JP2012247304A - Method and device for detection of peak power spectrum of short-time signal - Google Patents

Abstract

PROBLEM TO BE SOLVED: To enhance frequency resolution while enhancing resolution in a time range to be measured, in detection of peak power spectrum by Fourier transform.SOLUTION: A method for detecting a peak power frequency within an intended duration in a temporally-changing signal includes: a sampling step of sampling a signal within the intended duration and determining it as a digital data column; an addition step of setting a sample number required in fast Fourier transform to satisfy required frequency resolution as a reference sample number and adding zero data to the digital data column so as to reach the reference sample number; and an FFT step of applying the fast Fourier transform to the zero-data-added digital data column. A frequency showing a maximum value in a result of the fast Fourier transform is detected as a peak power frequency.

Description

  The present invention relates to a method and apparatus for extracting a portion within a desired time width from a signal that changes according to time and detecting a peak power spectrum of the signal in the extracted portion, and in particular, speeding up detection. It is related with the method and apparatus which improved the frequency accuracy of the spectrum detected, aiming at.

  It will be described later that only a portion having a desired time width is cut out from a signal having a predetermined frequency bandwidth and changes every moment, and the peak power spectrum of the signal in the cut portion is detected. For example, it is widely used in Doppler measurement. The desired time width here is sufficiently short when compared with the duration of the entire signal. For example, the start time is given or the start time can be automatically detected. Further, the detected peak power spectrum has the strongest power spectrum in the frequency spectrum of the signal in the cut out portion. For the detection of the power spectrum, Fourier transform is generally used, and FFT (Fast Fourier Transform) is used from the viewpoint of calculation amount.

  By the way, when a signal is emitted (transmitted) into a medium and a signal (echo signal) reflected from the medium is received, if the transmitted time is the start time, the echo signal from the start time is received until the echo signal is received. Is dependent on the propagation distance of the signal in the medium, that is, the distance to the object. Therefore, in consideration of the propagation speed of a signal (the speed of sound in the case of sound waves), an echo signal received when a desired time has elapsed from the start time is from an object located at a distance corresponding to the elapsed time. It becomes an echo signal. Application devices that display the intensity of the echo signal as an image according to the time (that is, distance) from the start time are, for example, a radar and a fish finder.

  Assuming that the object that reflects the signal is relatively moving, a frequency shift from the transmitted frequency is observed in the reflected echo due to the Doppler effect. This frequency difference, that is, the difference between the frequency when transmitted to the medium and the frequency observed by the reflected echo is called the Doppler frequency. In Doppler measurement, a signal having a constant frequency is emitted into a medium, a signal reflected by an object in the medium (reflection echo) is received, and the frequency analysis is performed to determine the Doppler frequency. Examples of Doppler measurements include Doppler radar, Doppler sonar, ADCP (acoustic Doppler current profiler), tide meter, sonic radar, and ultrasonic Doppler velocimeter, which are based on Doppler frequency. To determine the relative speed with the object.

A signal having a constant transmission frequency f _tx is generated by the transmission circuit, and this signal is emitted from the transducer to the medium. Assuming that the object (reflector) is moving in the medium, the Doppler frequency f _dop has the moving speed of the object as V (m / s) and the propagation speed of the signal in the medium as C (m / s). Then, when the propagation speed of the signal in the medium is sufficiently faster than the speed of the object (C >> V), it is expressed by the following approximate expression.

Here, θ is an angle formed by the direction when the transducer is viewed from the object and the moving direction of the object, and if the direction is the same (when the object is moving straight toward the transducer) ), Θ = 0. Accordingly, the Doppler frequency f _dop is positive (+) when the object is approaching, and is negative (−) when the object is moving away.

A frequency analysis of the echo signal is performed to obtain a Doppler frequency f _dop , and a Fourier transform method is generally used for this frequency analysis. As the Fourier transform, when performing power spectrum analysis, DFT (Discrete Fourier Transform) is used, or when the number of signal samples (number of samples) is a power of 2, high-speed arithmetic processing is possible. FFT (Fast Fourier Transform) is usually used. Both DFT and FFT repeat complex multiplication operations. If the number of samples is N, the number of complex multiplications in the DFT is N × N times (that is, N ² times), and N = 2 ⁿ , The number of complex multiplications in the FFT is 2 ⁿ × log ₂ 2 ⁿ times (that is, N × log ₂ N times), and the higher the N, the faster the FFT can perform operations compared to the DFT.

