Subarray angle of arrival processing for near field effect reduction

Abstract

Methods, sensor systems, and non-transitory computer readable media are provided. Embodiments include receiving, at a plurality of receiver antennas, a plurality of incident signals reflected from a target. A processor identifies a subset of receiver antennas from the plurality of receiver antennas and performs angle of arrival (AOA) processing on respective incident signals of the subset of receiver antennas. The processor determines an angle of arrival of the target based on the AOA processing.

Description

Technical Field

[0001] The field relates to radar devices, for example angle-of-arrival processing in the near field. Background Art

[0002] Autonomous vehicles, vehicles including advanced driver assistance systems (ADAS), and robotic devices rely on data from sensors, cameras, radars, and lidars to perceive the real-world environment during operation. The data is processed to detect one or more objects in the real-world environment.

[0003] Typically, a radar's transmitting antenna emits a radio frequency (RF) signal that propagates toward an object in the radar's field of view. The signal reflected by the object depends on the object's backscattering properties (i.e., radar cross section). The signal reflected by the object is received by the radar's receiving antenna. Typically, the receiving antenna is connected to a processing device. The processing device processes the signal reflected by the object to determine the object's position (e.g., elevation angle). In some cases (e.g., within a very close range of an object), processing may present some challenges, such as inaccuracies. In addition, advanced processing methods for such cases have the problem of high computational complexity.

[0004] There is a need for improved methods for processing radar data. Summary of the invention

[0005] According to an embodiment, a method for determining an angle of arrival of a target is provided. In the method, a plurality of incident signals reflected from a target are received at a plurality of receiver antennas. A processor identifies a subset of receiver antennas from the plurality of receiver antennas and performs angle of arrival (AOA) processing on the corresponding incident signals of the subset of receiver antennas. The processor determines the angle of arrival based on the AOA processing.

[0006] According to an embodiment, a sensor system includes a plurality of receiver antennas and a processor coupled to the plurality of receiver antennas. The processor is configured to identify a subset of receiver antennas from the plurality of receiver antennas, and to perform AOA processing on corresponding incident signals of the subset of receiver antennas. The processor is further configured to determine an angle of arrival based on the AOA processing.

[0007] System, apparatus, and computer program product aspects are also disclosed.

[0008] Further features and advantages and the structure and operation of various aspects are described in detail below with reference to the accompanying drawings. It should be noted that the specific aspects described herein are not intended to be limiting. These aspects proposed herein are for illustrative purposes only. Based on the teachings contained herein, additional aspects will be apparent to those skilled in the relevant art. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The features and advantages of the example embodiments described herein will become apparent to those skilled in the art to which the present disclosure pertains when reading the following description with reference to the accompanying drawings.

[0010] Figure 1 A block diagram of a system including a radar is shown in accordance with some embodiments.

[0011] Figure 2A Shown are reflected waves from a target located in the far field of a radar, in accordance with some embodiments.

[0012] Figure 2B Shown is a reflected wave from a target located in the far field of a radar, incident at an angle relative to the radar's receive array, in accordance with some embodiments.

[0013] Figure 3 Shown are reflected waves from a target located in the near field of a radar, according to some embodiments.

[0014] Figure 4 Reflected waves from a target located in the near field of a radar are shown received at a subarray of antennas in accordance with some embodiments.

[0015] Figure 5A A transmitter array and a receiver array of a multiple-input multiple-output (MIMO) antenna array are shown in accordance with some embodiments.

[0016] Figure 5B A uniform linear array of a MIMO antenna array is shown in accordance with some embodiments.

[0017] Figure 6 Angle-of-arrival spectra generated using different processing techniques in accordance with some embodiments are shown.

[0018] Figure 7 is a method for determining an angle of arrival of a target according to some embodiments.

[0019] Figure 8 A computer system according to some embodiments is shown.

[0020] In the drawings, like reference numbers generally refer to the same or similar elements. Additionally, generally, the leftmost digit(s) of a reference number identifies the drawing in which the reference number first appears. DETAILED DESCRIPTION

[0021] Radar is a sensor that identifies objects in four-dimensional (4D) space. Radar can identify the range (distance), azimuth (AZ) (direction), relative velocity (Doppler), and elevation (EL) of objects in the environment. Radar can radiate a beam of electromagnetic energy from the radar's transmitter antenna. When an object (e.g., a target, road worker, pedestrian, sidewalk, pole, vehicle, cyclist) is illuminated by the beam, the object reflects a portion of the radiated energy back to the radar's receiver antenna. By processing the reflected energy received at the receiver antenna, the radar can compare the transmitted signal and the received signal to determine the object's 4D spatial information (e.g., 3D position and radial velocity information).

