example in the following detailed description, which refers to the accompanying drawings, wherein:

[0068] Figure 1 This is an illustration of a vehicle having a processing system for radar interference mitigation according to one or more embodiments;

[0069] Figure 2A It is for radar interference mitigation according to one or more embodiments. Figure 1 A block diagram of the processing system;

[0070] Figure 2B These are examples of radar data with interference according to one or more embodiments;

[0071] Figure 3 It is a block diagram of an environment for radar interference mitigation according to one or more embodiments;

[0072] Figure 4 This is a block diagram of a radar interference mitigation system for a vehicle according to one or more embodiments; and

[0073] Figure 5 This is a flowchart of a method for mitigating radar interference for a vehicle according to one or more embodiments. Detailed Implementation

[0074] The following description is exemplary in nature only and is not intended to limit this disclosure, its application, or use. It should be understood that throughout the drawings, corresponding reference numerals indicate similar or corresponding parts and features. As used herein, the term "module" refers to processing circuitry, which may include application-specific integrated circuits (ASICs), electronic circuitry, processors (shared, dedicated, or grouped) and memories executing one or more software or firmware programs, combinational logic circuitry, and / or other suitable components that provide the described functionality.

[0075] One or more embodiments described herein relate to radar interference mitigation.

[0076] Vehicles can use Advanced Driver Assistance Systems (ADAS) to improve vehicle performance and enhance driving comfort by providing automated, adaptive, or augmented vehicle systems to offer better perception, decision-making, and control. ADAS typically uses data from sensors (such as one or more radar devices, one or more LiDAR devices, proximity sensors, etc.), images from cameras, and other sources (including combinations and / or multiples of the above) to make decisions and control one or more aspects of the vehicle.

[0077] An example of ADAS is Adaptive Cruise Control (ACC), which automatically adjusts the speed of the lead vehicle to maintain a safe following distance from another vehicle ahead. Another example of ADAS is Automatic Lane Change (ALC), which enables the lead vehicle to change lanes. Yet another example is Forward Collision Alert (FCA), which generates an alert for the driver of the lead vehicle to warn of a potential forward collision. Another example of ADAS is Collision Emergency Braking (CIB), which applies the brakes to the lead vehicle to reduce its speed. Finally, another example of ADAS is Automatic Evasive Steering (AES), which adjusts the lead vehicle's trajectory.

[0078] While various ADAS systems are useful for their intended purposes, such systems can be negatively affected by radar interference. For example, vehicles equipped with radar are vulnerable to interference from another radar system (e.g., radar in another vehicle). Radar interference is expressed as an increase in the noise floor during radar processing, leading to increased false alarms (e.g., detecting objects that are not actually present) or hindering target detection (e.g., present objects are not actually detected). In automotive applications, false alarms may cause ADAS to malfunction, such as incorrect emergency braking or incorrect speed adjustment. Hindering target detection may prevent desired ADAS actions, such as preventing emergency braking or speed adjustment.

[0079] One or more embodiments described herein address these and other drawbacks by providing radar interference mitigation, particularly in automotive implementations. More specifically, one or more embodiments described herein perform time signal reconstruction and / or spectral signal reconstruction to reduce or eliminate interference in radar data. According to one or more embodiments, time signal reconstruction is performed in the time domain after analog-to-digital conversion sampling and before performing a range Fast Fourier Transform (FFT). Then, once the range FFT has been performed, spectral signal reconstruction is performed in the spectral (e.g., frequency) domain, identifying and removing anomalous energy spikes in the radar data. By identifying and replacing the interfered samples (e.g., time samples for time signal reconstruction and range samples for spectral signal reconstruction), the effects of interference are reduced.

[0080] It should be understood that the functionality of a vehicle implementing one or more embodiments described herein is improved. For example, the vehicle can reduce or eliminate interference in the radar signal, thereby generating more accurate data, which in turn enables the vehicle to make more accurate decisions in the context of ADAS. This is achieved, for example, by reducing or eliminating false alarms that lead to erroneous ADAS actions (such as incorrect emergency braking or incorrect speed adjustment), and / or by improving target detection to improve emergency braking or speed adjustment, resulting in improved vehicle operation.