  By the way, in Doppler measurement, it is often desirable to acquire information on both the position and speed of an object. For example, in order to obtain the flow velocity profile by obtaining the direction and velocity of the tidal current at each depth in the ocean, a reflected echo is obtained by emitting a sound pulse in an oblique direction with respect to the ocean, and frequency analysis is performed. At this time, the reflected echo is cut out at a certain time width after a lapse of a predetermined time from the emission of the sound wave pulse, and frequency analysis is performed on the cut out portion. The depth of flow to be measured is determined by the predetermined time after the sound wave is emitted, and the flow velocity as an average over the depth range (thickness) is determined by the time width when the reflected echo is cut out. Whether or not is calculated is determined. For example, if the time width at the time of cutting is large, an average flow velocity in a thick layer in the sea is obtained. On the other hand, if the time width is small, it is possible to obtain the flow velocity in a thin layer, and as a result, a fine flow velocity profile is obtained.

  However, a problem of Fourier transform as frequency analysis for obtaining the Doppler frequency is that the frequency resolution and the time (distance) resolution are in a contradictory relationship. Here, the frequency resolution is a resolution for obtaining the Doppler frequency, and is proportional to the resolution of the speed. The time resolution refers to how far the time width can be reduced when extracting the reflected echo, which is proportional to the distance or position resolution in Doppler measurement. If the time resolution is rough, in the case of the above-described flow velocity profile, only a rough average flow velocity in a layer having a large thickness in the depth direction can be obtained.

  The discrete Fourier transform (DFT) is expressed by the following equation.

When the sampling frequency in DFT or FFT is f _ft and the period of the fundamental wave of Fourier transform is T ₀ , the reciprocal of the period is called the fundamental frequency f _{0 in} Fourier transform,
f ₀ = 1 / T _0: Equation 1-4
It is expressed. The fundamental frequency f ₀ is the minimum resolution frequency in DFT or FFT, that is, the frequency resolution. If the total number of sampled signal points, ie the number of samples, is N,
T ₀ = N / f _ft : Formula 1-5
Of course, and the minimum resolution frequency f ₀ , which is the frequency resolution, is
_{f 0 = 1 / T 0 =} f ft / N: Equation 1-6
Will be expressed. Conversely, given the desired frequency resolution f ₀ , the required number of samples N is
N = f _ft / f ₀ : Formula 1-7
Will be expressed. In the Fourier transform, N samples are extracted at equal intervals from a signal having a time width equal to the period T _{0 of the} fundamental wave, so that T ₀ is a signal cutting time (cutting time width).

An example of a power spectrum obtained by FFT is shown in FIG. The power spectrum of the FFT is expressed as a spectrum in which values 14 and 15 are given for each frequency at a constant frequency interval from 0 to (N / 2) −1 with respect to the number N of samples. Here frequency interval is consistent with the above f _0, a f ₀ = 1 / T _0.

As shown in Equation 1-4, the frequency resolution f _0, since the reciprocal of the cut-out duration T ₀ of the signal, in order to increase the frequency resolution (the lower f _0), the signal of the cut time width T ₀ Must be lengthened. As a result, if the frequency resolution is made twice as fine, the time resolution, that is, the position (distance) resolution becomes twice as coarse and deteriorates.

The Doppler frequency f _dop changes depending on the relative speed with the object. _Assuming that the range in which the Doppler frequency f _fop changes is Δf _p , assuming that the movement in the approaching direction and the moving away direction occur equally (this process is a reasonable assumption in applications such as tidal current meters). The center frequency f _c of the frequency range Δf _P of the Doppler signal, that is, the frequency of the received signal when the Doppler frequency f _dop is zero matches the transmission frequency f _tx (f _c = f _tx ).

  Consider a case where an ultrasonic pulse signal is transmitted into the sea under the following conditions and the Doppler frequency of a reflected echo from a moving object is measured.