[0022] The azimuth and elevation are determined based on the received signal using an angle of arrival (AOA) algorithm. In particular, the radar system may include multiple transmitters and multiple receivers. Multiple incident signals reflected from the target and received at multiple receivers can be used to determine the location information of the target. Radar reflections behave like and are modeled as point sources. The incident radar wave induces a current in a conductive material. The current behaves like a radiating antenna. The point source radiates with a spherical wavefront (or a portion of a spherical wavefront). The radius of the sphere is the distance between the reflecting object and the radar receiver antenna. Therefore, when the object is far away (i.e., in the far field region), the error of simplifying the physical model to a plane wavefront is small and can be ignored. However, for close objects (i.e., in the near field region), the error generated by this simplification is considerable and should be considered. For targets located in the far field of the sensor system, the AOA algorithm can use a plane wave AOA algorithm (e.g., fast Fourier transform (FFT) processing) to determine the spatial frequencies of multiple incident signals. However, for targets located in the near field of the sensor system, multiple incident signals cannot be simplified to plane waves. Therefore, for near-field signals, AOA processing usually uses matched filtering techniques. However, the matched filtering technique has a high computational cost.

[0023] Aspects of the present invention use data from a subset of multiple receivers in AOA processing for targets located in the near field of a sensor system. When only a subset of receivers is used, the return signal (which may appear spherical when all receivers are used) instead appears plane. Because the multiple incident signals can be considered plane waves, a plane wave AOA algorithm (e.g., FFT processing) can be used. In this way, near-field effects can be reduced.

[0024] Additionally, the spectra from multiple subsets of receiver antennas can be coherently or incoherently combined to provide enhanced target tracking, e.g., a high signal-to-noise ratio (SNR). In some embodiments, the sensor system includes a multiple-input multiple-output (MIMO) radar, and the subsets of the multiple receivers correspond to subarrays of a virtual array of the MIMO radar.

[0025] Figure 1 A block diagram of a system 100 including a radar 104 is shown in accordance with some embodiments. A vehicle 102 may be configured to support the system 100 (e.g., installed or implemented in the vehicle 102). The vehicle 102 includes a car, a truck, a motorcycle, a bus, a motorbike, a boat, or any other vehicle. The system 100 may include an autonomous vehicle system, an automatic driving system, a driver assistance system, an advanced driver assistance system, and the like.

[0026] ADAS or Advanced Driver Assistance Systems are technologies that enhance the safety and convenience of drivers and passengers by providing assistance, warnings or interventions in various driving scenarios. ADAS can involve parking sensors, blind spot monitors, adaptive cruise control and lane keeping assist, or can involve fully autonomous systems such as automatic parking and autonomous driving. ADAS helps reduce human errors, improve traffic flow, reduce fuel consumption and prevent collisions and injuries.

[0027] Autonomous vehicles, also known as self-driving cars, are vehicles that can operate without human intervention or supervision, using sensors, cameras, software and artificial intelligence to perceive and navigate their environment. Autonomous vehicles have the potential to improve road safety, mobility, efficiency and environmental sustainability by reducing human error, traffic congestion, fuel consumption and greenhouse gas emissions.

[0028] The system 100 may receive input from a plurality of sensors. Based on the input, the system 100 may detect and determine one or more characteristics (e.g., size, speed, location, category) of an object 108 in the environment of the vehicle 102. Using the one or more characteristics, the system 100 may control the behavior of the vehicle 102 (e.g., path planning, steering, braking, etc.). The plurality of sensors may include light detection and ranging sensors (lidar) sensors, camera sensors, radars, etc.

[0029] The vehicle 102 may include a radar 104. The radar 104 may include one or more radars of the same type or different radar types. The radar 104 may be installed in the vehicle 102 (e.g., installed on the surface of the vehicle 102 or inside the vehicle 102) for detecting one or more objects (targets).

[0030] The radar 104 may include a transmitter antenna (Tx) 110 and a receiver antenna (Rx) 112. The transmitter antenna (Tx) 110 may include multiple antenna elements and the receiver antenna (Rx) may include multiple antenna elements 112. In some embodiments, the radar 104 may include multiple antenna elements arranged in both the vertical direction and the horizontal direction to provide elevation information. In some embodiments, the radar 104 may include a MIMO radar.

[0031] MIMO radars can include multiple transmit (Tx) and receive (Rx) elements with separability features between Tx elements. The Tx side transmits orthogonal waveforms, while the Rx side uses this orthogonality and information about the Tx antenna positions to build a virtual array. The virtual array has a larger aperture than the original Rx array and therefore improves the performance of AOA processing. For example, on the receiver side, the signal processing method can work on the Tx-Rx pair with minimal self-interference.

[0032] MIMO radar systems transmit different signals from multiple transmit antennas to extend resolution. Multiple different signals from different transmit antennas are extracted from each of the receive antennas. In this way, by changing the signal, the physical array can be virtually extended. For example, if a MIMO radar system has 3 transmit antennas and 4 receive antennas, 12 signals can be extracted from the receiver due to the orthogonality of the transmitted signals. That is, only 7 antennas are used to create a 12-element virtual antenna array, thereby obtaining finer spatial resolution than its phased array counterpart.

