Radar device

Abstract

A radar device according to the present disclosure is an FMCW-type or fast chirp-type radar device comprising: a beat signal generation unit (8) that generates an I-axis local oscillation signal and a Q-axis local oscillation signal on the basis of a local oscillation signal that is a real signal, mixes the I-axis local oscillation signal and a received signal to generate an I-axis beat signal, and generates a Q-axis beat signal on the basis of the Q-axis local oscillation signal; mixing the Q-axis local oscillation signal and the reception signal to generate a Q-axis beat signal; and a signal processing unit (16) for performing signal processing on I-axis digital data and Q-axis digital data obtained by sampling the I-axis beat signal and the Q-axis beat signal, the signal processing unit (16) generating complex digital data from the I-axis digital data and the Q-axis digital data, performing two-dimensional FFT on the complex digital data, and performing signal processing on the complex digital data. And measuring the distance and Doppler velocity of the observation object according to the property that the analysis signal does not have the negative frequency component.

Description

Technical Field

[0001] The disclosed technology relates to a radar device. Background Art

[0002] There are known radar devices mounted on vehicles. In addition, regarding radar devices mounted on vehicles, there are known techniques for suppressing radio wave interference of radar signals with other vehicles.

[0003] For example, Patent Document 1 describes the following technique: a camera that captures an area including the direction in which a radar signal is transmitted, and based on the lighting state of the lights of other vehicles included in the image captured by the camera, the transmission intervals of the own vehicle and other vehicles are made different from each other.

[0004] In addition, Patent Document 1 also discloses that the fast chirp method is advantageous for separating and detecting multiple targets.

[0005] Prior Art Documents

[0006] Patent Documents

[0007] Patent Document 1: Japanese Unexamined Patent Application Publication No. 2016-224024 Summary of the Invention

[0008] Problems to be Solved by the Invention

[0009] In the existing radar device exemplified in Patent Document 1, in order to suppress radio wave interference, it is necessary to set a time when no radar signal is transmitted to observe electromagnetic noise.

[0010] An object of the disclosed technology is to provide a radar device that can suppress interference caused by electromagnetic noise without setting a so-called "radar radiation rest period" in which the transmission of radar signals is stopped to observe electromagnetic noise.

[0011] Means for Solving the Problems

[0012] The radar device of the disclosed technology is a radar device of the FMCW method or the fast chirp method, and the radar device includes: a beat signal generation unit that generates an I-axis local oscillation signal and a Q-axis local oscillation signal based on a local oscillation signal that is a real signal, mixes the I-axis local oscillation signal and the received signal to generate an I-axis beat signal, and mixes the Q-axis local oscillation signal and the received signal to generate a Q-axis beat signal; and a signal processing unit that performs signal processing on I-axis digital data and Q-axis digital data obtained by sampling the I-axis beat signal and the Q-axis beat signal, the signal processing unit generates complex digital data based on the I-axis digital data and the Q-axis digital data, performs FFT on the complex digital data, and measures the distance and Doppler velocity of the observation object based on the property that the analysis signal does not have a negative frequency component.

[0013] Advantages of the Invention

[0014] Since the radar device of the present disclosure has the above structure, it is possible to suppress interference caused by electromagnetic noise without providing a radar radiation pause period. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a block diagram showing the structural elements of the radar device according to Embodiment 1.

[0016] Figure 2 It is a block diagram showing the detailed structure of the signal processing unit 16 in the radar device according to Embodiment 1.

[0017] Figure 3 It is a flowchart showing the processing steps implemented by the signal processing unit 16 in the radar device according to Embodiment 1.

[0018] Figure 4 It is a diagram explaining the processing content implemented by the signal processing unit 16 in the radar device according to Embodiment 1.

[0019] Figure 5 It is a block diagram showing the detailed structure of the signal processing unit 16 in the radar device according to Embodiment 2.

[0020] Figure 6 It is a flowchart showing the processing steps implemented by the signal processing unit 16 in the radar device according to Embodiment 2.

[0021] Figure 7 It is a diagram explaining the processing content implemented by the signal processing unit 16 in the radar device according to Embodiment 2.

[0022] Figure 8 It is a block diagram showing the detailed structure of the signal processing unit 16 in the radar device according to Embodiment 3.

[0023] Figure 9 It is a flowchart showing the processing steps implemented by the signal processing unit 16 in the radar device according to Embodiment 3.

[0024] Figure 10 It is a diagram explaining the processing content implemented by the signal processing unit 16 in the radar device according to Embodiment 3.

[0025] Figure 11 It is a block diagram showing the detailed structure of the signal processing unit 16 in the radar device according to Embodiment 4.

[0026] Figure 12 It is a flowchart showing the processing steps implemented by the signal processing unit 16 in the radar device according to Embodiment 4.

[0027] Figure 13This is a diagram showing the processing content implemented by the signal processing unit 16 in the radar device of Embodiment 4. Detailed Embodiment

[0028] In this specification, the name "〇〇 unit" represents the unit of each structural element when the radar device of the present disclosed technology is divided into structural elements. That is, the name "〇〇 unit" in this specification does not represent the division of business organizations such as government agencies or companies, nor does it represent the collection of peers in club activities or community activities. The units and methods shown in this specification are mainly for the mechanical radar device and do not intend to be mainly for humans. That is, the units and methods shown in this specification are not only using methods based on human agreements.

[0029] Embodiment 1

[0030] Figure 1 This is a block diagram showing the structural elements of the radar device of Embodiment 1. As Figure 1 shown, the radar device of Embodiment 1 includes a radar signal output unit 1, a transceiver unit 4, a beat signal generation unit 8, an I-axis ADC 14, a Q-axis ADC 15, and a signal processing unit 16.

[0031] The radar signal output unit 1 includes a control unit 2 and a signal source 3.

[0032] The transceiver unit 4 includes a distribution unit 5, a transmitting antenna 6, and a receiving antenna 7.

[0033] The beat signal generation unit 8 includes a 90-degree phase shifter 9, an I-axis frequency mixing unit 10, a Q-axis frequency mixing unit 11, an I-axis filter unit 12, and a Q-axis filter unit 13.

[0034] The radar device of Embodiment 1 is connected to each functional block as Figure 1 shown.