Sound wave velocity in seawater C: C = 1500 (m / s)
Transmission frequency f _tx : f _tx = 120 kHz
Maximum detection speed (horizontal direction) V: V = 15 (m / s)
It is assumed that sound waves are transmitted and received in the oblique direction (θ = 60 °) from the horizontal direction. From equation 1-1:

Next, if the detection maximum speed is 15 m / s, the frequency range Delta] f _p which is observed as Doppler signal is a 120 ± 1.2 (kHz).

  Since the measurement speed range, that is, the maximum detection speed is usually determined in advance, the frequency range of the Doppler signal is also determined in advance and measured.

If the speed accuracy by Doppler measurement is 0.1 m / s, the frequency resolution f ₀ required for this is 12 Hz. Assuming that the range (position resolution) of a position to be detected in Doppler measurement is 7.5 m, the signal extraction time width is multiplied by 2/1500 (m / s), which is the time for a sound wave to reciprocate 1 m in seawater. 7.5 × 2/1500 = 0.01, which is 10 ms.

However, if 12 Hz, which is the frequency resolution f ₀ , is substituted into Equation 1-4, T ₀ = 1 / f ₀ = 1 / 12≈83.3 ms, and 83.3 ms is the time required for the sound wave to reciprocate 1 m in seawater. When converted to a distance by dividing by 2/1500 (m / s), 83.3 (ms) × 1500 (m / s) /2≈62.5 (m).

That is, if the frequency resolution f _{0 is set} to 12 Hz in order to set the speed accuracy to 0.1 m / s, 83 ms is required as the signal extraction time width, which corresponds to 63 m in terms of distance, and the position (distance ) Cannot satisfy the requirement for a resolution of 7.5 m. On the other hand, if FFT is performed with a signal having a position-related resolution of 7.5 m, the frequency resolution f ₀ is 100 Hz according to Equation 1-4, and the request for the frequency resolution of 12 Hz determined from the speed accuracy cannot be satisfied.

  As described above, the Fourier transform has a basic problem that the frequency resolution and the time resolution related to the measurement target are not compatible. In the case of Doppler measurement, this is the frequency resolution or velocity resolution and the distance or position. This means that the resolution is not compatible.

FIG. 2 shows an example of the configuration of a general Doppler measuring device. Here, it is assumed that the signal is an acoustic signal and the medium through which the signal propagates is water (or seawater). The acoustic signal transmitter / receiver 1 is connected to the output of the transmission circuit 3 and the input of the reception amplifier 4 via a transmission / reception switching circuit 2. The transmission circuit 3 generates a signal having a transmission frequency f _tx . The output of the reception amplifier 4 is provided with a modulator 5 that converts the received signal into an intermediate frequency signal. A signal having a local oscillation frequency f _loc is supplied from the local oscillation circuit 6 to the modulator 5. . An output of the modulator 5, that is, an intermediate frequency signal, is supplied to an analog / digital converter (A / D) 10 through an analog filter 7 to be converted into a digital signal, and this digital signal has a predetermined number of samples (that is, time). Is supplied to a signal cut-out gate 11 that cuts out a signal by width). The signal cut out by the signal cut-out gate 11 is then sent to the FFT processing unit 13 and subjected to frequency analysis by FFT. The calculated power spectrum is output from the FFT processing unit 13.

In this Doppler measuring device, when a sound wave pulse is emitted in water, a signal having a transmission frequency f _tx is supplied from the transmission circuit 3 to the transmitter / receiver 1 via the transmission / reception switching circuit 2. Immediately thereafter, the transmission / reception switching circuit 2 is set as the reception side, the reflected echo from the medium (underwater) is received by the transducer 1 and converted into a reception signal which is an electrical signal, and the reception signal is received via the transmission / reception switching circuit 2. This is supplied to the amplifier 4. As a result, the received signal is amplified by the receiving amplifier 4 and supplied to the modulator 5.

