KR20190108006A - Apparatus and method for processing radar signal - Google Patents

Abstract

Disclosed are a radar signal processing device and method. The radar signal processing method comprises the steps of: generating a spatial-temporal covariance matrix by using a radar signal reflected and received by a target present in a search region; identifying a steering vector for time delay of arrival (TOA) and angle of arrival (AOA) of the target by using the generated spatial-temporal covariance matrix; determining TOA of the target by performing frequency transformation, to which the steering vector of the identified TOA is applied, to the received radar signal; and extracting AOA of the target by applying the determined TOA of the target to a frequency detection algorithm. The present invention can simultaneously estimate TOA and AOA of a target.

Description

Radar signal processing apparatus and method {APPARATUS AND METHOD FOR PROCESSING RADAR SIGNAL}

The present invention relates to a radar signal processing apparatus and method, and more particularly to an apparatus and method for improving the performance of the frequency detection in the field of sensors using the radar.

The frequency modulation continuous wave (FMCW) radar system can estimate distance-velocity information for multiple targets by simultaneously using the time-frequency domain. In addition, the FMCW radar system has high bandwidth efficiency and low complexity, making it a key technology for automotive radar systems. In the FMCW radar system, since the beat frequency is determined according to the distance and speed of each target, it is very important to accurately estimate the frequency components.

In order to estimate such frequency components, a frequency transform based method such as a Fast Fourier Transform (FFT) is most widely used in an FMCW radar system. However, FFT-based schemes for estimating frequency components do not have high resolution, and thus, when multiple targets are adjacent, there is a high probability of recognizing a single target. In the vehicle radar system, since high resolution and long-range detection conditions are required, the existing 24 GHz Industry-Science-Medical (ISM) band radar has a problem that it is difficult to meet the various requirements of vehicle detection.

To improve this, super-resolution frequency detection algorithms such as 2D-ESPRIT (2 dimension-estimation of signal parameters via rotational invariance techniques) or 2D-MUSIC (2 dimension-multiple signal classification) have been proposed. However, these techniques have very high computational complexity and are not suitable for vehicles requiring frequency estimation in real time.

The present invention provides an apparatus and method for simultaneously estimating the arrival delay time (TOA) and arrival direction (AOA) of a target to be detected by using a discrete Fourier transform (DFT) and a MUSIC algorithm for a low complexity FMCW radar system. .

Radar signal processing method according to an embodiment of the present invention comprises the steps of generating a space-time covariance matrix using a radar signal received by the target reflected in the search region; Steering vector for Time Delay Arrival (TOA) and Angle of Arrival (AOA) of the target using the generated spatial-temporal covariance matrix Identifying; Determining a TOA of the target by performing a frequency conversion to which the steering vector of the identified TOA is applied to the received radar signal; And applying the determined TOA of the target to a frequency detection algorithm to extract the AOA of the target.

The generating may include stacking the received radar signal; And generating a space-time covariance matrix using the stacked radar signals.

Decomposing the generated spatiotemporal covariance matrix into a signal subspace matrix and a noise subspace matrix through eigen value decomposition (EVD), wherein the identifying is orthogonal to the noise subspace matrix. A steering vector for the TOA and the AOA of the target may be identified based on the direction vector of the target.

The determining may include performing a Discrete Fourier Transform (DFT) on the received radar signal; And determining a TOA of the target by performing peak detection on a radar signal on which the DFT is performed.

The extracting may include applying a TOA of the determined target to a multiple signal classification (MUSIC) estimator; And extracting an AOA of the target by performing peak detection on a result value of the MUSIC estimator.

Radar signal processing apparatus according to an embodiment of the present invention comprises a communication module for receiving a radar signal received by the target reflected in the search area; And a processor for simultaneously estimating TOA and AOA of the target by using the received radar signal, wherein the processor generates a space-time covariance matrix using the received radar signal and generates the space-time covariance matrix. identify a steering vector for a Time Delay Arrival (TOA) and an Angle of Arrival (AOA) of the target using a temporal covariance matrix, the received radar The TOA of the target may be determined by performing a frequency transformation to which the steering vector of the identified TOA is applied to the signal, and the AOA of the target may be extracted by applying the determined TOA to the frequency detection algorithm.

The processor may stack the received radar signal and generate a space-time covariance matrix using the stacked radar signal.

The processor decomposes the generated space-time covariance matrix through an eigen value decomposition (EVD) into a signal subspace matrix and a noise subspace matrix, and is based on a direction vector of the target orthogonal to the noise subspace matrix. The steering vector for the TOA and AOA of the target can be identified.

