JP2011099771A - Time information acquisition apparatus and radio-controlled timepiece - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To reduce the amount of calculation and the time for calculation, and to accurately acquire codes included in a standard time radio wave. <P>SOLUTION: An average value tracking circuit 19 removes a DC component from an input signal from a receiving circuit 16 and generates an output signal indicating either, with the average value of the input signal as the center, a larger value and a smaller value than the average value. A correlation value calculating unit 25 of a signal comparison circuit 18, without calculating the average value of input waveform data and the average value of predicted waveform data, calculates calculated values, by multiplying the data values of the input waveform data by the data values of the predicted waveform data, and calculates the sum of the calculated values as a correlation value, corresponding to the covariance value between the input waveform data and the predicted waveform data. For example, a CPU 11 determines a second head position in a time code, on the basis of the predicted waveform data indicative of an optimum value. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a time information acquisition device that receives a standard time radio wave and acquires the time information, and a radio clock equipped with the time information acquisition device.

  Currently, in Japan, Germany, the United Kingdom, Switzerland, etc., long standard time radio waves are transmitted from transmitting stations. For example, in Japan, standard time radio waves with amplitude modulation of 40 kHz and 60 kHz are transmitted from transmitting stations in Fukushima Prefecture and Saga Prefecture, respectively. The standard time radio wave includes a sequence of codes constituting a time code indicating the year, month, day, hour and minute, and is transmitted in one cycle of 60 seconds. That is, the period of the time code is 60 seconds.

  A timepiece (radio timepiece) capable of receiving a standard time radio wave including such a time code, taking out the time code from the received standard time radio wave, and correcting the time has been put into practical use. The reception circuit of the radio clock accepts the standard time radio wave received by the antenna and demodulates the standard time radio signal amplitude-modulated by a band pass filter (BPF) for extracting only the standard time radio signal, envelope detection, etc. A demodulation circuit and a processing circuit that reads a time code included in the signal demodulated by the demodulation circuit are provided.

  The conventional processing circuit synchronizes at the rising edge of the demodulated signal, and then binarizes at a predetermined sampling period to obtain TCO data of a unit time length (1 second) which is a binary bit string. Further, the processing circuit measures the pulse width of the TCO data (that is, the time of bit “1” or the time of bit “0”), and codes “P”, “0” corresponding to the width. "Or" 1 "is determined, and time information is acquired based on the determined code sequence.

  In a conventional processing circuit, a process of second synchronization processing, minute synchronization processing, code acquisition, and matching determination is performed from the start of reception of standard time radio waves to acquisition of time information. When processing cannot be completed properly in each process, the processing circuit needs to start processing from the beginning. For this reason, processing may have to be performed again and again due to the influence of noise included in the signal, and the time until the time information can be acquired may be significantly increased.

  Second synchronization is to detect the rising of the code that arrives every second among the codes indicated by the TCO data. The minute synchronization is to specify the start position of the minute. Data according to the JJY standard can be realized by detecting a portion where the position marker “P0” arranged at the end of the frame and the marker “M” arranged at the beginning of the frame are continuous. Since the beginning of the frame is recognized by the above-mentioned minute synchronization, code acquisition is started thereafter, and after acquiring the data for one frame, the parity bit is checked, and an impossible value (year, month, day, and time cannot actually occur) Value) is determined (consistency determination). For example, minute synchronization finds the beginning of a frame and may take 60 seconds. Of course, it takes several times as long to detect the beginning of a frame over several frames.

  In Patent Document 1, TCO data obtained by binarizing a demodulated signal at a predetermined sampling interval (50 ms) is acquired, and a data group consisting of binary bit strings every second (20 samples) is listed. It becomes. The apparatus disclosed in Patent Document 1 includes this bit string, a binary bit string template representing the code “P: position marker”, a binary bit string template representing the code “1”, and a binary bit string representing the code “0”. Each of the templates is compared with each other to obtain the correlation, and it is determined by the correlation whether the bit string corresponds to the code “P”, “1”, or “0”.

JP 2005-249632 A JP 2009-250623 A

  In the technique disclosed in Patent Document 1, TCO data, which is a binary bit string, is acquired and matched with a template. In a state where the electric field strength is weak or a state where a lot of noise is mixed in the demodulated signal, many errors are included in the acquired TCO data. Therefore, it is necessary to finely adjust the filter for removing noise from the demodulated signal and the threshold of the AD converter to improve the quality of TCO data.