[0081] Figure 1 This is an illustration of a vehicle 100 having a processing system 102 for radar interference mitigation according to one or more embodiments. The vehicle 100, also referred to herein as the "main vehicle," can be a car, truck, van, bus, motorcycle, boat, or any other type of automobile. According to one embodiment, the vehicle 100 includes an internal combustion engine that uses gasoline, diesel, or the like as fuel. According to another embodiment, the vehicle 100 is a hybrid electric vehicle that is partially or wholly powered by electricity. According to another embodiment, the vehicle 100 is an electric vehicle powered by electricity. According to one or more embodiments, the vehicle 100 is an autonomous or semi-autonomous vehicle. An autonomous vehicle is a vehicle with self-driving capability.

[0082] According to one or more embodiments, vehicle 100 includes a processing system 102 that provides radar interference mitigation. Further features of the processing system 102 will now be described with reference to Figures 2-5.

[0083] In particular, Figure 2A It is for radar interference mitigation according to one or more embodiments. Figure 1A block diagram of the processing system 102 is provided. The processing system 102 includes a processing device 202, a memory 204, and a detection engine 210 for radar interference mitigation. It should be understood that the processing system 102 can be any device suitable for performing radar processing. For example, the processing system 102 can be a device implemented in or otherwise associated with vehicle 100. As another example, the processing system 102 can be a smartphone, tablet computer, laptop computer, desktop computer, wearable computing device, and / or the like, including combinations and / or multiple devices of the foregoing.

[0084] Processing device 202 is any suitable processing circuitry for processing data and / or instructions. In various aspects of this disclosure, processing device 202 is a Reduced Instruction Set Computer (RISC) microprocessor or the like.

[0085] Memory 204 is any suitable device for storing data and / or instructions. Memory 204 may include one or more temporary and / or permanent memory devices, such as random access memory (RAM), read-only memory (ROM), and / or the like, including combinations of the above and / or multiple devices thereof.

[0086] The detection engine 210 uses radar data 212 to detect objects as further described herein. Radar data 212 may include data from one or more radar devices, such as radar device 104 associated with vehicle 100. Radar data 212 may include interference, such as interference caused by other radar devices (e.g., radar devices located in another vehicle). The detection engine 210 may analyze and process radar data 212 to remove or reduce interference. Figure 2B This is an example of radar data 212 with interference according to one or more embodiments (in this example, radar data 212 after range FFT). In this example, radar data 212 is shown according to the distance value 240 (e.g., in meters) (y-axis) for each chirp 241 (indexed) (x-axis). Vertical lines 242 represent interference. As described herein and as... Figure 2B As illustrated in the diagram, each chirped index (x-axis) includes distance data arranged in columns, and for each distance value 240 (y-axis), the chirped index is arranged in rows.

[0087] Continue to refer to Figure 2A According to one or more embodiments, the detection engine 210 performs time signal reconstruction and / or spectral signal reconstruction to reduce or eliminate interference in the radar data 212. According to one or more embodiments, time signal reconstruction (as referenced herein) is performed after analog-to-digital conversion sampling in the time domain and before performing the range FFT. Figure 4 and 5(Further described). Then, once the distance FFT has been performed, spectral signal reconstruction is performed in the spectral (e.g., frequency) domain (as referenced herein). Figure 4 and 5 (Further described), the spectrum signal reconstruction identifies and removes anomalous energy spikes in the radar data. By identifying and replacing the jammed samples, the interference effects within the radar data 212 are reduced, enabling the detection engine 210 to perform more accurate object detection, which can then be used to perform perception tasks, operate one or more ADAS systems, and / or directly operate the vehicle 100. References herein Figure 3-5 Other aspects and features of the detection engine 210 are described.