The processor may perform a Discrete Fourier Transform (DFT) on the received radar signal, and perform peak detection on the radar signal on which the DFT is performed to determine the TOA of the target. have.

The processor may extract the AOA of the target by applying a TOA of the determined target to a multiple signal classification (MUSIC) estimator and performing peak detection on a result value of the MUSIC estimator.

According to an embodiment of the present invention, a time delay of arrival (TOA) and a direction of arrival of a target to be detected by using a discrete Fourier transform (DFT) and a MUSIC algorithm for a low complexity FMCW radar system Angle of arrival (hereinafter referred to as AOA) can be estimated simultaneously.

1 is a diagram illustrating a radar signal processing apparatus according to an exemplary embodiment of the present invention.
2 is a flowchart illustrating a radar signal processing method according to an embodiment of the present invention.

Hereinafter, exemplary embodiments will be described in detail with reference to the accompanying drawings. However, various changes may be made to the embodiments so that the scope of the patent application is not limited or limited by these embodiments. It is to be understood that all changes, equivalents, and substitutes for the embodiments are included in the scope of rights.

The terminology used herein is for the purpose of description and should not be construed as limiting. Singular expressions include plural expressions unless the context clearly indicates otherwise. In this specification, terms such as "comprise" or "have" are intended to indicate that there is a feature, number, step, action, component, part, or combination thereof described on the specification, and one or more other features. It is to be understood that the present invention does not exclude the possibility of the presence or the addition of numbers, steps, operations, components, components, or a combination thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art. Terms such as those defined in the commonly used dictionaries should be construed as having meanings consistent with the meanings in the context of the related art and shall not be construed in ideal or excessively formal meanings unless expressly defined in this application. Do not.

 In addition, in the description with reference to the accompanying drawings, the same components regardless of reference numerals will be given the same reference numerals and duplicate description thereof will be omitted. In the following description of the embodiment, when it is determined that the detailed description of the related known technology may unnecessarily obscure the gist of the embodiment, the detailed description thereof will be omitted.

1 is a diagram illustrating a radar signal processing apparatus according to an exemplary embodiment of the present invention.

Referring to FIG. 1, the radar signal processing apparatus 100 of the present invention may include a communication module 110 and a processor 120. In detail, the communication module 110 may receive the radar signal reflected by the target present in the search area. In addition, the processor 120 may simultaneously estimate the TOA and the AOA of the target using the radar signal received through the communication module 110. In this case, the processor 120 uses a discrete Fourier transform (DFT) and a multiple signal classification (MUSIC) estimator instead of an ultra high-resolution frequency detection algorithm such as 2D-ESPRIT or 2D-MUSIC having a high computational complexity. It is possible to estimate the target's TOA and AOA at the same time, quickly and accurately, with computational complexity. In this case, the radar signal processing apparatus 100 may be included in the FMCW radar system.

To this end, the radar signal processed by the radar signal processing apparatus 100 may have a signal model as follows. First, the transmission radar signal transmitted through the transmission channel of the radar may be expressed by Equation 1 below.

<Equation 1>

Where ω _s is the initial frequency, μ is the instantaneous frequency change rate of the chirp symbol, μ = ω _BW / T _sym , ω _BW is the bandwidth of the FMCW signal, and T _sym is the signal period of the FMCW symbol.

In the case of a uniform linear array (ULA) consisting of K elements, M objects may be considered. The reception radar signal for each antenna element in the time invariant channel of T _sym may be represented by Equation 2 below.

<Equation 2>

Where a _m represents the complex amplitude for the m th target, τ _m defines the TOA for the m th target, λ represents the wavelength of the carrier signal, d represents the spacing between adjacent antenna elements, and θ _m is An AOA can be defined for the m th target. And ω _k ( t ) is the additive white Gaussian noise (AWGN) signal at the k-th antenna element.

Using the signal reflected from the target, de-chirping multiplies the conjugation of the reception radar signal y ( t ) and the transmission radar signal s ^* ( t ) by d _k as shown in Equation 3 below. (t) can be obtained.

<Equation 3>

Here, d _k (t) means the output result of the de-chirp method in the k-th antenna array. The signal d _k (t) converted using Equation 3 may be expressed as a sine wave through Equation 4 below.

<Equation 4>

Where d is assumed to be λ / 2.

When the Nyquist sampling frequency is f _s = 1 / T _s , the discrete time model d _k [ n ] of d _k ( t ) through the analog-to-digital converter (ADC) is expressed as in Equation 5 below. Can be.