[0035] 《Radar Signal Output Unit 1》

[0036] The radar signal output unit 1 is a structural element that outputs a radar signal. The radar signal output by the radar signal output unit 1 is a signal in the FMCW (Frequency Modulated - Continuous Wave) method or the fast chirp method (FCM method: Fast Chirp Modulation). In the fast chirp method, modulation is performed at a period much shorter than the modulation period of the FMCW method, and only either the modulation with frequency increase or the modulation with frequency decrease is used. That is, in the fast chirp method, one waveform of the transmitted wave with a sawtooth wave-like frequency change becomes one chirp (for example, refer to Figure 4(the curve shown in the upper layer). In the fast chirp mode, the modulation period is very short. Therefore, the frequency change caused by the Doppler effect is considered small enough to be negligible. Furthermore, in the fast chirp mode, malfunction caused by the pairing process in the FMCW mode can be solved. Therefore, it has received wide attention in recent years. In short, the radar device of the present disclosed technology is not a pulsed radar but a CW radar (Continuous Wave radar).

[0037] If a generalized expression is used, the radar signal output by the radar signal output unit 1 is a frequency modulation signal whose frequency changes over time and is output intermittently and repeatedly. As Figure 1 shown, the radar signal output from the radar signal output unit 1 is sent to the distribution unit 5 of the transceiver unit 4.

[0038] 《Control Unit 2 in Radar Signal Output Unit 1》

[0039] The control unit 2 in the radar signal output unit 1 is a structural element that generates a control signal. The control signal generated by the control unit 2 determines, for example, the output timing of the radar signal. As Figure 1 shown, the control signal output from the control unit 2 is sent to the signal source 3 and the signal processing unit 16.

[0040] 《Signal Source 3 in Radar Signal Output Unit 1》

[0041] The signal source 3 in the radar signal output unit 1 is a structural element that serves as the source of the radar signal. As described above, the radar signal generated from the signal source 3 is sent to the distribution unit 5 of the transceiver unit 4.

[0042] 《Transceiver Unit 4》

[0043] The transceiver unit 4 is a structural element having a transmission system for radar signals and a reception system for reflected signals from a target as an object to be observed. As described above, the transceiver unit 4 has a distribution unit 5, a transmission antenna 6, and a reception antenna 7.

[0044] 《Distribution Unit 5 in Transceiver Unit 4》

[0045] The distribution unit 5 in the transceiver unit 4 is a structural element that distributes the radar signal into a signal for transmission and a signal for reference. In this specification, the radar signal for transmission is also referred to as the "radar signal". In addition, in this specification, the radar signal for reference is referred to as the "local oscillation signal".

[0046] The radar signal for transmission is sent to the transmission antenna 6.

[0047] The radar signal for reference, that is, the local oscillation signal, is sent to the frequency mixer 10 for the I axis and is sent to the frequency mixer 11 for the Q axis via the 90-degree phase shifter 9.

[0048] Transmitting Antenna 6 in Transceiver Unit 4

[0049] The transmitting antenna 6 in transceiver unit 4 is an antenna that radiates radar signals into space such as the atmosphere.

[0050] Receiving Antenna 7 in Transceiver Unit 4

[0051] The receiving antenna 7 in transceiver unit 4 is an antenna that receives the radar signal reflection wave reflected by the object to be observed. In this specification, the signal received by the receiving antenna 7 in the radar signal reflection wave is only referred to as the "received signal". As Figure 1 shown, the received signal received by the receiving antenna 7 is sent to the frequency mixer 10 for the I-axis and the frequency mixer 11 for the Q-axis.

[0052] Beat Signal Generation Unit 8

[0053] The beat signal generation unit 8 is a structural element that generates a beat signal. The beat signal is a signal generated by mixing a local oscillation signal and a received signal. The frequency of the beat signal, i.e., the beat frequency, contains information about the distance to the target and the relative speed of the target. When considering the radar irradiation direction, the distance to the target gives the relative position of the target observed from the radar device.

[0054] When the radar signal output by the radar signal output unit 1 alternately uses both the up-chirp and the down-chirp, two pieces of information, namely, the beat frequency (f up ) of the up-chirp from the increasing FM gradient and the beat frequency (f down ) of the down-chirp from the decreasing FM gradient, are obtained. When the radar signal output by the radar signal output unit 1 is in the fast chirp mode, only one beat frequency is obtained.

[0055] One of the technical features of the radar device of the present disclosure is that a so-called IQ conversion is performed on the beat signal as a real signal to generate a complex signal composed of an I-axis beat signal and a Q-axis beat signal. The I-axis (In-Phase axis) is the so-called in-phase. The Q-axis (Quadrature axis) is the quadrature phase. A signal in the complex signal that does not have a negative frequency component is called an analytic signal.

[0056] In the technical field of radar, a detection method called quadrature detection or IQ detection is generally known. Quadrature detection uses two oscillators, namely, a local oscillator (LO: Local Oscillator) with high frequency stability and a coherent oscillator (CO: Coherent Oscillator). First, the received signal and the signal from the local oscillator (equivalent to the signal source 3 of the present disclosure technology) are down-converted to an intermediate frequency (IF: Intermediate Frequency, hereinafter referred to as "IF frequency") band near their difference component through a mixer (equivalent to the I-axis frequency mixing unit 10 of the present disclosure technology). Then, the down-converted signal passes through an amplifier and a BPF (equivalent to the I-axis filter unit 12 of the present disclosure technology) designed near the IF frequency band. The above operations are called frequency conversion or heterodyne detection. Then, by mixing the in-phase component and the quadrature component with the coherent oscillator (zero-difference detection), the in-phase component and the quadrature component of the received signal are extracted.

[0057] The radar device of the present disclosure technology can also perform heterodyne detection and zero-difference detection using two oscillators, namely, a local oscillator (LO) and a coherent oscillator (CO). The present disclosure technology obtains not only the amplitude information but also the phase information from the received signal that has been made complex.

[0058] 《90-degree Phase Shifter 9 in Beat Signal Generation Unit 8》

[0059] The 90-degree phase shifter 9 in the beat signal generation unit 8 is a structural element that gives a 90-degree phase difference (phase lead or phase delay) to the local oscillation signal. The purpose of giving a 90-degree phase difference to the local oscillation signal is to generate an analysis signal of the local oscillation signal. If the I-axis is considered as the real axis in the complex plane and the Q-axis is considered as the imaginary axis in the complex plane, the Q-axis is 90 degrees ahead in phase relative to the I-axis. For simplicity, in this specification, the 90-degree phase shifter 9 gives a 90-degree phase lead. That is, the 90-degree phase shifter 9 takes the local oscillation signal of the I-axis (hereinafter referred to as "I-axis local oscillation signal") as input and outputs the local oscillation signal of the Q-axis (hereinafter referred to as "Q-axis local oscillation signal"). The 90-degree phase shifter 9 can also be implemented as a Hilbert Filter.

[0060] Since the angular frequency of the chirp signal changes with time, it is difficult to imagine an operation such as "90 degrees ahead in phase". The chirp signal can be represented by complex numbers as follows, for example.

[0061]

[0062] Here, j represents the imaginary unit. A is the amplitude of the chirp signal.