[0088] about Figure 2A The various components, modules, engines, etc. described herein (e.g., detection engine 210) may be implemented as instructions stored on a computer-readable storage medium, hardware modules, special-purpose hardware (e.g., special-purpose hardware, application-specific integrated circuits (ASICs), dedicated application-specific processors (ASSPs), field-programmable gate arrays (FPGAs), embedded controllers, hardwired circuits, etc.), or implemented as one or more combinations of these. According to various aspects of this disclosure, the various components, modules, engines, etc. described herein may be a combination of hardware and program. The program may be processor-executable instructions stored in tangible memory, and the hardware may include processing device 202 for executing these instructions. Thus, system memory (e.g., memory 204) may store program instructions that, when executed by processing device 202, implement the engine described herein. Other components, modules, engines, etc. may also be used to include other features and functionalities described in other examples herein.

[0089] According to one or more embodiments, vehicle 100 includes ADAS 214, which provides one or more advanced driver assistance functions. For example, ADAS 214 may provide one or more of ACC, ALC, FCA, CIB, AES and / or the like, including combinations of the above and / or multiples thereof.

[0090] Turn now Figure 3A block diagram of an environment 300 for radar interference mitigation according to one or more embodiments is shown. Environment 300 represents a real-world environment in which vehicles operate. In this example, environment 300 includes a road 301 having a first lane 301a and a second lane 301b. Vehicle 100 and target vehicle 310 occupy the first lane 301a, and interfering vehicle 320 occupies the second lane 301b. Radar device 104 of vehicle 100 transmits radio waves 304 in the form of a chirp 306. The chirp 306 is one of a plurality of signals transmitted by radar device 104 over time. According to one or more embodiments, radar device 104 uses frequency modulation, which increases or decreases the frequency of the radio waves (e.g., the chirp 306) over time. This method improves the determination of the distance to target vehicle 310 by enhancing resolution and reducing the effects of noise. Radar device 104 detects the echo 308 that bounces back when the transmitted radio waves (e.g., the chirp 306) encounter target vehicle 310. Chirp 306 and Echo 308 were together Figure 2A The detection engine 210 is used to determine the distance from vehicle 100 to target vehicle 310.

[0091] The jamming vehicle 320 includes a radar device 322 that also emits radio waves 324. When the jamming vehicle 320 is within a specific distance / proximity to the vehicle 100, these radio waves 324 interfere with the radar device 104 of the vehicle 100 in the form of jamming 326. For example, the distance / proximity that causes the jamming 326 is determined based on the range of the radar device 104, the range of the radar device 322, and environmental conditions (e.g., humidity, temperature, terrain / topography, etc., including combinations and / or multiples of the above).

[0092] Figure 4 This is a block diagram of a radar interference mitigation system 400 for a vehicle according to one or more embodiments. System 400 includes at least a radar device 104 and a detection engine 210.

[0093] In one embodiment, radar device 104 uses a linear frequency modulator (LFM) 402, and in other embodiments, other waveforms, to generate radio waves (e.g., radio wave 304) from transmitter (Tx) antenna 404. Radio waves encountering object 406 (e.g., target vehicle 310) are returned as echoes (e.g., echo 308) to receiver (Rx) antenna 408 of radar device 104. Receiver (Rx) antenna 408 also receives radio waves from jamming radar 410 (e.g., radar device 322 of jamming vehicle 320). At block 411, the radio waves received at receiver (Rx) antenna 408 (e.g., echoes of radio waves emitted by transmitter (Tx) antenna 404 and radio waves emitted by jamming radar 410) are combined with information from linear frequency modulator 402, and the resulting output is radar data 212.

[0094] Radar data 212 is received at the detection engine 210, which performs object detection. To this end, the detection engine 210 performs radar interference mitigation to remove or reduce interference in the radar data 212 caused by interfering radar 410, as now described. A low-pass filter (LPF) 412 performs initial filtering on the radar data 212 to remove high-frequency noise, prevent or reduce aliasing and interference, and allow the radar to focus on one or more desired signal components containing useful information about the target (e.g., target vehicle 310). The low-pass filter 412 enhances the signal-to-noise ratio of the radar data 212, improving the accuracy and clarity of detection and the measurement capabilities of the radar device 104. An analog-to-digital converter (ADC) 414 converts the radar data 212, received as an analog signal, into digital form. As now described, further processing can be performed on the digital representation of the radar data 212.