<Equation 5>

Where n = 0, 1,... N- 1. In the radar signal processing method of the present invention, the TOA and the AOA of the target may be simultaneously estimated using d _k [ n ], which is a discrete time model of the received radar signal.

2 is a flowchart illustrating a radar signal processing method according to an embodiment of the present invention.

In operation 210, the radar signal processing apparatus 100 may generate a space-time covariance matrix using the received radar signal. First, the radar signal processing apparatus 100 may stack the received radar signals to generate a stacking reception data matrix D _n as shown in Equation 6 below.

<Equation 6>

Where L is a selection parameter that satisfies 2 ≦ L < N .

The DFT-MUSIC estimation algorithm processed by the radar signal processing apparatus 100 of the present invention is based on the stacking reception data matrix of Equation 6, and generates a space-time covariance matrix using the stacking reception data matrix through Equation 7 below. can do.

<Equation 7>

In operation 220, the radar signal processing apparatus 100 may identify the steering vector for the TOA and the AOA of the target by using the generated space-time covariance matrix. In detail, the radar signal processing apparatus 100 may decompose the spatiotemporal covariance matrix into a signal subspace matrix U _s and a noise partial matrix U _n by performing eigenvalue decomposition. Thereafter, the radar signal processing apparatus 100 may obtain a direction vector of an actual target orthogonal to the decomposed noise partial matrix U _n as shown in Equation 8 below.

<Equation 8>

는 하기의 식 9과 같이 쓸 수 있다.At this time,

Can be written as in Equation 9 below.

<Equation 9>

이다.here

to be.

The radar signal processing apparatus 100 of the present invention can find the TOA and the AOA of the target, respectively, using Equation 9 above.

In operation 230, the radar signal processing apparatus 100 may determine the TOA of the target by performing a frequency conversion to which the steering vector of the identified TOA is applied to the received radar signal. First, the radar signal processing apparatus 100 may determine a TOA of a target by performing discrete Fourier transform on a sample of a received radar signal, that is, a stacking received data matrix, and performing peak detection on a result of the discrete Fourier transform being performed. . The TOA of the multiple targets can be estimated from the DFT index of the radar signal received at the first antenna array. Specifically, the discrete Fourier transform in the present invention may be defined as in Equation 10 below.

<Equation 10>

Where E = [ e ₁ , e _{2,... ,} e _P ] is the steering vector for TOA, e _p = [1 e- ^{j 2} _{π p} ^{/ L.} e- ^{j 2 ( L- 1) πp / L} ] ^T is represented.

을 의미한다. 따라서 m 번째 타겟에 대한 추정된 TOA의 방향 벡터는 하기의 식 11과 같이 나타낼 수 있다.That is, the radar signal processing apparatus 100 performs the discrete Fourier transform on the first antenna array and performs peak detection on the result of the discrete Fourier transform being performed. Thus, the TOA index vector I = [ I ₀ for the multiple targets is performed _. , I ₁ ,… , I _{M- 1} ] can be determined. Where I _m is

Means. Accordingly, the direction vector of the estimated TOA for the m th target may be expressed as in Equation 11 below.

<Equation 11>

In operation 240, the radar signal processing apparatus 100 may extract the target AOA by applying the determined TOA of the target to a frequency detection algorithm. In detail, the radar signal processing apparatus 100 may substitute the direction vector of the TOA determined in Equation 11 into Equation 9 to extract other AOAs. Through this, the radar signal processing apparatus 100 may obtain a MUSIC estimator for the m th target as shown in Equation 12 below.

<Equation 12>

이다. here

to be.

The radar signal processing apparatus 100 performs MUSIC estimation on the m th target using Equation 12, and then performs peak detection on the result of performing the AOA index matrix J = [ J ₀ , J ₁ ,... , J _{M - 1} ] can be used to extract the AOA of the m-th target as shown in Equation 13.

<Equation 13>

Where sin-1 (-) is the inverse operator of the sine function.

Through the above, the radar signal processing apparatus 100 of the present invention may estimate the TOA and the AOA of the target for the vehicle FMCW radar at the same time. At this time, the radar signal processing apparatus 100 uses a DFT and a MUSIC estimator, unlike the conventional method using an ultra high resolution frequency detection algorithm such as 2D-ESPRIT or 2D-MUSIC, which has a very high computational complexity, and thus has low computational complexity and speed. Accurately estimate the target's TOA and AOA simultaneously.