[0033] As discussed above, the radar 104 can radiate electromagnetic energy beams via a transmitter antenna (Tx). For example, multiple antenna elements can transmit waveforms having frequencies in a radio frequency (RF) band. The RF band can have a starting frequency above 10 gigahertz (GHz), for example, a frequency band with a starting frequency between 10 GHz and 120 GHz, between 30 GHz and 100 GHz, or between 100 GHz and 300 GHz. In some embodiments, the RF band can correspond to an automotive radar band (i.e., a frequency band between 76 GHz and 81 GHz).

[0034] The waveform radiated by the transmitter antenna (Tx) propagates through the environment and encounters the object 108. A portion of the waveform may be reflected by the object 108 and received by the receiver antenna (Rx).

[0035] After receiving the reflected waveform, the system 100 may process the reflected waveform. The radar 104 may be coupled to a processor 106. The processor 106 may be configured to generate radar information based on the radar signal transmitted by the radar 104. The radar information may include range information, Doppler information, and / or angle of arrival information. In some aspects, the radar information may be used to generate four-dimensional (4D) image information corresponding to the object 108. The 4D image information may include a range value based on the range information, a velocity value based on the Doppler information, an azimuth value based on the azimuth AOA information, and an elevation value based on the elevation AoA information.

[0036] In order to generate 4D image information, the processor 106 can process the reflected waveform. The processor 106 can include a baseband processing unit (BPU). The BPU can determine the range of the object 108 based on the power of the reflected waveform. In addition, the BPU can determine the speed of the object 108 based on the Doppler effect. AZ and EL estimation is performed using an angle of arrival (AOA) algorithm. The input of the AOA algorithm is the spatial channel (array signal) of each antenna element of the receiver antenna. The output of the AOA algorithm is a spatial spectrum indicating the AZ and EL of the object 108. For example, the processor 106 can identify peaks in the spatial spectrum. The azimuth of the object 108 can correspond to the position of the peak (ie, the x-coordinate). As further described below, the AOA algorithm can implement a fast Fourier transform (FFT) process or other AOA algorithms (e.g., super-resolution such as multiple signal classification (MUSIC), compressed sensing) to obtain the spatial spectrum of objects located in the far field of the radar. For objects located in the near field, the AOA algorithm can implement the FFT process using a sub-array of the receiving antenna (Rx). About Figure 7 The AOA process is further described.In some aspects, a joint process (eg, joint estimation) can be applied to determine two or more dimensions (eg, azimuth and Doppler) of the 4D spatial information of the object.

[0037] After estimating the azimuth and elevation of object 108 , processor 106 may generate radar point cloud data and track one or more objects in the environment of vehicle 102 .

[0038] Using one or more sub-arrays of antennas (eg, sub-arrays of a virtual MIMO array) during AOA processing provides a technical advantage of reducing the computational complexity of radar data used to determine objects located in the near field.

[0039] In some embodiments, system 100 may be implemented in a robotic device or a drone.

[0040] Figure 2A A reflected wave 200 from a target 202 located in the far field of a radar (e.g., the radar 104 of the vehicle 102) is shown according to some embodiments. The reflected wave 200 can be emitted spherically from the target 202 to the receiving array 204 of the radar. While the reflected waves are due to the distance of the far field target 200, when the reflected waves 200 reach the receiving array 204, they appear as plane waves 206. The reflected waves 200 are received by the receiving array 204. By evaluating the relative arrival times of the plane waves, the system can determine the AOA. As described below, FFT can be used to evaluate the arrival times and determine the AOA.

[0041] Figure 2B1 shows reflected waves 200 from a target 202 located in the far field of a radar (e.g., radar 104 of vehicle 102) incident at an angle θ relative to a receive array 204 of the radar, according to some embodiments. As described above, reflected waves 200 may be emitted spherically from target 202 toward the receive array 204 of the radar. Although reflected waves 200 are emitted spherically, due to the distance of far field target 200, when reflected waves 200 reach receive array 204, they appear as plane waves 206. The received signal at each element of receive array 204 is related to exp(-j2πd n / λsin(θ)), where d n represents the distance between the reference point and the elements of the receiving array, and λ is the wavelength of the reflected wave. For a uniform array (i.e., equal spacing (d1) between each element of the array), the phase difference between the two signals received at the two elements is 2πd 1 / λ The linear phase results in a single spatial frequency (the spatial frequency can be obtained by taking the derivative of the phase, for a linear phase ax+b, the spatial frequency will be a).

[0042] Due to the single spatial frequency of the reflected wave 200, the AOA processing can use an FFT process. The FFT process can be used to obtain a spatial spectrum in order to obtain the angle of arrival. One of the advantages of FFT is that the computational complexity is low. Therefore, the azimuth and elevation information of an object located in the far field of the radar can be accurately estimated at a low computational cost.

[0043] Figure 3 Shown is a reflected wave 300 from a target 302 located in the near field of a radar, in accordance with some embodiments. In the near field, reflected wave 300 is a spherical wave 306 (as opposed to plane wave 206 of reflected wave 200).