  In Patent Document 2, a covariance value between the data value of predicted waveform data including a predetermined code and the data value of input waveform data obtained from a standard time radio signal is calculated, and the largest positive correlation is obtained. A technique for detecting a code represented by input waveform data by specifying predicted waveform data has been proposed.

  When using the covariance value, it is necessary to calculate the average value of the predicted waveform data and the average value of the input waveform data. As for the input waveform data, it is necessary to calculate the average value every time the input waveform data is obtained from the standard time radio wave signal, which increases the processing load.

  In the present invention, even when a covariance value is used as a correlation value, a time at which the current time can be obtained by accurately acquiring a code included in the standard time radio wave while reducing the amount of calculation and the calculation time. An object is to provide an information acquisition device and a radio timepiece including a time information acquisition device.

An object of the present invention is to receive a standard time radio wave including a time code representing time information;
An average value follow-up signal that removes a DC component from the input signal from the receiving means and generates an output signal indicating either a value larger than the average value or a value smaller than the average value around the average value of the input signal Generating means;
The output signal including the time code output from the average value tracking signal generation means is sampled at a predetermined sampling period, and the data value at each sample point indicates a first value indicating a low level and a high level. Input waveform data generating means for generating any one of the second values and generating input waveform data having one or more unit time lengths;
The data value of each sample point takes either the first value or the second value, has the same time length as the input waveform data, and the waveform shape is a predetermined code in the time code Predicted waveform data generating means for generating predicted waveform data including:
A calculated value is calculated by multiplying the data value of the input waveform data and the data value of the predicted waveform data, and the sum of the calculated values is equivalent to a covariance value between the input waveform data and the predicted waveform data. Correlation value calculating means for calculating as a correlation value;
A correlation value comparison unit that compares the correlation value calculated by the correlation value calculation unit and calculates an optimum value thereof;
This is achieved by a time information acquisition device comprising: control means for acquiring time information represented by the time code based on the optimum value.

  In a preferred embodiment, the average value follow-up signal generating means compares the average value signal generating means for generating a signal corresponding to the average value of the input signal, and the signal corresponding to the average value and the input signal. Comparing means for outputting an output signal indicating the comparison result.

In another preferred embodiment, the predicted waveform data generating means is configured such that each sample point has a first value indicating a low level in any predetermined section before and after the change point of the signal level, and before and after the change point. It takes one of the second value indicating the high level in any other predetermined section and the third value in other sections other than the predetermined section, and has the same time length as the input waveform data And generating a plurality of predicted waveform data whose waveform shape is sequentially shifted by a predetermined sample,
In the calculation by the correlation value calculating means, the calculation value of the third value and the first value or the second value is a value that does not affect the correlation value,
The control means specifies the second start position in the time code based on the predicted waveform data indicating the optimum value.

In another preferred embodiment, the input waveform data generation means generates a plurality of input waveform data having a plurality of unit time lengths starting from each of the first positions of the seconds,
The predicted waveform data generating means generates predicted waveform data having the same time length as the input waveform data, the waveform shape including a predetermined code before and after the start position of the minute in the time code,
Predicted waveform feature section extracting means for acquiring feature values of feature sections having unique and constant data values different from other codes in the predetermined code from the predicted waveform data;
Input waveform feature section extraction means for obtaining a data value of a feature section corresponding to the feature section of the predicted waveform data from the input waveform data,
The correlation value calculating means multiplies each of the plurality of input waveform data by the data value of the feature section and the feature value of the feature section of the predicted waveform data to calculate a calculated value,
The control means specifies the minute start position in the time code based on the input waveform data indicating the optimum value.

In yet another preferred embodiment, the input waveform data generation means starts a plurality of unit times starting from a position corresponding to the start position of a predetermined code string that constitutes time information included in the time code. Generating input waveform data having a length,
The predicted waveform data generation means generates a plurality of predicted waveform data having the same time length as the input waveform data, indicating the predetermined code sequence,
In each of the codes constituting the predetermined code string, a predicted waveform feature section extracting means for acquiring a feature value of a feature section having a unique and constant data value different from other codes from the predicted waveform data;
Input waveform feature section extraction means for obtaining a data value of a feature section corresponding to the feature section of the predicted waveform data from the input waveform data,
The correlation value calculation means calculates the operation value by multiplying the data value of the feature section of the input waveform data by the feature value of each of the plurality of predicted waveform data,
The control means acquires time information included in the time code based on the code string indicating the optimum value.