FIG. 3 shows a relationship between frequencies such as a received signal and an intermediate frequency signal. It is assumed that the signal itself output from the receiving amplifier 4 has a frequency band as indicated by reference numeral 52 in FIG. Band of the received signal is part of a frequency band indicated by reference numeral 52, the Doppler signal to be detected is within the frequency range Delta] f _p indicated by reference numeral 51. The center of the frequency range Δf _p , that is, the frequency f _c (47) when the Doppler frequency is zero is the same as the transmission frequency f _tx (f _c = f _tx ). The local oscillation circuit 6 generates a local oscillation signal having a local oscillation frequency f _loc (45) lower than the frequency f _c by the intermediate frequency f _mid (that is, f _c > f _loc ), and supplies it to the modulator 5. As a result, the modulator 5 multiplies the received signal by the local oscillation signal to convert the received signal into an intermediate frequency signal having the intermediate frequency f _mid .

Of the frequency band of the received signal, if the upper limit of the frequency range Δf _p of interest for topler measurement is the upper limit frequency f _max (49) and the lower limit is the lower limit frequency f _min (48), the frequency range to be Fourier transformed Δf _p (51) is represented by Δf _p = f _max -f _min.

Generation of the signal of the intermediate frequency f _mid in the modulator 5 is expressed by the following equation, and the lower frequency is obtained from the two conversion frequencies using a low-pass filter or a band-pass filter.

Frequency range Delta] f _p of the Doppler signal, centered on the intermediate frequency f _mid,

Will be transformed in the range, the frequency range Delta] f _p of the detection target is maintained even if the frequency converter. The above equation, <while indicating processing time of f _c, f _loc> f _loc even when f _c, only decoding (code (±)) is reversed, the same processing is performed .

In FIG. 3, the right portion represents the relationship between the received signal and the local oscillation signal, where f _mid (46) satisfies the relationship of f _mid = f _c −f _loc . On the other hand, the left part of FIG. 3 shows the spectrum after being converted into the intermediate frequency signal, and here, the center frequency of the intermediate frequency signal is f _mid (50). The above-described frequency band 52 is also converted to the frequency band 54, and the frequency range Δf _p (51) to be detected is converted to the frequency range Δf _p (53) whose center frequency is f _mid .

FIG. 4 shows a case where a reflected echo is received by emitting a sound wave pulse from the observation ship in the direction of θ = 60 ° (direction directed downward 60 ° from the horizontal direction) in order to measure the flow velocity profile in the tidal current. An example of the received waveform is shown. In the figure, the horizontal axis represents time. Here, the reflected echo 16 is shown as a signal after being converted into an intermediate frequency signal. The large-amplitude signal 17 immediately after time 0 is due to the reception of the transmitted sound wave pulse itself by the transducer. A waveform 18 having a large amplitude indicates an echo reflected from the seabed (seafloor echo). In seabed echo, according to the ship speed of research ship, it includes Doppler shift in the frequency range of ± Δf _p / 2.

Here, it is assumed that the intermediate frequency f _mid (that is, the center frequency of the frequency-converted signal) is 5 kHz, and the sampling frequency in analog / digital conversion and the sampling frequency f _{ft in} FFT are 20 kHz. At this time, the number of samples N in the Fourier transform is N = f _ft / f ₀ = 20000 / 12≈1667 from Equation 1-7. However, assuming the use of FFT, the number of samples is a power of two. Therefore, the number of samples is N = 2 ¹¹ = 2048. When the number of samples N is 2048, the frequency resolution is f ₀ = 20000/2048 = 9.766 Hz from Equation 1-6, which is finer than the frequency resolution of 12 Hz corresponding to the speed accuracy of 0.1 m / s, Satisfies the requirements.

In FIG. 4, reference numeral 20 represents a time T ₀ required to acquire 2048 signal samples necessary for FFT, assuming that acquisition is started simultaneously with transmission of a sound wave pulse. FIG. 5 shows the result of performing FFT on the 2048 signal samples.

