Patent Publication Number: US-2023152436-A1

Title: System and Method for Determining Angle of Arrival in a Radar Based Point Cloud Generation

Description:
BACKGROUND 
     Cross References to Related Applications 
     This application claims priority from Indian Patent application No. : 202141052298 filed on Nov. 15, 2021 which is incorporated herein in its entirety by reference 
     Technical Field 
     Embodiments of the present disclosure relate to radar system and in particular relates to a system and method for determining angle of arrival in radar based point cloud generation. 
     Related Art 
     Radar systems are generally employed for object detection and increasingly used in various automotive applications such as for driver assistance, obstacle detection, avoidance, and navigation of drones/UAVs, terrain mapping, for example. As is well known, radars can detect surrounding obstacles or objects and send the relevant information like distance, relative position, and direction and velocity of the object that are in motion to a controller (software or hardware) or to a decision making unit in the automotive device. 
     The point cloud often refers to set of points representing one or more objects in the three dimensional space detected by the radar system. Each point in the point cloud is represented by the distance (range), Azimuth, and Elevation angles in the three dimensional space. The Azimuth and/or Elevation angle are often determined by measuring the angle of arrival (AoA) of the received (reflected) signal. When the angle of arrival is determined in only one coordinate (say Azimuth or Elevation) the point cloud so formed, along with the range is a two dimensional point cloud. Similarly, when AoA is determined in both the coordinates, along with the range, the point cloud is three dimensional. 
     In some applications antenna arrays are employed to transmit and receive radar signal. The antenna array enables formation of an RF signal beam both for transmitting and receiving the radar signal. In that, time shifted (or phase shifted) radar signals are transmitted/received over the antennas to steer the beam in desired direction as is well known in the art. A two or three dimensional object shape and location is determined by steering the beam over a range/area. 
     Briefly,  FIG.  1 A  illustrates a conventional technique for determining the range and angle. In that, antenna array  101  transmits and receives the radar signal. In that, antenna array  101  transmits the radar signal provided by the radar transmitter  102 . As is well known, the radar transmitter  102  provides phase shifted version of a radar signal to the antenna array to form a beam in a desired direction and the phase angle is adjusted to steer the beam over the desired area. Similarly, the antenna array  101  receives the radar signal reflected from one or more objects and provides the received signal to the radar receiver  103 . 
     The arrangement of the antenna array and the geometrical precision determines the accuracy of the detection of the objects in two dimensions (2D) or three dimensions (3D) object.  FIG.  1 B  illustrates an example antenna array  101  arrangement. In that, transmitting antenna array  110 A-N is shown arranged in the vertical coordinate (along one of the desired axis, say Y-Axis) and the receiving antenna array  120 A-K is shown arranged in the horizontal coordinate (along another axis of interest, say X-axis). The antenna elements are positioned at equidistance from one another (generally referred to as linear). In the MIMO configuration, the antenna array  110  and  120  together form two dimensional array with K columns and N rows (NXK) that are orthogonal to each other.  FIG.  1 C  illustrates the equivalent 2D MIMO antenna array formed by the antenna arrangement in  FIG.  1 B . As well known in the art, the objects position/motion in vertical direction (elevation) is captured by the signal received on the vertically positioned antenna array and the objects position in horizontal directions (Azimuth) are captured/ detected by signal received on the horizontal antenna array (orthogonal). 
     Continuing with respect  FIG.  1 A , the radar receiver  103  may demodulate and perform signal processing like Fast Fourier Transform (FFT) to extract range and Doppler. The range and Doppler is provided to the detector  104  that selects signals with Signal-to-Noise Ratio (SNR) higher than a preset threshold. The selected signal is provided to the beam former  105  for angle of arrival processing of the selected signals. The detector  106  selects the beam that corresponds to local peak. However such conventional radar system lacks resolution to detect objects with more precision. Additionally, the system may require antennas to be arranged geometrically precise. For example, the beam forming using FFT techniques may require the antenna arrangement to be uniformly spaced and geometrically orthogonal (as in  FIG.  1 B ) creating a filled 2D MIMO array as shown in  FIG.  1 C . 
     In some instances, the antenna array is not formed geometrically uniform or orthogonal to each other nor the MIMO array be filled. For example, a combination of receive and transmit antennas can be used to create two 1D MIMO arrays in two axis instead of a filled 2D MIMO array, where the two 1D array may/may not be orthogonal to each other.  FIG.  1 D  illustrates an example non-orthogonal MIMO antenna array. As shown there, the array  130  is aligned at an angle with the array  140 . Each of the array ( 130  or  140 ) may be created using a combination of transmitters and receivers to maximize the individual 1D MIMO arrays while minimizing the number of physical transmit and receive channels required, thus forming two dimensional MIMO array as is well known. In that, due to non-orthogonality, the array  130  detects both azimuth and elevation of the object while the array  140  detects the object only in the azimuth and the resultant MIMO array is un-filled, unlike example in  FIG.  1 C . In such scenario, the beamforming using FFT may be inaccurate and erroneous. 