Another object of the present invention is to provide the time information acquisition device,
An internal time measuring means for measuring the current time by an internal clock;
Time correction means for correcting the current time measured by the internal time measurement means according to the current time acquired by the time information acquisition device;
This is achieved by a radio-controlled timepiece comprising time display means for displaying the current time measured by the internal time measuring means or corrected by the time adjusting means.

  According to the present invention, even when a covariance value is used as a correlation value, the current time can be obtained by accurately acquiring the code included in the standard time radio wave while reducing the amount of calculation and the calculation time. It is possible to provide a simple time information acquisition device and a radio timepiece including the time information acquisition device.

FIG. 1 is a block diagram showing the configuration of the radio timepiece according to the present embodiment. FIG. 2 is a block diagram showing a configuration example of the receiving circuit according to the present embodiment. FIG. 3A is a diagram illustrating a configuration example of an average value tracking circuit according to the present embodiment, and FIG. 3B is a diagram illustrating an example of an input signal and an output signal of the average value tracking circuit. FIG. 4 is a block diagram showing the configuration of the signal comparison circuit according to the present embodiment. FIG. 5 is a flowchart showing an outline of processing executed in the radio timepiece according to the present embodiment. FIG. 6 is a diagram for explaining the standard of the standard time radio signal according to the JJY standard. FIGS. 7A to 7C are diagrams illustrating examples of codes according to JJY, WWVB, and MSF standards, respectively. FIG. 8 is a diagram illustrating a portion of predicted waveform data used in the second synchronization according to the present embodiment. FIG. 9 is a flowchart showing in more detail the detection of the second pulse position (second synchronization) according to the present embodiment. FIG. 10 is a diagram schematically illustrating second pulse position detection processing according to the present embodiment. FIG. 11 is a diagram for explaining an example of calculating a covariance value according to the present embodiment. FIG. 12 is a flowchart showing in detail the start position detection (minute synchronization) according to the present embodiment. FIG. 13 is a diagram for explaining input waveform data and predicted waveform data in the detection of the leading position according to this embodiment. FIGS. 14A and 14B are diagrams illustrating feature sections in each code of JJY. FIG. 15 is a flowchart showing an example of a fractional detection process according to the embodiment of the present invention. FIGS. 16A to 16C are diagrams for explaining the covariance values between the input waveform data and the predicted waveform data. FIG. 17 is a diagram for explaining a feature section in each code of WWVB. FIG. 18 is a diagram for explaining a feature section in each code of MSF. FIG. 19 is a flowchart showing in more detail the detection of the second pulse position (second synchronization) according to the second embodiment of the present invention. FIG. 20 is a diagram schematically illustrating second pulse position detection processing according to the second embodiment.

  Embodiments of the present invention will be described below with reference to the accompanying drawings. In the embodiment of the present invention, a standard time radio wave in a long wave band is received, the signal is detected, a sequence of codes indicating a time code included in the signal is extracted, and based on the sequence of the codes The radio timepiece for correcting the time is provided with the time information acquisition device according to the present invention.

  Currently, standard time radio waves are transmitted from a predetermined transmitting station in Japan, Germany, the United Kingdom, Switzerland, and the like. For example, in Japan, standard time radio waves with amplitude modulation of 40 kHz and 60 kHz are transmitted from transmitting stations in Fukushima Prefecture and Saga Prefecture, respectively. The standard time radio wave includes a string of codes constituting a time code indicating the year, month, day, hour and minute, and is transmitted in one cycle of 60 seconds. Since one code has a unit time length (1 second), one cycle can include 60 codes.

  FIG. 1 is a block diagram showing the configuration of the radio timepiece according to the present embodiment. As shown in FIG. 1, the radio timepiece 10 includes a CPU 11, an input unit 12, a display unit 13, a ROM 14, a RAM 15, a receiving circuit 16, an internal clock circuit 17, a signal comparison circuit 18, and an average value tracking circuit 19.

  The CPU 11 reads out a program stored in the ROM 14 at a predetermined timing or in response to an operation signal input from the input unit 12, expands the program in the RAM 15, and configures the radio clock 10 based on the program. Execute instructions and data transfer. Specifically, for example, by receiving the standard time radio wave by controlling the receiving circuit 16 every predetermined time, a sequence of codes included in the standard time radio signal is obtained from digital data based on the signal obtained from the receiving circuit 16. Specific processing is performed to correct the current time measured by the internal clock circuit 17 based on this sequence of codes, and to transfer the current time clocked by the internal clock circuit 17 to the display unit 13. In the present embodiment, one or more unit time lengths of predicted waveform data in a predetermined form are generated, and the predicted waveform data and input waveform data obtained from the standard time radio wave received by the receiving circuit 16 are obtained. By comparing, the beginning of the second is specified.