The spectrum shown in FIG. 5 includes the peak 38 located at the 512th in the FFT step and the peak 39 located around the 574th as prominent peaks, and the peak 38 is larger in intensity. The frequency obtained by multiplying the number of FFT steps by the frequency resolution f ₀ is the actual frequency. Here, f ₀ = 2000/2048 = 9.766 Hz, and therefore the frequency of the peak 38 is 9.766 Hz × 512 = 5000 Hz. Become. As described above, the center frequency f _mid in the intermediate frequency signal is 5 kHz, which matches the frequency converted signal of the transmission frequency, so that the peak 38 corresponds to the peak obtained by directly detecting the transmission wave. Further, when the same consideration is made, the peak 39 corresponds to a sea bottom echo, and the transmission frequency is a frequency that is Doppler shifted according to the ship speed. In the example shown here, since the sampling frequency f _ft = 20 kHz and the number of samples N = 2048, T ₀ = 102.4 ms from Equation 1-5. In terms of distance, this means that the location from the position of the transducer to the sea floor is collectively subject to FFT. As a result, the transmission signal itself having the highest power is detected as the peak power spectrum. That is, for an FFT input signal having a strong signal outside the desired time range, it is not possible to obtain the spectrum or frequency that is the peak power within the desired time range.

In FIG. 4, it is conceivable to perform FFT by shifting only the signal in the time range T ₁ (21) including only the peak 18 by shifting the transmission time of the sound wave pulse by the time t ₁ (22). Assuming that 128 samples are cut out and FFT is performed, the frequency resolution f ₀ is f ₀ = 20000 / 128≈156 Hz, which is 156 Hz different if the FFT step is shifted by 1 with a coarse accuracy. is there. This frequency resolution is extremely coarse compared to the required resolution of 12 Hz and cannot meet the requirements.

  For the sake of explanation, in FIG. 6, the spectrum is drawn with a continuous solid line, but since it is actually an analysis result by FFT, it is expressed as a discrete value for each FFT step, as shown in FIG. It is what is done.

In conventional Doppler measurement, when obtaining the peak power frequency within a desired time interval, first, the distance (time) resolution is prioritized, and the necessary range T ₁ is extracted from the received signal until the frequency resolution is coarse. Perform frequency analysis by FFT. Interpolate from the sampling point with the highest value in the analysis result, the sampling point with the next largest value, the sampling point with the next largest value, etc. by a method such as curve fitting that assumes the peak shape in the spectrum The method of estimating a true peak power frequency by performing was used. Because of interpolation, the true peak power frequency can be calculated with a finer resolution than the frequency resolution in FFT.

  However, in such a conventional method, a circuit and an estimation algorithm for obtaining the peak power frequency by interpolation become complicated, and as a result, it is necessary to spend calculation power for processing other than FFT, and the calculation speed is reduced. It was a factor of cost increase. Moreover, since frequency estimation is performed after FFT, there is also a problem that measurement accuracy is likely to deteriorate.

  Patent Document 1 discloses a signal processing method that increases the frequency resolution while reducing the number of calculation points in FFT.

WO2006 / 043511

  As described above, when Fourier transform is applied to Doppler measurement or the like, improvement of frequency resolution and improvement of resolution with respect to time (or distance) of a range to be measured are incompatible with each other. Problems arise from basic problems. In order to avoid this problem, the signal is cut out in a desired short time width and then FFT is performed. Various interpolation methods and estimation methods are applied to the FFT result, and the frequency interval discretized by FFT is used. Although the frequency of the peak power is also finely determined, this leads to an increase in the configuration and complexity of the algorithm, which leads to a decrease in calculation speed and an increase in cost. Furthermore, when these interpolation methods and estimation methods are used, there is a problem that desired frequency accuracy cannot always be obtained.

  An object of the present invention is to provide a detection method and apparatus capable of solving the above-described basic problems in Fourier transform and increasing the frequency resolution while increasing the resolution of the time range to be measured.

  The detection method of the present invention is a method for detecting a peak power frequency within a range of a desired time width in a time-varying signal, wherein the signal is sampled within the desired time width to obtain a digital data sequence. And an additional step of adding zero data to the digital data string so as to reach the reference sample number, with the number of samples required in the fast Fourier transform to satisfy the required frequency resolution as the reference sample number, and zero data An FFT stage that performs fast Fourier transform on the digital data sequence to which is added, and detects a frequency showing a maximum value in the result of the fast Fourier transform as a peak power frequency.

  The detection device of the present invention is a device for detecting a peak power frequency within a desired time width in a time-varying signal, and sampling means for sampling the signal within a desired time width to obtain a digital data string And zero adding means for adding zero data to the digital data string so as to reach the reference sample number, with the number of samples required in the fast Fourier transform to satisfy the required frequency resolution as the reference sample number, and zero FFT means for performing a fast Fourier transform on a digital data sequence to which data is added.