The method according to the embodiment may be embodied in the form of program instructions that can be executed by various computer means and recorded in a computer readable medium. The computer readable medium may include program instructions, data files, data structures, etc. alone or in combination. The program instructions recorded on the media may be those specially designed and constructed for the purposes of the embodiments, or they may be of the kind well-known and available to those having skill in the computer software arts. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tape, optical media such as CD-ROMs, DVDs, and magnetic disks, such as floppy disks. Magneto-optical media, and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like. Examples of program instructions include not only machine code generated by a compiler, but also high-level language code that can be executed by a computer using an interpreter or the like. The hardware device described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

The software may include a computer program, code, instructions, or a combination of one or more of the above, and configure the processing device to operate as desired, or process it independently or collectively. You can command the device. Software and / or data may be any type of machine, component, physical device, virtual equipment, computer storage medium or device in order to be interpreted by or to provide instructions or data to the processing device. Or may be permanently or temporarily embodied in a signal wave to be transmitted. The software may be distributed over networked computer systems so that they may be stored or executed in a distributed manner. Software and data may be stored on one or more computer readable recording media.

Although the embodiments have been described with reference to the accompanying drawings, those skilled in the art may apply various technical modifications and variations based on the above. For example, the described techniques may be performed in a different order than the described method, and / or components of the described systems, structures, devices, circuits, etc. may be combined or combined in a different form than the described method, or other components. Or even if replaced or substituted by equivalents, an appropriate result can be achieved.

Therefore, other implementations, other embodiments, and equivalents to the claims are within the scope of the following claims.

100: radar signal processing device
110: communication module
120: processor

Claims (11)

Generating a space-time covariance matrix using radar signals received and reflected by a target present in the search region;
Steering vector for Time Delay Arrival (TOA) and Angle of Arrival (AOA) of the target using the generated spatial-temporal covariance matrix Identifying;
Determining a TOA of the target by performing a frequency conversion to which the steering vector of the identified TOA is applied to the received radar signal;
Extracting the AOA of the target by applying the determined TOA of the target to a frequency detection algorithm;
Radar signal processing method comprising a.
The method of claim 1,
The generating step,
Stacking the received radar signals; And
Generating a space-time covariance matrix using the stacked radar signals
Radar signal processing method comprising a.
The method of claim 1,
Decomposing the generated space-time covariance matrix into a signal subspace matrix and a noise subspace matrix through eigen value decomposition (EVD);
More,
The identifying step,
And a steering vector for a TOA and an AOA of the target based on a direction vector of the target orthogonal to the noise subspace matrix.
The method of claim 1,
The determining step,
Performing a Discrete Fourier Transform (DFT) on the received radar signal; And
Determining the TOA of the target by performing peak detection on the radar signal subjected to the DFT
Radar signal processing method comprising a.
The method of claim 1,
The extracting step,
Applying the determined TOA of the target to a multiple signal classification (MUSIC) estimator; And
Extracting AOA of the target by performing peak detection on a result value of the MUSIC estimator
Radar signal processing method comprising a.
A computer-readable recording medium having recorded thereon a program for executing the method of any one of claims 1 to 5.
A communication module for receiving a radar signal received by the target reflected in the search area; And
A processor which simultaneously estimates TOA and AOA of the target using the received radar signal
Including,
The processor,
A space-time covariance matrix is generated using the received radar signal, and a time delay of arrival (TOA) and a direction of arrival of the target are generated by using the generated spatial-temporal covariance matrix. Identify a steering vector for an angle of arrival (hereinafter referred to as AOA), perform a frequency conversion to which the steering vector of the identified TOA is applied to the received radar signal, and determine the TOA of the target, A radar signal processing apparatus for extracting an AOA of the target by applying a target TOA to a frequency detection algorithm.
The method of claim 7, wherein
The processor,
Stacking the received radar signals, and generating a space-time covariance matrix using the stacked radar signals.
The method of claim 7, wherein
The processor,
The eigenvalue decomposition (EVD) is used to decompose the generated spatiotemporal covariance matrix into a signal subspace matrix and a noise subspace matrix, and based on the direction vector of the target orthogonal to the noise subspace matrix. A radar signal processing apparatus for identifying a steering vector for a TOA and an AOA.
The method of claim 7, wherein
The processor,
Radar signal processing to determine a TOA of the target by performing a Discrete Fourier Transform (DFT) on the received radar signal and performing peak detection on the radar signal on which the DFT is performed Device.
The method of claim 7, wherein
The processor,
And applying the TOA of the determined target to a multiple signal classification (MUSIC) estimator and performing peak detection on a result value of the MUSIC estimator to extract the AOA of the target.

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