[0063] It can be considered that the real part of g shown in Equation (1) is a real signal and is a local oscillation signal. If complex representation is used, the "90-degree phase lead" desired by the present disclosure technology means generating the imaginary part of g from the real part of g chirp (t). chirp (t). chirp (t).

[0064] In addition, whether the 90-degree phase shifter 9 gives a 90-degree phase lead or a 90-degree phase delay to the local oscillation signal is not essential.

[0065] The radar device of the present disclosure technology can also consider the local oscillation signal as the Q axis, which is a real signal, and use the 90-degree phase shifter 9 to generate the signal of the I axis. When the 90-degree phase shifter 9 gives a 90-degree phase delay, the input to the 90-degree phase shifter 9 is the Q-axis local oscillation signal, and the output of the 90-degree phase shifter 9 is the I-axis local oscillation signal.

[0066] "Frequency Mixing Unit 10 for I Axis in Beat Signal Generation Unit 8"

[0067] The frequency mixing unit 10 for the I axis in the beat signal generation unit 8 is a structural element that mixes the local oscillation signal and the received signal. The I-axis beat signal is generated in the frequency mixing unit 10 for the I axis.

[0068] The I-axis beat signal generated by the frequency mixing unit 10 for the I axis is sent to the filter unit 12 for the I axis.

[0069] "Frequency Mixing Unit 11 for Q Axis in Beat Signal Generation Unit 8"

[0070] The frequency mixing unit 11 for the Q axis in the beat signal generation unit 8 is a structural element that mixes the local oscillation signal with a 90-degree phase delay and the received signal. The Q-axis beat signal is generated in the frequency mixing unit 11 for the Q axis.

[0071] The I-axis beat signal generated by the frequency mixing unit 11 for the Q axis is sent to the filter unit 13 for the Q axis.

[0072] "Filter Unit 12 for I Axis in Beat Signal Generation Unit 8"

[0073] The filter unit 12 for the I axis in the beat signal generation unit 8 is a filter for the I-axis beat signal. Specifically, the filter unit 12 for the I axis is an LPF (Low Pass Filter) or a BPF (Band Pass Filter). The filter unit 12 for the I axis is used to suppress unnecessary components such as spurs from the I-axis beat signal just generated in the frequency mixing unit 10 for the I axis. Spurs are mainly composed of high frequencies and are unwanted frequency components included in the AC signal in terms of design.

[0074] "Q - axis Filter Section 13 in Beat Signal Generation Section 8"

[0075] The Q - axis filter section 13 in the beat signal generation section 8 is a filter for the Q - axis beat signal. Similar to the I - axis filter section 12, specifically, the Q - axis filter section 13 is an LPF (Low Pass Filter) or a BPF (Band Pass Filter). The Q - axis filter section 13 is used to suppress unwanted components such as spurs from the Q - axis beat signal just generated in the Q - axis frequency mixing section 11.

[0076] "I - axis ADC 14 and Q - axis ADC 15"

[0077] Specifically, the I - axis ADC 14 and the Q - axis ADC 15 are analog - to - digital converters.

[0078] The I - axis ADC 14 converts the I - axis beat signal, which is an analog signal, into I - axis digital data. The I - axis digital data is represented as follows.

[0079]

[0080] Here, \(i\) is shown in Equation (2) k is a real number, but strictly speaking, it is a value (such as double - type or float - type) after quantization of the real number. \(k\) in Equation (2) is the sampling number, taking integers from 1 to \(N\) _smpl of integers.

[0081] The Q - axis ADC 15 converts the Q - axis beat signal, which is an analog signal, into Q - axis digital data. The Q - axis digital data is represented as follows.

[0082]

[0083] Here, \(q\) is shown in Equation (3) k is a real number, but strictly speaking, it is a value (such as double - type or float - type) after quantization of the real number. \(k\) in Equation (3) is also the sampling number.

[0084] The I - axis digital data and the Q - axis digital data are collectively called IQ data. The IQ data is sent to the signal processing section 16.

[0085] "Signal Processing Section 16"

[0086] The signal processing section 16 is a structural element that performs signal processing for calculating the distance to the target and the relative speed of the target.

[0087] The signal processing unit 16 can determine the period during which the radar signal is output from the radar signal output unit 1 by referring to the control signal sent from the control unit 2. In this specification, the period during which the radar signal is output from the radar signal output unit 1 is referred to as the "specific period".

[0088] Figure 2 It is a block diagram showing the detailed structure of the signal processing unit 16 in the radar device of Embodiment 1.

[0089] As Figure 2 shown, the signal processing unit 16 in the radar device of Embodiment 1 includes a spectrum calculation unit 1610, a range-velocity spectrum calculation unit 1620, an electromagnetic noise spectrum calculation unit 1625, a range-velocity information calculation unit 1630, an electromagnetic noise information calculation unit 1635, and a detection processing unit 1650.

[0090] The signal processing unit 16 in the radar device of Embodiment 1 is connected to each functional block as Figure 2 shown.

[0091] Figure 3 It is a flowchart showing the processing steps implemented by the signal processing unit 16 in the radar device of Embodiment 1. As Figure 3 shown, the processing steps implemented by the signal processing unit 16 include ST11, ST12, ST13, ST14, ST15, and ST16. The details of each processing step will become clear from the following description.

[0092] "Spectrum Calculation Unit 1610 in Signal Processing Unit 16"

[0093] The spectrum calculation unit 1610 in the signal processing unit 16 is a structural element that performs a Fourier transform in the range direction (hereinafter referred to as "range Fourier transform") and calculates the frequency spectrum ( Figure 3 shown as ST11). Since the range Fourier transform is the first Fourier transform to be performed, it is sometimes also referred to as the first Fourier transform.

[0094] The spectrum calculation unit 1610 uses the digital data within the specific period to create the complex digital data given below.

[0095]

[0096] k in Equation (4) is also the sampling number.

[0097] More specifically, the spectrum calculation unit 1610 performs a range Fourier transform on the complex digital data shown in Equation (4). The result obtained through the range Fourier transform is called the frequency spectrum.

[0098] The data obtained from the result of the range Fourier transform is complex data in the frequency domain. In an ideal situation without noise, the frequency at which the peak is taken in the frequency domain is the beat frequency. The peak in the frequency domain (spectral peak) is also complex, but the Doppler frequency can be calculated based on the phase information of the spectral peak. In order to calculate the Doppler frequency based on the phase information of the spectral peak, the following Doppler Fourier transform is implemented.

[0099] The beat signal is repeatedly generated, and the spectral calculation unit 1610 performs the range Fourier transform each time.

[0100] The multiple spectra calculated by the spectral calculation unit 1610 are sent to the range velocity spectrum calculation unit 1620 and the electromagnetic noise spectrum calculation unit 1625.