  In the present invention, instead of obtaining the peak power frequency by interpolation or estimation from the FFT result with coarse frequency resolution, the FFT is performed after adding zero data so that a desired frequency resolution can be obtained. The peak power frequency can be directly obtained from the FFT with a desired frequency resolution without performing interpolation or estimation. Since the present invention does not require a complicated circuit or algorithm, the peak power frequency can be obtained with a simple configuration, low cost, high accuracy, and high speed.

It is a graph which shows the frequency spectrum analysis result by FFT. It is a block diagram which shows an example of a structure of a Doppler measuring device. It is a spectrum figure explaining conversion etc. to the intermediate frequency of a received signal. It is a wave form diagram which shows an example of the received waveform of the reflective echo when an acoustic signal is transmitted in the sea in the diagonal direction. It is a figure which shows an example of the frequency spectrum analysis result of the reflective echo containing a transmission signal. It is a figure which shows the frequency spectrum analysis result by FFT when there are few input samples. It is a block diagram which shows the structure of the peak power spectrum detection apparatus of one Embodiment of this invention. It is a wave form diagram explaining the input signal to FFT.

  FIG. 7 shows a configuration of a Doppler measurement device suitable for implementing the peak power spectrum detection method according to the embodiment of the present invention. This Doppler measuring device is an example of a peak power spectrum detection device based on the present invention.

  The Doppler measuring device shown in FIG. 7 is obtained by inserting a zero adding unit 12 between the signal cut-out gate 11 and the FFT processing unit 13 in the Doppler measuring device shown in FIG. The signal cut-out gate 11 outputs a digital data string obtained by sampling and digitizing a signal corresponding to the time range to be measured. The zero adding unit 12 is used to satisfy the required frequency resolution. The number of samples required in FFT is used as a reference sample number, and zero data is added to the digital data string so as to reach this reference sample number. Details of processing in the zero adding unit 12 will be described later.

The Doppler measurement apparatus shown in FIG. 7, in the same manner as shown in FIG. 2, by using the modulator 5 and the local oscillator 6, low-frequency frequency range Delta] f _p above in the received signal at the transducer 1 Frequency conversion on the side. This is because in order to perform FFT in order to detect a high frequency component, it is necessary to increase the sampling frequency, and the number of samples becomes too large for the higher sampling frequency. For Doppler measurements, for example, may be detected Doppler frequency in the frequency range of 120kHz ± 1.2 (kHz), since the frequency range Delta] f _p to be a detection target are determined, lowering the sampling frequency in the FFT In this embodiment, the received signal is frequency-converted into an intermediate frequency signal having a frequency lower than the original frequency in order to reduce the number of samples within a necessary resolution range. As shown by the like above equations 2-1 to 2-3, even in an intermediate frequency signal after the frequency conversion, the frequency range Delta] f _p is maintained.

  An analog filter 7 is provided to extract only the intermediate frequency component on the low frequency side from the output of the modulator 5 and to prevent aliasing from occurring in the subsequent analog / digital conversion. The analog / digital converter (A / D) 10 samples the output of the analog filter 7 at a sampling frequency at which FFT can be performed, and performs analog / digital conversion. As a result, the A / D converter 10 outputs a digital data string composed of digital values representing instantaneous values in the intermediate frequency signal. The signal cut-out gate 11 cuts out a digital data string in a desired time range. The number of samples of the extracted data is defined as the number of cut samples. The zero adding unit 12 calculates the number of FFT samples corresponding to the required frequency resolution as the reference sample number, and the number of zeros corresponding to the difference between the reference sample number and the cut sample number so as to reach the reference sample number. Data (sample with a value of zero) is added to the extracted digital data string. Then, the FFT processing unit 13 performs FFT on the digital data string in which zero data is added and the number of samples is the reference number of samples, and calculates a peak power spectrum. The calculated peak power spectrum is for the range cut out by the signal cut-out gate 11 and indicates the peak power frequency in the time range of the signal. In addition, by adding zero data, the time width to be subjected to FFT in the signal is substantially expanded, and the reciprocal of this time width corresponds to the frequency resolution, so the frequency resolution is improved. . As described above, according to the present embodiment, the peak power spectrum in a desired time range (or distance range) in the received signal can be detected by satisfying the desired frequency accuracy only by the FFT calculation. .