     In particular, when the radar system is employed for imaging (often referred to as imaging radar) or generating point cloud, a large field of view (FoV) as well as a high angle resolution (both azimuth and elevation) is desirable to get the shape and contour of a 3D object. For example, high angle resolution in a radar system enables representing a 3D object with a larger number of points for more accurate detection of the object. However, the beam width is limited by the antenna radiation pattern such as main lobe, side lobes etc., as is well known in the art. Some of the conventional techniques employed for detecting more objects (increase angle resolution) are described below for reference. 
       FIG.  1 E  illustrates another conventional technique. As shown there, correlator  157  and Capon beamformer  158  are additionally employed between the detector  104  and  106 . The correlator  157  makes use of the selected signal from detector  104  over multiple frames to determine the covariance. For example, the correlator  157  may perform correlation of the data received from the detector  104  with the data received over prior K frames. The correlated data is provided to the Capon beamformer  158  for generating the beam. 
     Due to correlation (data dependent beam forming) and Capon beamforming, the nonlinearity and non-orthogonality in the antenna arrangement (for example, side lobes), errors are removed to an extent there by increasing the resolution as is well known in the art. However, such conventional technique requires buffering the data over K frames there by increasing the response time, at least. 
     As may be appreciated, the conventional techniques of  FIG.  1 E  employs multiple snapshots of the received data and hence are referred to as data dependent beam forming. The conventional techniques consume high processing power and time to process large data to determine the 2D AoA, at least. 
     SUMMARY 
     According to an aspect, a method of determining two dimensional (2D) angle of arrival (AoA) in a radar system comprising determining one dimensional (1D) AoA to generate a first set of (AoA), selecting a set of valid 1D AoA angles from the first set AoA, and determining the 2D AoA from the set of valid 1D AoA and input data. Wherein the 1D AoA is determined on a first set of data received over a first linear MIMO antenna array arranged in the first axis and the first set of AoA comprising K angles, and the set of valid 1D AoA comprising L angles, in that L is less than K. 
     According to another aspect, the 2D AoA is determined on a second set data received over the 2D MIMO antenna array for the set of valid 1D AoA in the first axis. Wherein the second antenna array is may/may not be orthogonal to the first linear MIMO array. 
     According to another aspect, the 2D AoA is determined iteratively using relation Res(k) = ∥Y - A mi (k)x∥ 2  such that Res(k) successively reduced by iteratively setting the values for x, in that Y represents the high SNR received signal, Ami represents the interpolated direction vector, k is a value representing number of iteration and x is a value determined at every iteration to minimize the residue Res(k).. 
     According to another aspect, a radar system comprises, a two dimensional (2D) multiple input and multiple output (MIMO) antenna array arranged in first axis and second axis is configured to receiving a radar signal reflected from a set of objects, wherein MIMO antennas in the first axis form a uniform linear array, a range detector generating a set of ranges representing ranges of the set of objects, a Doppler detector generating a plurality of Doppler representing relative velocity of the set of object, a one dimensional (1D) angle of arrival generator configured to determine a first set of valid angles corresponding to the set of objects using only the MIMO antennas in the first axis, and a two dimensional (2D) angle of arrival generator configured to determine a second set of 2D angle of arrival using the first set of valid angles and the 2D MIMO antenna array. 
     Several aspects are described below, with reference to diagrams. It should be understood that numerous specific details, relationships, and methods are set forth to provide full understanding of the present disclosure. Skilled personnel in the relevant art, however, will readily recognize that the present disclosure can be practiced without one or more of the specific details, or with other methods, etc. In other instances, well-known structures or operations are not shown in detail to avoid obscuring the features of the present disclosure. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG.  1 A  illustrates one conventional technique for determining the range and angle. 
         FIG.  1 B  illustrates an example antenna array  101  arrangement. 
         FIG.  1 C  illustrates the 2D MIMO antenna array for beam forming. 
         FIG.  1 D  illustrates the non-orthogonal antenna array 
         FIG.  1 E  illustrates another conventional technique. 
         FIG.  2    is a block diagram of an example radar system (environment) in which various aspects of the present invention may be seen. 
         FIG.  3 A  is an example radar transceiver for object detection and recognition in an embodiment. 