  Further, in the present embodiment, predicted waveform data including a predetermined code having one or more unit time lengths is generated, and the beginning of the minute is specified. Furthermore, in the present embodiment, by using an operation value obtained by multiplying the accumulated value of the data value of a predetermined section (feature section) of the input waveform data and the multiplication value based on the predicted waveform data, Various code values including date are specified. By specifying the date and time, the error in the internal clock circuit 17 is calculated, and the current time in the internal clock circuit 17 can be corrected.

  The input unit 12 includes a switch for instructing execution of various functions of the radio timepiece 10, and outputs a corresponding operation signal to the CPU 11 when the switch is operated. The display unit 13 includes a dial, an analog pointer mechanism controlled by the CPU 11, and a liquid crystal panel, and displays the current time measured by the internal clock circuit 17. The ROM 14 stores a system program, an application program, and the like for operating the radio timepiece 10 and realizing a predetermined function. The program for realizing the predetermined function includes a program for controlling the signal comparison circuit 18 for second pulse position detection processing, minute leading position detection processing, and code decoding processing, which will be described later. The RAM 15 is used as a work area for the CPU 11 and temporarily stores programs and data read from the ROM 14, data processed by the CPU 11, and the like.

  The reception circuit 16 includes an antenna circuit, a detection circuit, and the like, obtains a signal demodulated from the standard time radio wave received by the antenna circuit, and outputs the signal to the signal comparison circuit 18. The internal clock circuit 17 includes an oscillation circuit, counts clock signals output from the oscillation circuit, counts the current time, and outputs current time data to the CPU 11.

  The average value tracking circuit 19 is called a so-called average value tracking type slicer, receives the output of the receiving circuit 16, removes its DC component, and outputs it to the signal comparison circuit 18. The average value tracking circuit 19 outputs a high level signal with respect to a signal having a value larger than the average value and a low level signal with respect to a signal having a value smaller than the average value, based on the average value of the input signal. A signal is output. Therefore, the average value of the output signal is “0”. The average value tracking circuit 19 will be described later with reference to FIG.

  FIG. 2 is a block diagram showing a configuration example of the receiving circuit 16 according to the present embodiment. As shown in FIG. 2, the receiving circuit 16 includes an antenna circuit 50 that receives standard time radio waves, a filter circuit 51 that removes noise of a standard time radio signal (standard time radio signal) received by the antenna circuit 50, and a filter An RF amplification circuit 52 that amplifies a high-frequency signal that is an output of the circuit 51, and a detection circuit 53 that detects a signal output from the RF amplification circuit 52 and demodulates a standard time radio signal, and is demodulated by the detection circuit 53. The signal is output to the average value tracking circuit 19.

  FIG. 3A is a diagram illustrating a configuration example of the average value tracking circuit 19 according to the present embodiment, and FIG. 3B is a diagram illustrating examples of input signals and output signals of the average value tracking circuit 19. As shown in FIG. 3A, the average value tracking circuit 19 according to the present embodiment includes a resistor 301, a capacitor 302, and a comparator 303. The path through resistor 301 is connected to capacitor 302 and the-(minus) terminal of the comparator. In this path, the resistor 301 and the capacitor 302 generate a signal of the reference voltage Vth corresponding to the average value of the input signal in. Therefore, as shown in FIG. 3B, when the input signal in is higher than the reference voltage Vth, the output signal out from the comparator 303 becomes the high level H. On the other hand, when the input signal in is a voltage lower than the reference voltage Vth, the output signal from the comparator 303 becomes a low level L. Further, the direct current component is removed from the output signal out from the average value tracking circuit 19. Therefore, in the present embodiment, the average value Vth is considered as the central value “0”, and in the binarized data, a value larger than the average value Vth is “1”, and the average value Vth The small value is “−1”.

  FIG. 4 is a block diagram showing the configuration of the signal comparison circuit 18 according to the present embodiment. As shown in FIG. 4, the signal comparison circuit 18 according to this exemplary embodiment includes an input waveform data generation unit 21, a reception waveform data buffer 22, a predicted waveform data generation unit 23, a waveform cutout unit 24, a correlation value calculation unit 25, and A correlation value comparison unit 26 is included. In addition, the signal comparison circuit 18 according to the present embodiment includes feature section extraction units 27 and 28, a data value accumulation unit 29, and an accumulation value buffer 30.