  Hereinafter, the frequency resolution in this embodiment will be described by giving numerical examples.

Consider a case where an ultrasonic pulse signal is transmitted into the sea under the same conditions as described in the background art section, and the Doppler frequency of a reflected echo from a moving object is measured. That is, the sound wave propagation speed C in seawater is C = 1500 (m / s), the transmission frequency f _tx is f _tx = 120 kHz, the maximum detection speed (horizontal direction) V is V = 15 (m / s), It is assumed that sound waves are transmitted and received in a diagonal direction (θ = 60 °) from the horizontal direction.

At this time, the Doppler signal is in the range of 120 ± 1.2 (kHz), and if the speed accuracy is required to be 0.1 m / s, the frequency resolution f ₀ is 12 Hz. In addition, the range (position resolution) of the position to be detected in Doppler measurement is 7.5 m, the center frequency of the signal after frequency conversion, that is, the intermediate frequency f _mid (50) is 5 kHz, and the sampling frequency in analog / digital conversion. And the sampling frequency f _{ft of} FFT is 20 kHz.

When obtaining the T ₀ required from the frequency resolution f _0, the _{T 0 = 1 / f 0 =} 1/12 ≒ 83.3ms.

In FIG. 4 which shows the waveform after emitting a sound wave pulse in the sea, observing the received signal, and converting the received signal into an intermediate frequency signal, reference numeral 16 represents a reflected echo and reference numeral 17 represents transmission. The signal represents the signal itself, and reference numeral 18 represents a seabed echo. Consider a case where the frequency of the seafloor echo 18 is analyzed and the speed of the ship is obtained from the Doppler frequency based on Formula 1-1. Here, in order to prevent unnecessary signals such as transmission signals from being included, only the seafloor echo 18 is cut out and subjected to FFT to obtain the Doppler frequency for the reflected wave from the seabed. FIG. 8 shows a signal 19 obtained by cutting out only the sea bottom echo from the signal waveform shown in FIG. Here, it is assumed that the time width T ₂ (24) is cut out after the elapse of time t ₂ (26) from the transmission of the sound wave pulse as the portion of the seabed echo 19. The signal cut out here is 100 samples.

The frequency resolution f ₀ when the Fourier transform is performed using only 100 samples of the time width T ₂ is f ₀ = 20000 Hz / 100 = 200 Hz, and does not satisfy the required frequency resolution of 12 Hz.

Here, when the number N of samples necessary for the Fourier transform to satisfy the required frequency resolution of 12 Hz is obtained, N = f _ft / f ₀ = 20000 / 12≈1667 from Expression 1-7. Since 1667 is not a power of 2, considering the power of 2 that is closest to 1667 beyond 1667, 2 ¹¹ = 2048 is found. Therefore, when 2048 is adopted as the number of samples N in the FFT, the frequency resolution f ₀ is f ₀ = 20000 Hz / 2048 = 9.766 Hz from Equation 1-6, which satisfies the requirements.

Therefore, in this embodiment, it is assumed that FFT is executed with the number of samples N = 2048, and the number of samples of the signal 19 of the sea bottom echo is 100. Therefore, for the insufficient 1948 samples, samples having zero values are inserted. . In FIG. 8, T ₀ (23) is a time corresponding to 2048 samples and is a time width to be subjected to FFT analysis.

Here, the relationship of T ₀ = T ₂ + T ₃ holds, and the duration of the zero value signal added so as to satisfy the number N of samples necessary for FFT analysis by cutting out the signal 19 in the range to be measured is T _3. It will correspond to. The insertion position of the time width T ₃ may be before or after the time width T _2, that is, the extracted signal 19. Alternatively, the time width T ₀ (27) for FFT analysis may be set by arranging a time width for inserting the zero value signal by dividing the signal 19 before and after the signal 19 therebetween.