[0044] Because we cannot assume that the waves in the near field are planar, the assumptions required to use FFT do not hold. In order to perform AOA estimation for spherical waves, matched filtering implemented by matrix multiplication can be used instead of FFT. Using the matched filtering technique, the reflected wave is compared with the intensity of different azimuths (e.g., 0 degrees, 30 degrees) measured previously. Based on the comparison, the best match is determined. The azimuth of target 202 can correspond to the best match. Matching is performed for each hypothesis, which complicates the AOA processing calculations for targets located in the near field. Although matched filtering can determine AOA in the near field, it has a higher computational complexity than the FFT process.

[0045] As discussed above, 4D image information may depend on the lateral range of the radar. The lateral resolution of the radar depends on both the range and the angular resolution of the system 100. Assuming fixed lateral system requirements in meters for short and long ranges, the angular resolution requirements of the system 100 may be relaxed for close ranges (e.g., near field). This may be true in the context of autonomous vehicles and advanced driver assistance, as the vehicle may need to move away from objects when they are close enough to appear in the near field. If the angular near field resolution requirements are relaxed, a subarray of the receiver antenna (Rx) of the radar 104 of the system 100 may be used for AOA processing. A subarray of the receiver antenna (Rx) is an array that includes a portion of the antenna elements of the receiver antenna (Rx). For example, if the receiver antenna (Rx) includes 10 elements, the subarray may use 5 elements. Using only a portion of the array may have the effect of reducing resolution. However, when only a portion of the array of receivers positioned close to each other is used, spherical waves may otherwise appear as planes. This is in Figure 4 Shown in.

[0046] The subarray is chosen to obtain a reduced aperture size. For smaller apertures, the spherical waves can be Figure 4 The shown approximation is a plane wave. Therefore, the processor 106 can use FFT-based processing or other plane wave AOA processing techniques to determine radar information. Using low-complexity FFT-based processing provides the advantages of lower computational complexity and smaller chips. In addition, power consumption is reduced.

[0047] Figure 4 Reflected waves 400 from a target 402 located in the near field of a radar are shown in accordance with some embodiments. Reflected waves 400 are received by a subarray 404 of an array of receiver antennas (Rx) of system 100 (as shown, subarray 404 includes a portion of the elements of array 304). Although reflected waves 400 are spherical waves, they can be considered as plane waves 406 relative to a subset of antenna elements (a subarray of the array of receiver antennas (Rx)) (i.e., relative to the far field of the subarray because the subarray has smaller dimensions than the entire array). Reflected waves can be considered as Figure 4 A plane wave of subarray 404 is shown.

[0048] As discussed above, the radar 104 can be configured to utilize, for example, MIMO technology to support a reduced physical array aperture (e.g., array size) and / or utilize a reduced number of antenna elements. In some embodiments, the radar 104 can be a MIMO antenna array. The MIMO radar may include multiple Tx antennas (e.g., N elements of a Tx array) and multiple Rx antennas (e.g., M elements of an Rx array). Multiple Tx antennas are configured to transmit multiple Tx signals, and multiple Rx antennas are configured to receive multiple Rx signals. For example, the radar 104 can be configured to transmit orthogonal signals via the Tx antennas and process signals received via the Rx antennas.

[0049] As described above, utilizing MIMO technology that transmits orthogonal signals from a Tx array having N elements and processes received signals in an Rx array having M elements may be equivalent to (e.g., in the far field approximation) utilizing a radar that transmits from one antenna and receives with an N×M antenna. For example, a MIMO radar may be configured to utilize a MIMO antenna array as a virtual array having an equivalent array size of N×M. The virtual array may define the position of a virtual element as a convolution of the position of a physical element. For example, a virtual channel may be formed as a Kronecker product between a transmit antenna element and a receiver antenna element.

[0050] Figure 5A 5 shows a transmitter array 502 and a receiver array 504 of a MIMO antenna array according to some embodiments. The transmitter array 502 may include four antenna elements (e.g., Figure 5A The antenna elements of the transmitter array 502 may be positioned along one direction (eg, horizontal direction). The receiver array 504 may include 16 antenna elements ( Figure 5A 1 to 16 in FIG. 5 ). The antenna elements of the receiver array 504 may be positioned along one direction. For example, the antenna elements of the receiver array 504 may be positioned along the same direction as the elements of the transmitter array 502. In this example, the number or size of elements of the virtual array is 16×4=64 elements.

[0051] Figure 5B A uniform linear array (ULA) 500 for a MIMO antenna array is shown, which includes a transmitter array 502 and a receiver array 504. When the transmitter array 502 and the receiver array are one-dimensional and in the same direction (e.g., the transmitter array 502 and the receiver array 504), the virtual array is a ULA. The ULA includes 64 elements. For each transmitter in the transmitter array, use Figure 5BIn some embodiments, when the elements of the transmitter antenna and the elements of the receiver antenna are positioned in opposite directions (e.g., Tx in the vertical direction and Rx in the horizontal direction), the virtual array can be a two-dimensional array. In order to increase the resolution of the MIMO antenna, the Tx antenna and the Rx antenna can each include a 2D array of antenna elements (e.g., at least two elements in the horizontal direction and two elements in the vertical direction). The corresponding virtual array can be a 2D array in which each virtual element is positioned at a spacing different from the corresponding spacing in the physical array.