[0095] According to one or more embodiments, the detection engine 210 performs time signal reconstruction 416 to reduce or eliminate interference in the radar data 212. Time signal reconstruction 416 can be performed in such a way as to identify samples affected by each chirp (see...). Figure 2B Then, the affected samples for each chirp are recovered using the corresponding samples from the unaffected chirps.

[0096] Detection engine 210 performs a first detection phase, in which the median of each chirp is determined by the absolute values ​​of the samples across the time span. Then, detection engine 210 determines the third quartile of the median. Next, detection engine 210 uses the subtraction of the third quartile and the first quartile to determine the interquartile range (IQR) and identifies outliers based on a first threshold, which is the sum of the third quartile and the IQR of 1.5 times. More specifically, for a time-chirped signal x, the median of the absolute values ​​of the samples across each chirp is calculated using the following equation:

[0097] med1 = median(|x|).

[0098] The third quartile value q31 is calculated as follows:

[0099] q31 = percentile(med1, 0.75). Calculate IQR using the following equation:

[0100] IQR1 = IQR(med1).

[0101] The first threshold (th1) is calculated as follows:

[0102] th1 = q31 + 1.5IQR1.

[0103] Once the first detection phase is performed, the detection engine 210 performs a first recovery phase to interpolate the damaged sample based on neighboring samples. This is done by detecting which chirp medians are greater than a first threshold (th1). According to one or more embodiments, the interpolation (I) is determined using the following equation:

[0104] I = med1 ≥ th1 and

[0105] |x|=interpolation(I,~I,|x[~I]|).

[0106] Together, the first detection phase and the first recovery phase provide a global method for detecting interference values ​​within radar data 212 and reconstructing the interference values ​​using interpolation based on neighboring samples.

[0107] According to one or more embodiments, the detection engine 210 performs a second detection phase and a second reconstruction phase to provide a local method for detecting interference values ​​within radar data 212. The second detection and reconstruction phases together localize a threshold for each time period (or distance when operating in the spectral domain after the distance FFT). Figure 2B In other words, the second detection stage detects interference on a time-by-time basis and then reconstructs the interference value using interpolation of neighboring chirped samples based on that time.

[0108] The second detection and recovery phase examines the rows (time samples) to detect interference and interpolates the samples within that time period using samples from other chirps. More specifically, the second detection phase is performed using the following equation to perform detection on a time-by-time basis (e.g., Where k is each element in time:

[0109]

[0110] as well as

[0111]

[0112] The second reconstruction phase is performed using the following equation, where each line has its own threshold:

[0113] as well as

[0114]

[0115] It should be understood that in some embodiments, the time signal reconstruction 416 includes a first detection phase and a first recovery phase, while in some other embodiments, the time signal reconstruction 416 includes a first detection phase, a first recovery phase, a second detection phase, and a second reconstruction phase.

[0116] The time signal reconstruction 416 generates the first filtered data, which can be further processed as described here.

[0117] Once time signal reconstruction 416 has been performed, an FFT (e.g., distance FFT 418) can be performed to transform the first filter data from the time domain to the frequency (or distance) domain (see [link]). Figure 2B The range FFT 418 transforms the time-domain radar signal into the frequency domain. By analyzing the frequency components of the received signal, the range FFT 418 allows system 40 to accurately measure the distance to the target based on the time delay of the reflected signal (e.g., echo 308), thereby helping to determine the distance from vehicle 100 to the target.

[0118] After performing the range FFT 418, the detection engine 210 performs a spectrum signal reconstruction 420 to further reduce or eliminate interference in the radar data 212. The spectrum signal reconstruction 420 is performed similarly to the time signal reconstruction 416 described herein. That is, the spectrum signal reconstruction 420 may include performing a first detection, a first reconstruction, a second detection, and a second reconstruction to detect interference and interpolate values ​​to replace the interference values.