         FIG.  3 B  illustrates the example transmitted and received chirps in an embodiment. 
         FIG.  4    is a block diagram illustrating the manner in which the 2D angle of arrival is determined in an embodiment. 
         FIG.  5    is a block diagram illustrating the manner in which 2D AoA may be implemented in an embodiment. 
         FIG.  6    is a graphical representation illustrating the manner in which iterative AoA is performed in an embodiment. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EXAMPLES** 
       FIG.  2    is a block diagram of an example radar system  200  (environment) in which various aspects of the present invention may be seen. The environment is shown comprising objects  210 , Radio Frequency (RF) transceiver  220 , processor  230 , output device  240  and memory  250 . Each element in the system  200  is further described below. 
     RF transceiver  220  transmits a radar (RF) signal over a desired direction(s) and receives a reflected radar signal that is reflected by the object  210 . In one embodiment, the RF transceiver  220  may employ multiple (one or more) receiving antennas to receive the reflected RF signal and multiple (one or more) transmitting antenna for transmitting the radar signal. Accordingly, the transceiver  220  may employ these multiple transmitting/receiving antennas in several of multiple input and multiple output (MIMO) configurations to form desired transmitting and receiving RF signal beam (often referred to as Beam forming) to detect objects from the reflected signal. The objects  210  may comprise a terrain, terrain projections, single object, cluster of objects, multiple disconnected objects, stationary object, moving object, live objects etc. 
     Processor  230  conditions and processes the received reflected RF signal to detect one or more objects (for example  210 ) and determines one or more properties of the objects. The properties of the object thus determined (like shape, size, relative distance, velocity, position in terms of azimuth and elevation etc. ) are provided to the output device  240 . In an embodiment, the processor  230  comprises signal conditioner to perform signal conditioning operations and provides the conditioned RF signal for digital processing. The memory  250  may store RF signal like samples of the reflected RF signal for processing. The processor  230  may temporarily store received data, signal samples, intermediate data, results of mathematical operations, etc. , in the memory  250  (such as buffers, registers). In an embodiment, the processor  230  may comprise group of signal processing blocks each performing the specific operations on the received signal and together operative to detect object and its characteristics/properties. 
     The output device  240  comprises navigation control electronics, display device, decision making electronic circuitry and other controllers respectively for navigation, display and further processing the received details of the object. Accordingly, the system  200  may be deployed as part of unmanned vehicles, driver assistant systems, for obstacle detection, navigation and control, and for terrain mapping. 
     In an embodiment, the RF transceiver  220 , processor  230 , and memory  250  are implemented as part of an integrated circuit integrated with other functionality and/or as a single chip integrated circuit with interfaces for external connectivity like the output device  240 . The manner in which the transceiver  220  and the processor  230  (together referred to as Radar transceiver) may be implemented in an embodiment is further described below. 
       FIG.  3 A  is an example radar transceiver for object detection and recognition in an embodiment. The radar transceiver  300  is shown comprising transmitting antenna array  310 , transmitter block  315 , receiving antenna array  320 , mixer  325 , filter  330  Analog to digital converter (ADC)  340 , Range FFT  350 , Doppler FFT  360  and AoA detector  370 . Each element is described in further detail below. 
     The transmitting antenna array  310  and the transmitter  315  operate in conjunction to transmit RF signal over a desired direction. The transmitter  315  generates a radar signal for transmission and provides the same to the transmitting antenna array  310  for transmission. The transmitting antenna array  310  is employed to form a transmit beam with an antenna aperture to illuminate objects at suitable distance and of suitable size. Various known beam forming techniques may be employed for changing the illuminated region. In one embodiment, the transmitter  215  may generate a radar signal comprising sequence of chirps. 
     The receiving antenna array  320  comprises antenna elements each element capable of receiving reflected RF signal. The receiving antenna array  320  is employed to form an aperture to detect objects with a desired resolution (for example object of suitable size). The RF signal received on each element corresponding to one transmitted chirp represents one snapshot. The received signal (the sequence of snapshots corresponding to the sequence of chirps transmitted) is provided to the mixer  325 . 
     The Mixer  325  mixes RF signal received on each antenna element in the array with the transmitted chirp (local oscillator frequency) to generate an intermediate frequency signal (IF signal). In that the mixer  325  may comprise number of complex or real mixers to mix each RF signal received on the corresponding antenna elements. Alternatively, the mixer  325  may comprise of fewer mixers multiplexed to perform desired operation. The number of intermediate frequency (IF) signal is provided on path  323  to filter  330 . The filter  330  passes the IF signal attenuating the other frequency components (such as various harmonics) received from the mixer. 