[0052] AOA processing can be performed on the ULA using an FFT process to obtain a spatial spectrum. For a virtual two-dimensional array, the spatial spectrum can be obtained by applying a 2D FFT. In some aspects, the antenna may include a non-uniform array, a scanning radar, or a switching antenna system. For example, in a switching antenna system or a switching antenna array, the number of antenna elements may not correspond to the number of RF channels. The desired Tx element and the desired Rx element can be activated, while other elements are deactivated. Based on the desired range, the antenna element is identified and activated.

[0053] The subarrays are selected to provide the best signal quality among the available subarrays. The receiver antenna subsets for near-field processing may be identified by selecting elements from a virtual array of the same Tx element (e.g., elements associated with Tx 502a, Tx 502b, Tx 502c, or Tx 502d). For example, the subarrays may be used in conjunction with Figure 5B 1 to 16 associated with the first transmitter Tx 502a in the array. The set of elements (i.e., elements associated with Tx 502a, Tx 502b, Tx 502c, or Tx 502d) may be selected based on a number of factors. The multiple factors may include transmitter-to-receiver leakage and calibration quality for each subarray. Leakage may be based on the distance between the Rx element and the Tx element. For example, the Rx element farthest from the selected Tx element may be used to reduce leakage between the two elements. As further described below, spectra from multiple subarrays may be combined to improve SNR. The spectra may be combined incoherently with low complexity and some loss to SNR, or coherently using a time-realistic propagation model from the Tx to the target.

[0054] The receiver antenna subset for near field processing can be identified by testing the separation capability of the radar 104. For example, by testing the separation capability of the radar 104, the size of the subarray is determined. To test the separation capability, the reception of one or more antenna elements can be blocked or attenuated. For example, radiation absorbing material can be positioned in front of one or more antenna elements. The performance of the radar is monitored. If the performance of the radar does not change (or decreases slightly, but the performance is still within the system requirements) (i.e., after blocking one or more antenna elements), then the one or more antenna elements are not included in the subarray.

[0055] For MIMO radar, the receiver antenna subset can be identified by testing the separation capability of the physical receive array. For example, if the receive array includes 16 antenna elements, the first 8 elements can be blocked. The virtual array formed will be a subset of the virtual array. The virtual array formed has a size of 8×4=24 elements (assuming the transmitter antenna has 4 antenna elements).

[0056] As previously described herein, processor 106 may generate 4D radar information based on radar signals received via the Rx antenna. To generate 4D radar information including azimuth and elevation, at least some of the antenna elements of the RX antenna are positioned vertically and horizontally (eg, along a rectangle).

[0057] Figure 6 An AOA spectrum using different AoA processing techniques according to some embodiments is shown, the AoA processing technique using ULA 500. In a non-limiting illustrative example, a single object is within a range of 1 meter. The AOA spectrum is determined using an AoA algorithm.

[0058] The first spectrum 602 can be obtained by performing FFT-based AOA beamforming on a full virtual array. The FFT process can use a Chebyshev window (e.g., a 30-point Chebyshev window) in the processing. As discussed above, the AOA algorithm using the FFT process is designed for targets located in the far field, where a single peak with side lobes indicated by the window function is observed. However, for near-field targets, the FFT process (which is based on plane waves) fails and thus produces a distorted spectrum as shown in the first spectrum 602. The first spectrum 602 shows a peak 612 and two side lobes 608, 610. However, the two side lobes 608, 610 have high amplitudes. The side lobes may cause false alarms (i.e., incorrectly identifying objects located at approximately 7.5 degrees and approximately 12.5 degrees). As described above, there is a nonlinear phase between the elements of the array, because the target is in the near field, which results in a distorted spectrum with high amplitude side lobes.

[0059] The second spectrum 604 is obtained by processing the radar data using near-field processing based on propagation time modeling from each TX to each RX. Figure 1 As described, AOA beamforming with near-field processing uses matrix multiplication of the received signal with each AOA hypothesis vector. The second spectrum 604 shows a peak 612 and low sidelobes. AOA beamforming with near-field processing has good performance in terms of resolution and sidelobes. However, the complexity of near-field processing is higher than that of FFT, i.e., for matrix multiplication O(N 2 ), rather than O(N log N) for FFT. Therefore, near-field processing suffers in terms of chip size and power consumption.

[0060] The third spectrum 606 may be generated using AOA beamforming, which uses FFT processing on a sub-array of the array (e.g., a sub-array of a virtual MIMO). As discussed above, for targets located within the close range of the radar, a smaller array is used in the AOA processing. For the above example, the sub-array may contain 16 elements. Due to the smaller size of the array used in the AOA processing, the near-field effect (i.e., the spherical wave propagation model becomes more linear, such as Figure 4 shown).