[0101] 《Range Velocity Spectrum Calculation Unit 1620 in Signal Processing Unit 16》

[0102] The range velocity spectrum calculation unit 1620 in the signal processing unit 16 is a structural element that performs the Fourier transform in the relative velocity direction (hereinafter referred to as "Doppler Fourier transform") and calculates the range velocity spectrum ( Figure 3 ST12 shown). Since the Doppler Fourier transform is the second Fourier transform, it is sometimes also referred to as the second Fourier transform.

[0103] The range velocity spectrum calculation unit 1620 performs the Doppler Fourier transform on the positive frequency domain (hereinafter referred to as "positive region spectrum data") in the spectrum data. That is, the result obtained by performing the Doppler Fourier transform on the positive region spectrum data is called the range velocity spectrum.

[0104] In addition, the fast Fourier transform is called FFT (Fast Fourier Transform). The radar device of the present disclosed technology can perform the range Fourier transform and the Doppler Fourier transform in the form of range FFT and Doppler FFT. The information obtained by performing both the range FFT and the Doppler FFT operations is two-dimensional (refer to Figure 4 , Figure 7 and Figure 10 ), so it is also called two-dimensional FFT.

[0105] As Figure 2 shown, the range velocity spectrum is sent to the range velocity information calculation unit 1630.

[0106] 《Electromagnetic Noise Spectrum Calculation Unit 1625 in Signal Processing Unit 16》

[0107] The electromagnetic noise spectrum calculation unit 1625 in the signal processing unit 16 is a structural element that performs the Doppler Fourier transform and calculates the electromagnetic noise spectrum ( Figure 3 ST13 shown).

[0108] The electromagnetic noise spectrum calculation unit 1625 performs a Doppler Fourier transform on the negative frequency domain in the spectrum data (hereinafter referred to as "negative region spectrum data"). That is, the result obtained by performing a Doppler Fourier transform on the negative region spectrum data is called the electromagnetic noise spectrum.

[0109] As Figure 2 shown, the electromagnetic noise spectrum is sent to the electromagnetic noise information calculation unit 1635.

[0110] "Range-Velocity Information Calculation Unit 1630 in Signal Processing Unit 16"

[0111] The range-velocity information calculation unit 1630 in the signal processing unit 16 is a structural element that calculates the distance to the target and the relative velocity of the target ( Figure 3 ST14 shown) from the range-velocity spectrum.

[0112] More specifically, the range-velocity information calculation unit 1630 detects the peak of the range-velocity spectrum and calculates the beat frequency and Doppler frequency based on the peak. The beat frequency gives the distance to the target, and the Doppler frequency gives the Doppler velocity of the target.

[0113] The information on the beat frequency and Doppler frequency calculated in the range-velocity information calculation unit 1630, or the information on the distance to the target and the Doppler velocity of the target, is sent to the detection processing unit 1650.

[0114] "Electromagnetic Noise Information Calculation Unit 1635 in Signal Processing Unit 16"

[0115] The electromagnetic noise information calculation unit 1635 in the signal processing unit 16 is a structural element that calculates the frequency and Doppler frequency originating from electromagnetic noise ( Figure 3 ST15 shown) from the electromagnetic noise spectrum.

[0116] More specifically, the electromagnetic noise information calculation unit 1635 detects the peak of the electromagnetic noise spectrum and calculates the frequency and Doppler frequency originating from electromagnetic noise based on the peak.

[0117] The information on the frequency and Doppler frequency originating from electromagnetic noise calculated in the electromagnetic noise information calculation unit 1635 is sent to the detection processing unit 1650.

[0118] "Detection Processing Unit 1650 in Signal Processing Unit 16"

[0119] The detection processing unit 1650 in the signal processing unit 16 is a structural element that suppresses the influence of electromagnetic noise and detects the reasonable relative position and relative velocity related to the target ( Figure 3 ST16 shown). As Figure 2As shown, the processing performed by the detection processing unit 1650 is performed based on the information transmitted from the distance velocity information calculation unit 1630 and the information transmitted from the electromagnetic noise information calculation unit 1635.

[0120] Figure 4 FIG. is a diagram for explaining the processing content performed by the signal processing unit 16 in the radar device according to Embodiment 1.

[0121] In Figure 4 In the curve graph shown in the upper layer, {L O (1), L O (2), …, L O (K)} is a local oscillation signal. In Figure 4 In the curve graph shown in the upper layer, the horizontal axis represents time and the vertical axis represents frequency. In Figure 4 , as the local oscillation signal, a downward chirp is illustrated. The sweep time of one chirp signal is represented by “T” and is on the order of μs (microseconds). The frequency band of the chirp signal is represented by “BW”.

[0122] In Figure 4 In the curve graph shown in the upper layer, {R X (1), R X (2), …, R X (K)} is a received signal.

[0123] Figure 4 K in

[0124] In Figure 4 In the curve graph shown in the upper layer, the electromagnetic noise is shown by a dashed line. In this specification, for simplicity, it is assumed that the electromagnetic noise is a continuous wave with a constant frequency. Further, it is assumed that the electromagnetic noise directly enters the ADC 14 for the I axis and the ADC 15 for the Q axis. Furthermore, it is assumed that the electromagnetic noise entering the ADC 14 for the I axis and the electromagnetic noise entering the ADC 15 for the Q axis have no correlation with each other. Generally, since the ADC 14 for the I axis and the ADC 15 for the Q axis are arranged at different positions on the substrate, it is possible to assume that the entering noises have no correlation.

[0125] In Figure 4 , the plurality of rectangles marked with the description “signal acquisition timing” are the periods within the specific period and are the periods during which the beat frequency can be acquired. The signal processing unit 16 acquires a signal at this signal acquisition timing.

[0126] Figure 4 The three grid-like curve graphs shown in the right column of

[0127] Figure 4 In the two-dimensional FFT lattice diagram shown, the vertical axis represents the beat frequency (distance), and the horizontal axis represents the Doppler frequency (relative velocity). In addition, as a curve graph showing the result of the two-dimensional FFT, there is also a curve graph in which the horizontal axis takes the beat frequency and the vertical axis takes the Doppler frequency.

[0128] For the sake of simplicity of explanation, in Figure 4 the exemplified two-dimensional FFT lattice diagram, the part corresponding to the observation object (target) and the part corresponding to the electromagnetic noise (false detection) are each filled in one place.

[0129] In Figure 4 the part denoted as "FFT(1)" represents the range FFT. The beat frequency (F sb_r ) that can be obtained through the range FFT satisfies the following relational expression.