       FIG.  3 B  illustrates the example transmitted and received chirps in an embodiment. The curve  321 A represents the transmitted chirps, the curve  321 B represents the received chirps and the curve  326  representing the baseband signal (IF signal). In that,  322  representing the active chirp time,  323  representing the chirp bandwidth,  324  representing the chirp idle time and  327  representing the chirp usable time. 
     Continuing with  FIG.  3 A , the filter  330  may be implemented as a pass band filter to pass a desired bandwidth (in conjunction with chirp bandwidth BW). The filtered IF signal is provided on path  334  to ADC  340 . 
     The ADC  340  converts IF signal received on path  334  (analog IF signal) to digital values. The ADC  340  may sample the analog IF signal at a sampling frequency Fs and convert each sample value to a bit sequence or binary value. In one embodiment the ADC  340  may generate 256/512/1024 samples per chirp signal. That is, N samples in the time period  327 . The digitized samples of IF signal (digital IF signal) is provided for further processing. 
     The Range Fast Fourier transform (FFT)  350 , performs FFT on the digital IF samples to generate plurality of ranges of the plurality objects  210 . For example, range FFT  350  performs FFT on digital IF signal corresponding to each chirp. The Range FFT  350  produces peaks representing the ranges of the objects. 
     The Doppler FFT  360  performs FFT operation on the ranges across chirps. The peaks in the Doppler FFT represent the Doppler of the objects or the velocity of the objects. The ranges and Doppler of the objects are provided to the AoA detector  370 . 
     The AoA detector  370  determines the angle of arrival and estimates the azimuth and elevation the objects and points to form the points cloud. The AoA detector  370  detects objects with higher resolution with a reduced computational complexity and data processing from the RF signal received on the receiving antenna array  320  with resolution corresponding and/or in excess of the physical limitation of the antenna array. Thus, enhancing the antenna aperture. The manner in which the AoA detector  370  detects the azimuth and elevation in an embodiment is further described below. 
       FIG.  4    is a block diagram illustrating the manner in which the 2D angle of arrival is determined in an embodiment. In the block  410 , the AoA detector  370 , receives detected Doppler and range corresponding to set of object/points detected. The range and Doppler may be as received on path  367 . 
     In the block  420 , the AoA detector  370 , performs one dimensional angle of arrival determination. The one dimensional angle of arrival may correspond to one of the azimuth or elevation. That is, the AoA detector  370  uses only a partial data received on the antenna array (to say, a subset of the antenna array for processing). For example, the partial data corresponds to data receive on the selected antennas (also referred to as sensors) of the antenna array. The partial or set of antennas (or elements) are selected such that they are capable of determining the one dimensional angle of arrival instead of two dimensions. That is, selected antennas are from a row or a column that is linear. Accordingly, the one dimensional AoA may be one of elevation or azimuth only as may be the case. 
     In the block  430 , the AoA detector  370 , selects the subset of the 1D angles of arrival. In one embodiment, the subset of the 1D angles of arrival determined may comprise prominent peak in the angle estimation spectrum or in the beam former employed for determining the 1D AoA . A threshold value may be set to select the desired vectors (or angle of arrival) in 1D estimation. The only the vectors above the threshold value are selected as the subset for the determination of 2D angle of arrival. 
     In the block  440 , the AoA detector  370  performs the interpolation of the subset of the direction vectors selected for the 2D angle determination. In one embodiment, the interpolation may be performed based on the operating conditions like desired resolution, RF bandwidth, and Field of view (FOV). The interpolated set of data is used for 2D AoA determination. 
     In the block  450 , the AoA detector  370  determines the 2D AoA from the interpolated subset of the direction vector. As may be appreciated, the AoA detector  370  is configured to perform the angle of arrival estimation successively (Successive angle estimation), i. e. , at first 1D angle estimation and then 2D estimation on the selected data set derived from 1D AoA estimation. As a result, the 2D AoA determination is performed over limited direction vectors instead of entire set. Thus, the processing power and time for determining 2D AoA is reduced. In one embodiment, advantage of the reduced set of data processing is utilized to enhance the resolution in 1D AoA determination and 2D AoA determination. 
       FIG.  5    is a block diagram illustrating the manner in which 2D AoA may be implemented in an embodiment. The block diagram is shown comprising 1D AoA estimator  510 , first detector  520 , selector  530 , interpolator  540 , Iterative 2D estimator  550 , and the second detector  560 . Each block is described in further detailed below. 