[0061] The third spectrum 606 shows a peak 614. The third spectrum 606 provides low amplitude sidelobes, but reduces resolution compared to the full array processing (i.e., the second spectrum 604 and the first spectrum 602). That is, the peak 614 is wider than the peak 612. However, in many practical scenarios, the reduction in AOA resolution is acceptable for objects located at close range. As described above, for close range, the lateral resolution in meters can be maintained. This is because the lateral resolution is proportional to the range and the AOA resolution. While for close range, the range factor is reduced, the AOA beamwidth is increased, and thus the fixed lateral resolution is maintained.

[0062] In addition to performing AOA processing on a subarray, the processor 106 can also perform AOA processing on multiple subarrays of the radar (e.g., a virtual MIMO radar). A corresponding angular spectrum is generated from each of the multiple subarrays. The angular spectra can then be combined to improve the signal-to-noise ratio (SNR) of the radar 104. The angular spectra can be combined incoherently. Incoherently integrating the angular spectra provides the advantage of low computational complexity, but with some loss in SNR. For close range targets, some reduction in SNR is acceptable because even targets with a small radar cross section (RCS) are typically received at a higher SNR due to the close range.

[0063] Figure 7700 is a method for determining a characteristic of a target according to some embodiments. In embodiments, the method 700 may be implemented in any combination of hardware, software, or firmware. In an example, the method 700 may be implemented by a computing system of a motor vehicle. It should be understood that not all steps are required to perform the disclosure provided herein. Furthermore, as will be appreciated by one of ordinary skill in the art, some steps may be performed simultaneously or in combination. Figure 7 The different orders are shown.

[0064] Will refer to Figure 1 700 is described below. However, the method 700 is not limited to this example embodiment.

[0065] At 702, a plurality of receiver antennas receive a plurality of incident signals reflected from a target. For example, the plurality of receiver antennas may correspond to receiver antennas (Rx) of the MIMO antenna previously described herein.

[0066] At 704, the processor 106 may analyze the multiple incident signals (reflected waves) to determine the range of the target. Based on the range, the processor 106 may determine whether the target is located in the near field or the far field of the radar. The threshold of the far field is determined based on the dimensions of the antenna. The processor 106 may compare the threshold of the far field with the determined range to determine whether the target is in the far field or in the near field.

[0067] At 706, when the target is in the near field of the radar, the processor 106 may use an AOA algorithm that utilizes a subset of receiver antennas. A subset of receiver antennas is identified from a plurality of receiver antennas. For example, a subarray of receiver antennas is identified. When the target is in the far field of the radar, the processor 106 may use the AOA algorithm for the entire receiver antenna array. In some aspects, the processor 106 may determine the size of the subset of receiver antennas based on the range. For example, for a target located in the near field, the size of the subarray may be proportional to the range of the target. The farther the target is from the radar system, the larger the size of the subarray that can be used.

[0068] In various embodiments, the radar system may need to switch between far-field processing using the entire array and near-field processing using a portion of the array.

[0069] In some embodiments, if the desired target is in the near field, one or more Tx-Rx channels may be deactivated. For example, when the maximum expected range of the radar system is in the near field (e.g., when the vehicle is in a parking lot), one or more channels or one or more antenna elements may be deactivated. AOA processing may determine azimuth and elevation based on radar signals from active channels or active antenna elements.

[0070] At 708, the processor 106 may perform AOA processing on the corresponding incident signals of the receiver antenna subset. As described above, the AOA processing includes performing a fast Fourier transform (FFT) on the radar signals from the receiver antenna subset. The processor 106 may determine the azimuth and elevation based on the AOA processing.

[0071] As mentioned above, Figure 7 The method 700 in can be implemented on a computing system. Figure 7 An example computing system is shown in FIG.

[0072] Figure 8 800 according to some embodiments. For example, the various embodiments and components thereof may be implemented using the computer system 800 or any other well-known computer system. Figure 7 The method steps may be implemented via the computer system 800 .

[0073] In some embodiments, computer system 800 may include one or more processors (also referred to as central processing units or CPUs), such as processor 804. Processor 804 may be connected to a communications infrastructure or bus 806.

[0074] In some embodiments, one or more processors 804 may each be a graphics processing unit (GPU). In an embodiment, a GPU is a processor that is a dedicated electronic circuit designed to process mathematically intensive applications. A GPU may have a parallel structure that is efficient for parallel processing of large blocks of data, such as mathematically intensive data commonly found in computer graphics applications, images, videos, etc.

[0075] In some embodiments, the computer system 800 may also include a user input / output device 803, such as a monitor, a keyboard, a pointing device, etc., which can communicate with the communication infrastructure 806 through the user input / output interface 802. The computer system 800 may also include a main memory 808, such as a random access memory (RAM). The main memory 808 may include one or more levels of cache. The main memory 808 stores control logic (e.g., computer software) and / or data therein.