[0130]

[0131] Here, Δf represents the frequency difference between the upper limit and the lower limit of the frequency band (BW) (also referred to as the "maximum frequency offset width"), R represents the distance, c represents the speed of light, and T represents the scanning time (or chirp period). In addition, in Equation (5), it is assumed that the modulation period is very short, and the term related to the Doppler frequency is not recorded. In addition, in "F sb_r ", the subscript sb_r in sb_r is the first character of signalbeat, and r is the first character of range.

[0132] In Figure 4 below the part denoted as "FFT(1)", vertically long rectangles with dimensions of N _smpl ×1 are shown respectively. In each rectangle, there are three filled parts. The filled parts represent the positions of the peaks of the spectrum. That is, in Figure 4 the example, there are three spectrum peaks.

[0133] In each rectangle, the second part from the top among the filled parts represents the position corresponding to the beat frequency (F sb_r ) shown in Equation (5).

[0134] As described above, the analyzed signal does not have a negative frequency component. Moreover, the complex signal related to the ideal beat signal without noise is the analyzed signal.

[0135] In Figure 4 the vertically long rectangle shown, from the middle upwards (numbered 1 to N _smpl / 2) represents the positive frequency domain. In addition, in the vertically long rectangle, from the middle downwards (numbered (N _smpl / 2)+1 to N _smpl) represents the negative frequency domain. In addition, the exact middle position of the rectangle indicated by the dashed line is the position where the beat frequency is 0. In the time domain, the sampling numbers 1 to N are marked in the order of the passage of time. However, in the frequency domain, the numbers 1 to N are marked in the direction from the larger side of the positive frequency towards the negative frequency. _smpl The sampling numbers are 1 to N, but in the frequency domain, the numbers 1 to N are marked in the direction from the larger side of the positive frequency towards the negative frequency. _smpl The numbering.

[0136] It is indicated by being filled in the 4th position counted upwards from the exact middle of the rectangle, but it represents the spectral peak originating from the reflected wave caused only by the target. The spectral peak originating from the reflected wave caused only by the target appears as the result of the frequency analysis of the analysis signal, and thus does not have a negative frequency component. Therefore, in Figure 4 it is filled in the 4th position counted upwards from the exact middle of the rectangle, but it is not filled in the 4th position counted downwards from the exact middle of the rectangle. This indicates that according to the steps or methods of the present disclosure technology, the signal reflected by the target does not generate a spectral peak in the negative frequency domain.

[0137] In the case of performing a Fourier transform on a real signal instead of a complex signal, spectral peaks appear symmetrically not only in the positive frequency domain but also in the negative frequency domain. Therefore, for example, when electromagnetic noise enters either the ADC14 for the I-axis or the ADC15 for the Q-axis, if a Fourier transform is performed on the electromagnetic noise signal, spectral peaks appear in both the positive frequency domain and the negative frequency domain.

[0138] In Figure 4 In the vertical rectangle shown, the uppermost peak and the lowermost peak at symmetric positions represent the spectral peaks caused by electromagnetic noise.

[0139] In Figure 4 In the example shown, for K consecutive chirp signals, a beat signal is obtained at the signal acquisition timing K times, and a range FFT is performed K times.

[0140] In Figure 4 The part indicated as "FFT(2)" in sb_v represents the Doppler FFT performed by the range-velocity spectrum calculation unit 1620. The Doppler frequency (F sb_v ) satisfies the following relational expression.

[0141]

[0142] Here, f represents the center frequency of the local oscillation signal, and v represents the relative velocity of the target observed from the radar device. Strictly speaking, v represents the velocity component in the radar radiation direction among the relative velocities of the target observed from the radar device. Generally, the velocity component that generates the Doppler effect in the velocity of an object is called the Doppler velocity. Therefore, v in Equation (6) is the Doppler velocity of the target. In addition, "F sb_vIn the subscript sb_v, sb is the first character of signalbeat, and v is the first character of velocity.

[0143] Figure 4 The top two-dimensional FFT grid diagram in the illustrated two-dimensional FFT grid diagram shows the result of the Doppler FFT performed by the range-velocity spectrum calculation unit 1620. In this two-dimensional FFT grid diagram, in addition to illustrating that the Doppler frequency of the observed object (i.e., the target) is 0, the Doppler frequency of the electromagnetic noise (false detection) is also illustrated as a value corresponding to the second grid to the right from 0.

[0144] exist Figure 4 The portion indicated as "FFT (3)" in FIG. 1 represents the Doppler FFT performed by the electromagnetic noise spectrum calculation unit 1625. Figure 4 As illustrated, the electromagnetic noise spectrum calculation unit 1625 may perform a process of inverting the sign of the data related to the negative frequency domain obtained by the range FFT to a positive one, and then perform the Doppler FFT.

[0145] Figure 4 The second two-dimensional FFT grid diagram from the top of the illustrated two-dimensional FFT grid diagram shows the result of Doppler FFT performed by the electromagnetic noise spectrum calculation unit 1625. In this two-dimensional FFT grid diagram, the Doppler frequency of electromagnetic noise (false detection) is also illustrated as a value corresponding to the second grid from 0 to the right.

[0146] It can be said Figure 4 The third two-dimensional FFT lattice diagram from the top of the illustrated two-dimensional FFT lattice diagram is obtained by subtracting the second two-dimensional FFT lattice diagram from the top two-dimensional FFT lattice diagram. The third two-dimensional FFT lattice diagram from the top represents information obtained by the processing result of the detection processing unit 1650.

[0147] One of the technical features of the radar device of Embodiment 1 is that it includes a 90-degree phase shifter 9 that gives a 90-degree phase difference (phase advance or phase delay) to a local oscillation signal. With this configuration, the radar device of Embodiment 1 generates an I-axis beat signal and a Q-axis beat signal.

[0148] From another perspective, the technical feature of the radar device according to the first embodiment is that signal processing is performed using the principle that “the analysis signal does not have a negative frequency component”.

[0149] As described above, the radar apparatus according to the first embodiment has the effect of eliminating the need for a radar radiation quiescent period for observing only electromagnetic noise.

[0150] Implementation Method 2

[0151] The radar device of Embodiment 2 is a modified example of the radar device of the present disclosure technology. In Embodiment 2, unless otherwise specifically stated, the same reference numerals as those used in Embodiment 1 are used. In addition, in Embodiment 2, the descriptions overlapping with those in Embodiment 1 are appropriately omitted.

[0152] Figure 5 It is a block diagram showing the detailed structure of the signal processing unit 16 in the radar device of Embodiment 2.

[0153] The Figure 5 and Figure 2 Comparing with (Embodiment 1), in Embodiment 2, the signal processing unit 16 uses the electromagnetic noise spectrum calculation unit 1625B as a structural element instead of the electromagnetic noise spectrum calculation unit 1625. Information from the distance-velocity information calculation unit 1630 is input to the electromagnetic noise spectrum calculation unit 1625B.