     The 1D AoA estimators  510  is configured to perform 1D angle of arrival estimation over the one dimensional antenna array. In one embodiment the one dimensional antenna array is linearly arranged either in the azimuth or elevation such that, it is orthogonal to the other axis and also linear in its axis. The data received on the path  367  for every antenna in the 1D antenna array is processed for determination of 1D AOA. The processing may be a one of a one dimensional FFT over the antenna array or beamforming operation at a desired resolution. In case of a beam forming, any of the known beam forming techniques may be implemented such as capon Beam forming, for example. The 1D AoA may provide a K number of points representing the K angles. The K may be selected based on the resolution and the Field of View. 
     The first detector  520  selects the number of points that are valid. For example, the first detector  520  may select L number of points from the K points that are above a threshold (in case of FFT) or based on a below a residual value (in case of iterative beam forming). 
     The selector  530  generates the antenna matrix having a reflection coefficient or direction vector of the antenna array forming the two dimensions corresponding to the L 1D AoA’s. That is, the selector may prepare L X M antenna matrix where the M is the antenna elements in the other axis. That is, in case if K is linear array in the azimuth, the M may be the array in the elevation that may not be orthogonal to K antenna array in the azimuth. 
     The interpolator  540  interpolates the L X M matrix based on the resolution and field of view (FOV) required. Interpolator  540  may set the search space for iterative angle estimation in 2D. The interpolated data is provided to the iterative 2D estimator  550 . 
     The iterative 2D estimator  550  estimates the two dimensional angle of arrival for the set of data over the interpolated L X M antenna matrix. In one embodiment, the iterative 2D estimator  550  chooses 2D-AoA from among the components iteratively by reducing the residual error, that is measured as a function of the incoming data (on path  367 ). The Selection of the number of outputs at each stage is done using one or more criteria such as using a relative threshold from the output having maximum strength, iterate for pre-defined number of iteration(s) and selecting a solution of particular iteration if residual error is smaller than pre-defined threshold. 
     In one embodiment, the iterative 2D estimator  550  employs relation:Res(k) = ∥Y - A mi (k)x∥ 2 , in that, Y represents the data received on path  367 , A mi  represents the interpolated direction vector on the path  545 , k is the number of iteration and x is the value determined at every iteration to minimize the residue Res(k). The relation may be iterated as long as the res(k) is greater than pre-defined threshold or may be iterated over a pre-defined number of iterations (k). As an example the residual value less than 5 percent of Y in general implies that 95 percent of the energy of the incoming signal has been assigned to detected targets. The iterated data with the peaks above a threshold are provided to the second detector  560 . 
     The second detector  560  may perform operation similar to the first detector  520  and select the valid angles. The valid two dimensional angles of arrival representing the Azimuth and Elevation corresponding to each object/point detected in and received on path  367  is provided as 3D point cloud. 
       FIG.  6    is a graphical representation illustrating the manner in which iterative AoA is performed in an embodiment. In that  610  represents MIMO antenna array with K X M antennas. The  620  represents the data set received on each antenna in the array  610 . The  630  represents the set of ranges (rl, r2.. rx) determined in the range FFT  350 , the item  640  represents the velocities (Doppler) v1, v2, ...vx determined by the doppler FFT  360 . 
     Matrix  650  represents the 1D AoA determined by the 1D AoA estimator  510 . In that, θ 1 , θ 2 ... θ s  representing the angle detected over a search space in 1D, and θ 1 ~θ 2  representing the angle resolution and θ 1 ~θ s  representing the FoV in one direction (Azimuth). Matrix  660  represents the angles determined as valid by the first detector  620 , The matrix  660  is shown comprising θ 2 , θ 5 , ...θ p (L angles from Sangles in  650 ). The matrix  670  represents antenna matrix generated by the selector  530 . The antenna matrix  670  is shown comprising LXM elements θ 21,  θ 22 , θ 23 , ... θ 2M, θ 51 , θ 52 , θ 53 , ... θ 5M... θ p1 , θp 2 , θp 3 , ... θ pM . 
     The item  680  represents the interpolated data provided by the interpolator  540 . As shown there the data is shown comprising additional data points θ i1, θ i2  ... θ iq,  in each column. Though q number of data points is shown to have been added in sequence for illustration, each column may contain the added data points at interspersed. In that θ 1 ~θ q +Mrepresents FoV in the elevation and θ q+M-1 ~θ q+M  representing the resolution the elevation. Item  690  represents the selected angles in the 2D AoA as valid by the second selector  560 . The bold values illustrate the selected values in the 2D. 
     While various embodiments of the present disclosure have been described above, it should be understood that they have been presented by way of example only, and not limitation. Thus, the breadth and scope of the present disclosure should not be limited by any of the above-discussed embodiments, but should be defined only in accordance with the following claims and their equivalents.