[0076] In some embodiments, the computer system 800 may also include one or more auxiliary storage devices or memories 810. The auxiliary memory 810 may include, for example, a hard disk drive 812 and / or a removable storage device or drive 814. The removable storage drive 814 may be a floppy disk drive, a tape drive, an optical disk drive, an optical storage device, a tape backup device, and / or any other storage device / drive. The removable storage drive 814 may interact with a removable storage unit 818. The removable storage unit 818 may include a computer-usable or readable storage device having computer software (control logic) and / or data stored thereon. The removable storage unit 818 may be a floppy disk, a tape, an optical disk, a DVD, an optical storage disk, and / or any other computer data storage device. The removable storage drive 814 reads and / or writes to the removable storage unit 818 in a well-known manner.

[0077] In some embodiments, secondary memory 810 may include other devices, tools, or other methods for allowing computer programs and / or other instructions and / or data to be accessed by computer system 800. Such devices, tools, or other methods may include, for example, a removable storage unit 822 and an interface 820. Examples of removable storage unit 822 and interface 820 may include a program cartridge and cartridge interface (such as found in video game devices), a removable storage chip (such as an EPROM or PROM) and an associated slot, a memory stick and USB port, a memory card and an associated memory card slot, and / or any other removable storage unit and associated interface.

[0078] In some embodiments, the computer system 800 may also include a communication or network interface 824. The communication interface 824 enables the computer system 800 to communicate and interact with any combination of remote devices, remote networks, remote entities, etc. (individually and collectively referenced by reference numeral 828). For example, the communication interface 824 may allow the computer system 800 to communicate with a remote device 828 via a communication path 826, which may be wired and / or wireless and may include any combination of a LAN, a WAN, the Internet, etc. Control logic and / or data may be sent to and from the computer system 800 via the communication path 826.

[0079] In some embodiments, a non-transitory tangible device or article of manufacture including a non-transitory tangible computer usable or readable medium having control logic (software) stored thereon is also referred to herein as a computer program product or program storage device. This includes, but is not limited to, computer system 800, main memory 808, auxiliary memory 810, and removable storage units 818 and 822, as well as tangible articles of manufacture embodying any combination of the foregoing. When executed by one or more data processing devices (e.g., computer system 800), such control logic causes such data processing devices to operate as described herein.

[0080] Based on the teachings included in this disclosure, it will be clear to those skilled in the relevant art how to use the Figure 8 The embodiments of the present disclosure may be made and used with data processing devices, computer systems, and / or computer architectures other than those shown in the drawings. Specifically, the embodiments may operate with software, hardware, and / or operating system implementations other than those described herein.

[0081] Although several embodiments have been described, it will be appreciated by those skilled in the art that various modifications and changes may be made without departing from the scope of the embodiments described in detail herein. Therefore, the description and drawings should be regarded as illustrative rather than restrictive, and all such modifications are intended to be included within the scope of the present teachings. Benefits, advantages, solutions to problems, and any elements that may cause any benefit, advantage, or solution to appear or become more apparent should not be construed as key, essential, or necessary features or elements of any or all claims. The present invention is limited solely by the appended claims, including any amendments made during the pendency of this application and all equivalents of those claims issued.

[0082] Identifiers such as "(a)", "(b)", "(i)", "(ii)" etc. are sometimes used for different elements or steps. These identifiers are used for clarity and do not necessarily specify the order of elements or steps.

[0083] In addition, in this document, relational terms such as first and second can only be used to distinguish one entity or action from another entity or action, without necessarily requiring or implying any actual such relationship or order between such entities or actions. As used herein, the terms "comprises", "comprising", "has", "having", "includes", "including", "contains", "containing" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment including, having, containing or containing a series of elements not only includes those elements, but also includes other elements that are not explicitly listed or inherent to such processes, methods, articles or equipment. The elements preceded by "including...", "having...", "including...", "containing..." do not exclude the presence of additional identical elements in the process, method, article and / or equipment including, having, containing and / or containing the element without additional restrictions. Unless otherwise expressly stated herein, the terms "one" and "an" are defined as one or more. The terms "approximately", "about" or any other version thereof are defined as close to what is understood by those of ordinary skill in the art. A device or structure that is "configured" in a certain way is configured in at least that way, but may also be configured in unlisted ways. For reference to an element, either the singular or plural form may be used, but this does not limit the scope of the present disclosure, and the same teachings may apply to multiple objects even if the object is referred to in the singular form in this application.

[0084] The embodiments detailed herein are provided to allow the reader to quickly determine the nature of the technical disclosure. It should be understood that they will not be used to interpret or limit the scope or meaning of the claims when submitted. In addition, in the foregoing detailed description, for the purpose of simplifying the present disclosure, it is demonstrated that multiple features are grouped together in various embodiments. The method of the present disclosure should not be interpreted as reflecting the intention that the claimed embodiments require more features than the features explicitly listed in each claim. On the contrary, as reflected in the following claims, in at least some cases, the subject matter of the invention lies in less than all the features of a single disclosed embodiment. Therefore, the following claims are hereby incorporated into the detailed description, with each claim independently serving as a separately claimed subject matter.