[0154] Figure 6 It is a flowchart showing the processing steps implemented by the signal processing unit 16 in the radar device of Embodiment 2.

[0155] The Figure 6 and Figure 3 Comparing with (Embodiment 1), in Embodiment 2, the signal processing unit 16 implements ST21 after ST14 instead of ST13.

[0156] Figure 7 It is a diagram for explaining the processing content implemented by the signal processing unit 16 in the radar device of Embodiment 2.

[0157] The Figure 7 and Figure 4 Comparing with (Embodiment 1), in Embodiment 2, the electromagnetic noise spectrum calculation unit 1625B performs Doppler FFT only on specific data where the spectrum peak is located, rather than on the entire negative frequency domain. Specifically, the specific data where the spectrum peak is located is the data related to the negative beat frequency corresponding to the beat frequency of the spectrum peak generated in the positive frequency domain.

[0158] Taking the Figure 7 example, the beat frequencies of the spectrum peaks generated in the positive frequency domain are the 4th grid from the center upward and the 11th grid from the center upward. Therefore, the electromagnetic noise spectrum calculation unit 1625B performs a process of reversing the sign to positive on the data related to the negative frequency domain obtained by range FFT, and performs Doppler FFT only for the 4th grid from the origin upward and the 11th grid from the center upward. That is, the electromagnetic noise spectrum calculation unit 1625B of Embodiment 2 performs Doppler FFT restrictively for the required range (ST21 shown in Figure 6 ).

[0159] The technical feature of the radar device according to Embodiment 2 is that, based on the technical features of the radar device according to Embodiment 1, the electromagnetic noise spectrum calculation unit 1625B performs Doppler FFT in a limited manner for a required range.

[0160] As described above, the radar device according to Embodiment 2 exhibits the effect of minimizing the number of times of Doppler FFT to be performed, based on the effects described in Embodiment 1.

[0161] Embodiment 3

[0162] The radar device according to Embodiment 3 is a modified example of the radar device of the present disclosure technology. In Embodiment 3, unless otherwise specifically stated, the same reference numerals as those used in the above-described embodiments are used. In addition, in Embodiment 3, descriptions that are repetitive with the above-described embodiments are appropriately omitted.

[0163] Briefly speaking, the technical feature unique to the radar device according to Embodiment 3 is to determine whether the I-axis beat signal and the Q-axis beat signal actually measured by sampling become the real part and the imaginary part of an ideal analysis signal.

[0164] Figure 8 It is a block diagram showing the detailed structure of the signal processing unit 16 in the radar device according to Embodiment 3.

[0165] As Figure 8 shown, the signal processing unit 16 in the radar device according to Embodiment 3 includes a spectrum calculation unit 1610, a range-velocity spectrum calculation unit 1620B, a range-velocity information calculation unit 1640, a detection processing unit 1650B, an amplitude-phase calculation unit 1660, and a cancellation constant calculation unit 1670.

[0166] The signal processing unit 16 in the radar device according to Embodiment 3 is connected to each functional block as Figure 8 shown.

[0167] Figure 9 It is a flowchart showing the processing steps performed by the signal processing unit 16 in the radar device according to Embodiment 3. As Figure 9 shown, the processing steps performed by the signal processing unit 16 according to Embodiment 3 include ST11, ST31, ST32, ST33, ST34, and ST35. The details of each processing step will become clear from the following description.

[0168] Figure 10 It is a diagram for explaining the processing content performed by the signal processing unit 16 in the radar device according to Embodiment 3. As Figure 10 shown, the signal processing unit 16 in the radar device according to Embodiment 3 performs range FFT only for the I-axis beat signal (in Figure 10Shown as "FFT(I)") and the range FFT only for the Q-axis beat signal (in Figure 10 Shown as "FFT(Q)").

[0169] "Amplitude and Phase Calculation Unit 1660 in Signal Processing Unit 16"

[0170] The amplitude and phase calculation unit 1660 in the signal processing unit 16 is a structural element that performs range FFT on the I-axis beat signal and the Q-axis beat signal respectively and calculates the amplitude ratio and phase difference for each range bin.

[0171] The result of the range FFT for the I-axis beat signal is represented as follows, for example.

[0172]

[0173] Here, the handwritten F represents the operation of Fourier transform. In addition, as described above, the left side of Equation (7) in the time domain is labeled 1 to N in the order of time passage _smpl of the sampling numbers. On the other hand, the right side of Equation (7) in the frequency domain is labeled 1 to N in the direction from +∞ to -∞ of the frequency _smpl of the numbers. The numbers 1 to N in the frequency domain _smpl are also the numbers for identifying the range bins.

[0174] Similarly, the result of the range FFT for the Q-axis beat signal is represented as follows.

[0175]

[0176] The amplitude ratio and phase difference for each range bin calculated by the amplitude and phase calculation unit 1660 are represented as follows.

[0177]

[0178] Equation (9) is the amplitude ratio and phase difference of the I-axis beat signal observed from the Q-axis beat signal. The absolute value notation appearing in Equation (9) represents the magnitude of the complex number (the distance to the origin in the complex plane). In addition, the notation representing the angle appearing in Equation (9) represents the argument of the complex number. Also, in Figure 10 , the magnitude of the complex number is represented by "A_", and the argument of the complex number is represented by "θ_". In addition, in Figure 10 the example of, the amplitude ratio and phase difference for each range bin are shown by arrows as calculated at the initial signal acquisition timing, however, the technology of the present disclosure is not limited thereto. The amplitude and phase calculation unit 1660 of Embodiment 3 may also perform statistical calculations (for example, find the average value or the median value) based on the information obtained from multiple beat signals, and find the amplitude ratio and phase difference for each range bin.

[0179] If the I-axis beat signal and the Q-axis beat signal actually measured by sampling are the real part and the imaginary part of an ideal analysis signal, then regarding the amplitude ratio and the phase difference of each range bin shown in Equation (9), in all range bins, the amplitude ratio is 1, and in all range bins, the phase difference is -90 degrees.

[0180] The amplitude ratio and the phase difference of each range bin are sent to the cancellation constant calculation unit 1670.

[0181] "Cancellation Constant Calculation Unit 1670 in Signal Processing Unit 16"

[0182] The cancellation constant calculation unit 1670 in the signal processing unit 16 is a structural element that calculates the cancellation constant (weight) for canceling the component caused by electromagnetic noise for each range bin.

[0183] Whether the I-axis beat signal and the Q-axis beat signal actually measured by sampling become the real part and the imaginary part of an ideal analysis signal can be confirmed, for example, by the following equation.