[0119] The spectrum signal reconstruction 420 generates second filtered data, which can be further processed as described now.

[0120] Then, the detection engine 210 performs a Doppler FFT 422 on the second filtered data to analyze the frequency shift (e.g., Doppler shift) of the received signal (e.g., echo 308) caused by the relative motion between vehicle 100 and target vehicle 310. The Doppler FFT 422 helps determine the relative velocity of the target, enabling the radar system to measure the speed at which the object moves toward or away from vehicle 100.

[0121] Following the Doppler FFT 422, the detection engine 210 performs digital beamforming (DBF) 424 to direct and shape the beam pattern of the antenna array (e.g., transmitter (Tx) antenna 404 and receiver (Rx) antenna 408). DBF 424 provides precise control over the beam direction by adjusting the phase and amplitude of the signals received or transmitted by each element of the antenna array (e.g., transmitter (Tx) antenna 404 and receiver (Rx) antenna 408), enabling improved target detection, tracking, and interference suppression.

[0122] Then, the detection engine 210 performs object detection using detector 426. Detector 426 identifies and locates objects (e.g., target vehicle 310). To do this, detector 426 determines the time delay and frequency offset of the echo (e.g., echo 308) to determine the distance and / or speed of target vehicle 310.

[0123] Turn now Figure 5 A flowchart of a method 500 for mitigating radar interference for a vehicle is provided according to one or more embodiments. Method 500 can be implemented using any suitable system or device. For example, method 500 can use... Figure 1 The processing system 102 and / or similar (including combinations of the above and / or multiples thereof) shall be used to implement this. Now refer to Figure 1-4 Method 500 is described, but method 500 is not limited to this.

[0124] Method 500 begins at block 502, where engine 210 is detected receiving radar data 212. Radar data 212 is captured by radar equipment 104 of vehicle 100 and indicates the environment in which the vehicle operates. That is, radar data 212 includes data representing the environment approaching (e.g., within the operational range of radar equipment 104) vehicle 100. Radar data 212 also includes interference (e.g., interference 326 from radar equipment 322 of interfering vehicle 320).

[0125] At block 504, detection engine 210 performs temporal signal reconstruction on radar data 212 to generate first filtered data as described herein, prior to performing an FFT (e.g., range FFT 418) on the radar data 212. The FFT uses the first filtered data to generate ranging data. According to one or more embodiments, temporal signal reconstruction includes performing a detection phase and a reconstruction phase to detect interference values ​​within the radar data and interpolate substitute values ​​to replace the interference values.

[0126] At box 506, the detection engine 210 performs spectral signal reconstruction on the ranging data after performing an FFT (e.g., a distance FFT 418) on the ranging data to generate second filtered data as described herein. According to one or more embodiments, the spectral signal reconstruction includes performing a detection phase and a reconstruction phase to detect interference values ​​within the ranging data and interpolate values ​​to replace the interference values.

[0127] At box 508, the detection engine 210 detects objects in the environment (e.g., target vehicle 310) based at least in part on the second filtered data.

[0128] Additional processes may also be included, and it should be understood that... Figure 5 The processes described herein are illustrative, and other processes may be added, or existing processes may be removed, modified, or rearranged without departing from the scope of this disclosure. It should also be understood that... Figure 5 The process described herein can be implemented as program instructions stored on a non-transitory computer-readable storage medium, when executed by a computing system (e.g., Figure 1 The processor of the processing system 102 (e.g., 2) Figure 2A When the processing device 202 is executed, the program instructions cause the processor to perform the process described herein.

[0129] The terms “a” and “an” do not indicate a limitation of quantity, but rather the presence of at least one of the referenced items. Unless explicitly indicated by the context, the term “or” means “and / or”. Throughout this specification, the reference to “an aspect” means that a particular element (e.g., a feature, structure, step, or characteristic) described in connection with that aspect is included in at least one aspect described herein and may be present or absent in other aspects. Furthermore, it is to be understood that the described elements may be combined in any suitable manner across various aspects.