Claims

1. A method for determining an angle of arrival of a target, comprising: receiving, at a plurality of receiver antennas, a plurality of incident signals reflected from the target; identifying, by a processor, a subset of receiver antennas from the plurality of receiver antennas when the target is in a near field of the plurality of receiver antennas; as well as Angle of arrival (AOA) processing is performed by the processor on respective incident signals for the subset of receiver antennas to determine the angle of arrival.

2. The method according to claim 1, further comprising: An elevation angle and an azimuth angle to the target are determined based on the angle of arrival.

3. The method according to claim 1, wherein: Performing the AOA processing includes determining an azimuth or elevation spectrum describing the power of the corresponding incident signal with respect to the angle of arrival.

4. The method according to claim 3, further comprising: The corresponding azimuth or elevation spectra from multiple subsets of receiver antennas are integrated.

5. The method according to claim 1, wherein: The plurality of receiver antennas are part of a switched antenna array; And the method also includes: The subset of receiver antennas is activated.

6. The method according to claim 4, wherein: The corresponding azimuth or elevation spectra are incoherently integrated.

7. The method according to claim 1, further comprising: providing a first receiver antenna array in a first dimension; providing a second receiver antenna array in a second dimension different from the first dimension; as well as A first subset of receiver antennas is identified from the first array and the second array.

8. The method according to claim 1, wherein: The plurality of receiver antennas are part of a multiple-input multiple-output (MIMO) radar, and the subset corresponds to a portion of a virtual array formed by the MIMO radar.

9. The method according to claim 8, wherein: The virtual array is a two-dimensional (2D) array; and wherein the AOA processing includes performing a 2D FFT.

10. The method according to claim 1, further comprising: Electromagnetic energy beams are transmitted via a plurality of transmitter antennas, wherein the plurality of transmitter antennas and the plurality of receiver antennas are part of a radar.

11. The method according to claim 10, further comprising: determining a range to the target based on a received incident signal from among a plurality of received incident signals; as well as Based on the range, it is determined whether the target is in the near field or the far field of the radar.

12. The method according to claim 11, further comprising: The angle of arrival is determined using the plurality of incident signals when the target is in the far field of the radar.

13. The method according to claim 1, wherein: The plurality of receiver antennas are included in a vehicle, and the method further comprises: A behavior of the vehicle is controlled based on the angle of arrival.

14. The method according to claim 1, wherein: Identify receiver antenna subsets including: The size of the aperture of the receiver antenna is determined by testing the separation capability of the receiver antenna.

15. A sensor system comprising: a plurality of receiver antennas configured to receive a plurality of incident signals reflected from a target; as well as a processor coupled to the plurality of receiver antennas, wherein the processor is configured to: identifying a subset of receiver antennas from the plurality of receiver antennas when the target is in a near field of the plurality of receiver antennas; and Angle of arrival (AOA) processing is performed on respective incident signals of the subset of receiver antennas, wherein the AOA processing includes determining a characteristic of the target based on the AOA processing.

16. The sensor system of claim 15, wherein: The processor is further configured to: An elevation angle and an azimuth angle to the target are determined based on the angle of arrival.

17. The sensor system of claim 15, wherein: The processor is further configured to: An azimuth or elevation spectrum describing the power of the corresponding incident signal relative to the angle of arrival is determined.

18. The sensor system of claim 15, further comprising: A plurality of transmitter antennas configured to transmit electromagnetic energy beams, wherein the plurality of transmitter antennas and the plurality of receiver antennas form a virtual array of a multiple-input multiple-output (MIMO) radar.

19. The sensor system of claim 15, further comprising: Determine the scope of the stated objectives; determining whether the target is in the near field of the plurality of receiver antennas based on the range; as well as The angle of arrival is determined using the plurality of incident signals when the target is in the far field of the radar.

20. A non-transitory computer readable medium comprising instructions for determining an angle of arrival of a target, the instructions causing a computing system to perform operations comprising: receiving signal data corresponding to a plurality of incident signals reflected from the target and received at a plurality of receiver antennas; Determine the scope of the stated objectives; identifying a subset of receiver antennas from the plurality of receiver antennas based on the range; as well as Angle of arrival (AOA) processing is performed on the corresponding data of the subset of receiver antennas to determine the angle of arrival.

21. A method for determining an angle of arrival of a target, comprising: The processor determines the expected maximum range; activating, by the processor, a subset of antenna elements among a plurality of antenna elements based on the desired maximum range; receiving, at a plurality of receiver antennas, a plurality of incident signals reflected from the target from the plurality of antenna elements; Angle of arrival (AOA) processing is performed by the processor on respective incident signals for the subset of receiver antennas to determine the angle of arrival.

22. The method according to claim 21, further comprising: Elevation and azimuth angles relative to the target and Doppler velocity are determined based on the AOA processing.

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