In the example shown here, the elapsed time t ₂ (symbol 26 in FIG. 8) and the time width T ₂ (symbol 24 in FIG. 8) from the transmission of the sound wave pulse to the start of signal clipping are determined in advance. If a reflected echo having a high intensity such as a sea bottom echo is to be detected, it is possible to automatically detect and determine the elapsed time t ₂ until the cutout and the time width T _{2 of the} cutout. When obtaining the flow velocity of the tidal current at each depth, automatic detection cannot be performed, and t ₂ and T ₂ are set in advance.

  Here, addition of zero value data by the zero addition unit 12 will be described.

In general, in FFT, the target number of samples needs to be a power of two. On the other hand, the number of samples in the target data to be analyzed by FFT is often not a power of two. Therefore, adding zero data samples so that the number of samples is a power of 2 is called zero padding. In that case, it is sufficient that the number of samples is enough to perform the FFT anyway. Therefore, when the number of samples of the target data is N _{s and} there is a natural number m satisfying 2 ^m−1 <N _s ≦ 2 ^m , 2 ^m -N _s zero value data will be added. On the other hand, in the present embodiment, zero value data is not added so that the FFT can be executed, but the zero value is obtained so that a desired frequency resolution can be obtained in consideration of the sampling frequency f _ft in the FFT. Append data. Therefore, the number of zero value data added may be much larger than simply allowing the FFT to be performed. In the above-described example, assuming that the number of samples is 100 by cutting out the sea bottom echo, if only to execute FFT, 2 ⁷ = 128, so only 28 zero-value data need be added. However, 1948 zero-value data are added to satisfy the desired frequency resolution.

  As described above, the preferred embodiment of the present invention has been described by taking the detection of the Doppler frequency in the reflected echo as an example, but the scope of application of the present invention is not limited to this. The present invention is widely and generally applicable when a portion of a short time range is cut out from a signal that can assume a frequency range to be detected and analyzed by FFT. For example, the present invention can be applied to the case where the signal is converted into a signal in a desired frequency band through a filter such as a band pass filter, and then the signal is detected by cutting out a short time signal.

DESCRIPTION OF SYMBOLS 1 Transmitter / receiver 2 Transmission / reception switching circuit 3 Transmission circuit 4 Reception amplifier 5 Modulator 6 Local oscillation circuit 7 Analog filter 10 Analog / digital converter (A / D)
11 Signal Extraction Gate 12 Zero Addition Unit 13 FFT Processing Unit

Claims (7)

A method for detecting a peak power frequency within a desired time width in a time-varying signal, comprising:
A sampling step of sampling the signal within the desired time width into a digital data sequence;
An additional step of adding zero data to the digital data string so as to reach the reference sample number, with the number of samples required in the fast Fourier transform to satisfy the required frequency resolution as a reference sample number;
An FFT stage for performing a fast Fourier transform on the digital data sequence to which the zero data is added;
Have
A method of detecting a frequency showing a maximum value as a result of the fast Fourier transform as the peak power frequency.   The method according to claim 1, wherein the reference sample number is at least twice the number of samples of the digital data sequence obtained in the sampling step.   The signal has a predetermined frequency band, and includes a step of performing frequency conversion on the signal before the sampling step so that the predetermined frequency band is converted to a low frequency side. The method according to 1 or 2. An apparatus for detecting a peak power frequency within a desired time width in a time-varying signal,
Sampling means for sampling the signal within the desired time width into a digital data string;
Zero addition means for adding zero data to the digital data sequence so as to reach the reference sample number, with the number of samples required in the fast Fourier transform to satisfy the required frequency resolution as a reference sample number;
FFT means for performing a fast Fourier transform on the digital data sequence to which the zero data is added;
Having a device.   The apparatus according to claim 4, wherein the reference sample number is at least twice the number of samples of the digital data sequence obtained by the sampling means.   The sampling means includes an A / D converter that performs analog / digital conversion on the signal, and a signal cutout gate that cuts out a digital data string output from the A / D converter according to the desired time width. The device according to claim 4, comprising: The signal has a predetermined frequency band;
Furthermore, before the said sampling means, it has a frequency conversion means which performs a frequency conversion with respect to the said signal so that the said predetermined frequency band may be converted into the low frequency side. The device described.

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