[0184]

[0185] Here, ε (epsilon) that appears in Equation (10) is a threshold value that determines what degree of error is allowed. The W given by Equation (10) k is the cancellation constant (weight) for canceling the component caused by electromagnetic noise. For simplicity, in this specification, let N _smpl be an even number. When the I-axis beat signal and the Q-axis beat signal actually measured by sampling are close to the real part and the imaginary part of an ideal analysis signal, the conditional expression of the norm given by the right side of Equation (10) is satisfied, and W k becomes 0. On the contrary, when the I-axis beat signal and the Q-axis beat signal actually measured by sampling are far from the real part and the imaginary part of an ideal analysis signal, the conditional expression of the norm given by the right side of Equation (10) is not satisfied, and W k becomes 1.

[0186] Briefly speaking, the conditional expression of the norm shown in Equation (10) compares I k with the value obtained by multiplying Q k by -j. Multiplying Q k by -j is equivalent to delaying the phase of Q k by 90 degrees and converting it into a form that can be compared with the original I k .

[0187] By applying the ideal analysis signal exemplified below, the meaning of Equation (10) becomes clear.

[0188]

[0189] When performing a Fourier transform on the ideal analysis signal shown in logarithmic formula (11) with cos(ω0t) as the fundamental wave, at an angular frequency of ω0, the I-axis becomes 1 + 0j and the Q-axis becomes 0 + j. Thus, in formula (10), when the k-th distance corresponds to ω0, the conditional formula for the norm given by the right side of formula (10) is calculated as follows.

[0190]

[0191] In this way, in the case of an ideal analysis signal, the conditional formula for the norm given by the right side of formula (10) is satisfied.

[0192] The cancellation constant (weight, W k ) calculated by the cancellation constant calculation unit 1670 does not need to be the "binary value of 0 or 1" shown in formula (10). The cancellation constant (weight, W k ) calculated by the cancellation constant calculation unit 1670 can also take values other than binary values, for example, as given by the following formula.

[0193]

[0194] As described above, electromagnetic noise sometimes enters either the I-axis ADC 14 or the Q-axis ADC 15. In a certain k, in the axis where electromagnetic noise does not enter, it cannot be said that the case where the Fourier transform result becomes 0 does not occur at all. Formula (13) divides the two norms given by formula (10) by the two norms of I k or the two norms of Q k to perform so-called normalization. In formula (13), to avoid division by zero, the cases of dividing by the two norms of I k and the cases of dividing by the two norms of Q k are shown in two cases.

[0195] Formula (13) gives the normalized cancellation constant (weight, W k ), however, the radar device of the present disclosure is not limited to this. The radar device of the present disclosure can also use the non-normalized cancellation constant (weight, W k ).

[0196] The radar device of the present disclosure can also directly extract the range bin related to the target using the conditional formula for the norm given by formula (10).

[0197]

[0198] It can be said that the range bin where T k given by formula (14) is 1 is not interference caused by electromagnetic noise, but the range bin related to the target (refer to Figure 10of the two-dimensional FFT lattice diagram).

[0199] "Range-Velocity Spectrum Calculation Unit 1620B in Signal Processing Unit 16"

[0200] The range-velocity spectrum calculation unit 1620B in the signal processing unit 16 performs Doppler Fourier transform and calculates the range-velocity spectrum in the same way as the range-velocity spectrum calculation unit 1620 ( Figure 9 shown in ST33). However, different from the range-velocity spectrum calculation unit 1620, the object of the Doppler Fourier transform performed by the range-velocity spectrum calculation unit 1620B can be only the range bin where T k given by Equation (14) is 1.

[0201] In addition, as Figure 10 shown, the range-velocity spectrum calculation unit 1620B can also use the cancellation constant (weight, W k ) calculated by the cancellation constant calculation unit 1670 to eliminate the influence of electromagnetic noise, and then perform Doppler Fourier transform.

[0202] As described above, the technical feature unique to the radar device of Embodiment 3 is that, using the conditional expression of the norm given by the right side of Equation (10), it is determined whether the I-axis beat signal and the Q-axis beat signal actually sampled and measured become the real part and the imaginary part of the analysis signal.

[0203] By having such a technical feature, the radar device of Embodiment 3, on the basis of the effects described in Embodiment 1 and Embodiment 2, exhibits the effect of being able to eliminate the influence of interference caused by electromagnetic noise from the result of the two-dimensional FFT.

[0204] Embodiment 4

[0205] The radar device of Embodiment 4 is a modified example of the radar device of the present disclosed technology. In Embodiment 4, unless otherwise specifically stated, the same reference numerals as those used in the above-described embodiments are used. In addition, in Embodiment 4, the descriptions repeated from the above-described embodiments are appropriately omitted.

[0206] Figure 11 is a block diagram showing the detailed structure of the signal processing unit 16 in the radar device of Embodiment 4.

[0207] Comparing Figure 11 with Figure 8 (Embodiment 3), it can be seen that in the signal processing unit 16 of Embodiment 4, the cancellation constant calculation unit 1670B is provided as a structural element instead of the cancellation constant calculation unit 1670. Information from the spectrum calculation unit 1610 is input to the cancellation constant calculation unit 1670B.

[0208] Figure 12 This is a flowchart showing the processing steps implemented by the signal processing unit 16 in the radar device of Embodiment 4.

[0209] By comparing with Figure 12 (Embodiment 3), it can be seen that the signal processing unit 16 in Embodiment 4 implements ST41 instead of ST32. Figure 9 (Embodiment 3), it can be seen that the signal processing unit 16 in Embodiment 4 implements ST41 instead of ST32.

[0210] Figure 13 This is a diagram for explaining the processing content implemented by the signal processing unit 16 in the radar device of Embodiment 4. More specifically, Figure 13 The illustrated curve graph represents the frequency spectrum calculated by the spectrum calculation unit 1610. The horizontal axis in the curve graph is the distance proportional to the beat frequency (displayed as "Distance" in Figure 13 ), with the unit of [m]. The vertical axis in the curve graph is the relative power of the spectrum (displayed as "Relative Power" in Figure 13 ). In the illustrated curve graph of Figure 13 , the dashed line represents the positive region spectrum data, and the solid line represents the negative region spectrum data by inverting the sign of the frequency axis.

[0211] In the illustration of Figure 13 , the spectrum peak that appears near a distance of 10 [m] appears only in the positive region spectrum data and is an example of a peak caused by a target. In contrast, the spectrum peak that appears near a distance of 50 [m] appears in both the positive region spectrum data and the negative region spectrum data and is an example of a peak caused by electromagnetic noise. In addition, in the illustration of Figure 13 , near a distance of 40 [m], a spectrum peak appears only in the negative region spectrum data, but this is an example of a secondary peak.