[0130] When an element, such as a layer, film, region, or substrate, is referred to as being "on" another element, it can be directly on the other element, or there may be intermediate elements present. Conversely, when an element is referred to as being "directly on another element," there are no intermediate elements present.

[0131] Unless otherwise stated herein, all test standards are the most recent valid standards up to the filing date of this application (or, if priority is claimed, the filing date of the earliest priority application in which the test standard appeared).

[0132] Unless otherwise defined, the technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains.

[0133] While the above disclosure has been described with reference to exemplary embodiments, those skilled in the art will understand that various changes can be made and equivalents can replace elements of this disclosure without departing from its scope. Furthermore, many modifications can be made to adapt particular situations or materials to the teachings of this disclosure without departing from its essential scope. Therefore, it is intended that this disclosure be limited to the specific embodiments disclosed, but will include all embodiments falling within the scope of this disclosure.

Claims

1. A computer-implemented method for radio detection and ranging (RADAR) interference mitigation for a vehicle, the method comprising: receiving radar data captured by a radar device of the vehicle and indicative of an environment in which the vehicle operates, the radar data including interference; performing temporal signal reconstruction on the radar data to generate first filtered data prior to performing a fast Fourier transform (FFT) on the radar data, wherein the FFT generates ranging data using the first filtered data; performing spectral signal reconstruction on the ranging data to generate second filtered data after performing the FFT on the ranging data; and detecting an object in the environment based at least in part on the second filtered data.

2. The computer-implemented method of claim 1, wherein the temporal signal reconstruction includes performing a detection phase and a reconstruction phase to detect interference values within the radar data and interpolate replacement values to replace the interference values.

3. The computer-implemented method of claim 2, wherein the detection phase includes determining a median absolute value of time samples for each chirp of a plurality of chirps across the radar data, determining a third quartile of medians, determining an interquartile range (IQR) using a subtraction of the third quartile and a first quartile, and identifying outliers based on a first threshold.

4. The computer-implemented method of claim 2, wherein the detection phase includes a first detection phase, and wherein the temporal signal reconstruction further includes a second detection phase, wherein the second detection phase includes determining a third quartile of absolute sample values across chirps of the plurality of chirps for each time index, determining an interquartile range (IQR) using a subtraction of the third quartile of absolute sample values and a first quartile of the absolute sample values, and identifying outliers based on a second threshold.

5. The computer-implemented method of claim 3, wherein the reconstruction phase includes detecting which points in the radar data are greater than the first threshold and interpolating the replacement values based on neighboring points to replace the points greater than the first threshold.

6. The computer-implemented method of claim 1, wherein the temporal signal reconstruction includes performing a first detection phase, a first recovery phase, a second detection phase, and a second reconstruction phase to detect interference values within the radar data and interpolate values to replace the interference values.

7. The computer-implemented method of claim 1, wherein the spectral signal reconstruction includes performing a detection phase and a reconstruction phase to detect interference values within the ranging data and interpolate values to replace the interference values, wherein the detection phase includes determining a median absolute value of distance samples for each of a plurality of chirps of the ranging data, determining a third quartile of the medians, determining an interquartile range (IQR) using a subtraction of the third quartile and a first quartile, and identifying outliers based on a first threshold.

8. The computer-implemented method of claim 7, wherein the detection phase comprises a first detection phase, and wherein the time signal reconstruction further comprises a second detection phase, wherein the second detection phase comprises determining a third quartile of absolute sample values across chirps of the plurality of chirps for each range index, determining the IQR using a subtraction of the third quartile of absolute sample values and a first quartile of absolute sample values, and identifying outliers based on a second threshold.

9. The computer-implemented method of claim 7, wherein the reconstruction phase comprises detecting which points within the ranging data are greater than a first threshold, and interpolating out replacement values based on neighboring points to replace the points greater than the first threshold.

10. The computer-implemented method of claim 1, wherein the spectral signal reconstruction comprises performing a first detection phase, a first recovery phase, a second detection phase, and a second reconstruction phase to detect interfering values within the ranging data, and interpolating out values to replace the interfering values.

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