[0212] The spectrum calculation unit 1610 calculates the frequency spectrum by performing a distance FFT on the complex digital data shown in the logarithmic formula (4). However, this frequency spectrum can be expressed as follows, for example.

[0213]

[0214] Here, the left side of Equation (15) is the complex digital data in the time domain, but is labeled with the subscript numbers 1 to N _smpl in the order of time. The right side of Equation (15) is the frequency spectrum {S1,..., S N_sampl} shown in the frequency domain, but is labeled with the subscript numbers 1 to N _smpl in the direction from the larger side of the positive frequency towards the negative frequency.

[0215] "Elimination Constant Calculation Unit 1670B in Signal Processing Unit 16"

[0216] The cancellation constant calculation unit 1670B in the signal processing unit 16 is a structural element that calculates a cancellation constant (weight) for canceling out components caused by electromagnetic noise for each range bin, in the same manner as the cancellation constant calculation unit 1670.

[0217] The cancellation constant calculation unit 1670B may also calculate the cancellation constant (weight, W k ) according to the following conditional expression instead of the conditional expression shown in Equation (10).

[0218]

[0219] The ε that appears in the conditional expression of Equation (16) is a threshold value represented by the dashed line indicated as the "judgment threshold" in the Figure 13 curve graph.

[0220] The technical feature unique to the radar device of Embodiment 4 is that the magnitude of the spectrum obtained by range FFT is compared with a threshold value (refer to Equation (16)).

[0221] By having such a technical feature, the radar device of Embodiment 4 exhibits the same effects as those described in the above-mentioned embodiments.

[0222] Embodiment 5

[0223] The radar device of Embodiment 5 is a modified example of the radar device of the present disclosed technology. In Embodiment 5, unless otherwise specifically stated, the same reference numerals as those used in the above-mentioned embodiments are used. In addition, in Embodiment 5, descriptions that are repetitive with the above-mentioned embodiments are appropriately omitted.

[0224] The peak signals caused by electromagnetic noise in the spectrum obtained by performing range Fourier transform on the complex digital data are divided into the positive frequency domain and the negative frequency domain, and are given by the following equations.

[0225]

[0226] Among them, P on the left side of Equation (17) + represents the peak signal in the positive frequency domain, A represents the amplitude ratio of the I signal and the Q signal, θ1 represents the initial phase of the I signal, and θ2 represents the initial phase of the Q signal.

[0227]

[0228] Among them, P on the left side of Equation (18) - is the peak signal in the negative frequency domain.

[0229] The disclosed technology can also perform the following processing: by multiplying the complex conjugate of P− given by Equation (18) by a cancellation constant (C), the peak signal (P + ) in the positive frequency domain is eliminated. The conditional expression that the cancellation constant (C) should satisfy is given as follows.

[0230]

[0231] Here, the overbar accent mark in Equation (19) indicates the complex conjugate.

[0232] The technical feature unique to the radar device of Embodiment 5 is that the complex conjugate of the peak signal (P - ) in the negative frequency domain is multiplied by the cancellation constant (C) given by Equation (19).

[0233] By having such a technical feature, the radar device of Embodiment 5 exhibits the same effects as those described in the above-mentioned embodiments.

[0234] Industrial Applicability

[0235] The radar device of the disclosed technology can be applied to, for example, in-vehicle millimeter-wave radars and has industrial applicability.

[0236] Reference Signs Description

[0237] 1: Radar signal output unit; 2: Control unit; 3: Signal source; 4: Transceiver unit; 5: Distribution unit; 6: Transmitting antenna; 7: Receiving antenna; 8: Beat signal generation unit; 9: 90-degree phase shifter; 10: Frequency mixing unit for I-axis; 11: Frequency mixing unit for Q-axis; 12: Filter unit for I-axis; 13: Filter unit for Q-axis; 14: ADC for I-axis; 15: ADC for Q-axis; 16: Signal processing unit; 1610: Spectrum calculation unit; 1620, 1620B: Range-velocity spectrum calculation units; 1625, 1625B: Electromagnetic noise spectrum calculation units; 1630: Range-velocity information calculation unit; 1635: Electromagnetic noise information calculation unit; 1640: Range-velocity information calculation unit; 1650, 1650B: Detection processing units; 1660: Amplitude-phase calculation unit; 1670, 1670B: Cancellation constant calculation units.

Claims

1. A radar device, which is a radar device in the FMCW mode or the fast chirp mode, wherein, The radar device has: a beat signal generation unit that generates an I-axis local oscillation signal and a Q-axis local oscillation signal based on a local oscillation signal that is a real signal, mixes the I-axis local oscillation signal and a received signal to generate an I-axis beat signal, and mixes the Q-axis local oscillation signal and the received signal to generate a Q-axis beat signal; and a signal processing unit that performs signal processing on I-axis digital data and Q-axis digital data obtained by sampling the I-axis beat signal and the Q-axis beat signal, wherein the signal processing unit generates complex digital data based on the I-axis digital data and the Q-axis digital data, performs FFT on the complex digital data, and measures the distance and Doppler velocity of an observation object based on the property that the analysis signal does not have a negative frequency component.

2. The radar device according to claim 1, wherein the signal processing unit has a distance-velocity information calculation unit and an electromagnetic noise spectrum calculation unit, the distance-velocity information calculation unit calculates the relative position and relative velocity of a target based on a distance-velocity spectrum, when the beat frequencies corresponding to one or more distances are calculated by the distance-velocity information calculation unit, the electromagnetic noise spectrum calculation unit calculates the Doppler frequency corresponding to the relative velocity only for the data corresponding to the beat frequencies.

3. The radar device according to claim 1, wherein the radar device further has: an amplitude-phase calculation unit that performs distance FFT on the I-axis digital data and the Q-axis digital data respectively; and an elimination constant calculation unit that calculates, for each range bin, an elimination constant for eliminating the component caused by electromagnetic noise based on the processing result of the amplitude-phase calculation unit.

4. The radar device according to claim 3, wherein The cancellation constant is W given by the following equation k , Among them, 1 to N _smpl / 2 is the number of the range bin in the positive frequency domain, and ε is the threshold value that determines the allowable error.

5. The radar device according to claim 3, wherein The cancellation constant is W given by the following equation k , where 1 to N _smpl / 2 is the number of the range bin in the positive frequency domain.

6. The radar device according to claim 3, wherein The cancellation constant is the W given by the following formula k , Among them, 1 to N _smpl / 2 is the number of range bins in the positive frequency domain, and S k is the spectrum obtained by performing a Fourier transform on the complex digital data.

7. The radar device according to claim 3, wherein the elimination constant is C given by the following formula where P + is the peak signal in the positive frequency domain, and P - is the peak signal in the negative frequency domain. The cancellation constant cancels P by multiplying with the complex conjugate of P - and cancels P + .

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