  The input waveform data generation unit 21 converts the signal output from the average value tracking circuit 19 into digital data whose value takes any one of a plurality of values at a predetermined sampling interval, and outputs the digital data. For example, the sampling interval is 50 ms, and data of 20 samples per second can be acquired. The reception waveform data memory 22 sequentially stores the data generated in the input waveform data generation unit 21. The reception waveform data memory 22 can store a plurality of unit time length (1 second) data (for example, 10 unit time (10 seconds)). Erase.

  In the present embodiment, the input waveform data generation unit 21 binarizes the analog signal (see reference numeral 1010 in FIG. 10 described later) output from the receiving circuit 16. In the present embodiment, the average value tracking circuit 19 outputs a high level H or low level L signal out. In the present embodiment, at the time of binarization, when the level is low, the first value “−1” is given as the data value, and when the level is high, the second value “1” is given as the data value. Is given. Therefore, the received waveform data buffer 22 stores digital data composed of the first value and the second value. Therefore, the data value of the input waveform data Sn (j) extracted by the waveform cutout unit 24 also takes either the first value or the second value.

  The predicted waveform data generation unit 23 generates predicted waveform data of a predetermined time length to be compared, which is used in a second pulse position detection process, a minute leading position detection process, and the like, which will be described later. The predicted waveform data generated by the predicted waveform data generation unit 23 will be described in detail in each detection process. The waveform cutout unit 24 extracts input waveform data having the same time length as the predicted waveform data from the received waveform data buffer 22.

  The feature section extraction unit 28 extracts the data value (feature value) in the feature section in the predicted waveform data according to the type of code of the predicted waveform data. In addition, the feature section extraction unit 27 extracts data values of sections corresponding to the feature section extraction unit 28 in the input waveform data. In the present embodiment, in the second pulse position detection process, the minute leading position detection process, and the code decoding process, both the input waveform data and the predicted waveform data have data values corresponding only to a predetermined section (feature section). (Feature value) is used for the calculation. This feature section is determined by the type of code of the predicted waveform data. This feature section will be described in detail later.

  The correlation value calculation unit 25 calculates a correlation value between each of the plurality of predicted waveform data and the input waveform data. In the present embodiment, covariance is adopted to obtain a correlation as will be described later. The correlation value comparison unit 26 compares the correlation values (covariance values) calculated by the correlation value calculation unit 25 and identifies the optimum value.

  FIG. 5 is a flowchart showing an outline of processing executed in the radio timepiece 10 according to the present embodiment. The processing shown in FIG. 5 is mainly executed by the CPU 11 and the signal comparison circuit 18 based on instructions from the CPU 11. As shown in FIG. 5, the CPU 11 and the signal comparison circuit 18 (hereinafter referred to as “CPU 11 etc.” for convenience of description) detect the second pulse position (step 501). The process of detecting the second pulse position is also referred to as second synchronization. FIG. 6 is a diagram for explaining the standard of the standard time radio signal according to the JJY standard. As shown in FIG. 6, the standard time radio wave signal according to the JJY standard is transmitted in a predetermined order with the JJY code. In the standard time radio signal of JJY, symbols indicating “P”, “1” and “0” having a unit time length of 1 second are connected. The standard time radio wave has 60 seconds as one frame, and one frame includes 60 codes. Further, in the standard time radio wave, the position marker “P1”, “P2”,... Or the marker “M” arrives every 10 seconds, and the position marker “P0” and the frame arranged at the end of the frame. By detecting the portion where the marker “M” arranged at the head of the frame continues, the head of the frame that arrives every 60 seconds, that is, the head position of the minute can be found.

  FIGS. 7A to 7C are diagrams illustrating examples of codes according to JJY, WWVB, and MSF standards, respectively. As shown in FIG. 6 and FIG. 7A, JJY includes three codes indicating “0”, “1”, and “P”, respectively. The code of JJY is a code of unit time length (1 second), and rises from the low level to the high level at the head of the second. The code “0” of JJY becomes the high level only for the first 800 ms, and becomes the low level in the subsequent 200 ms. That is, the code “0” is an 80% duty signal. The code “1” becomes a high level only for the first 500 ms, and becomes a low level in the subsequent 500 ms. That is, the code “1” is a 50% duty signal. The code “P” is a code used as a position marker or a marker, and becomes a high level only for the first 200 ms and becomes a low level in the subsequent 800 ms. That is, the symbol “P” is a signal with a 20 percent duty.

  In the present embodiment, in order to accurately detect that the JJY signal rises from the low level to the high level at the beginning of the second, a predetermined number (units) of waveform data having a predetermined data value is obtained. In the embodiment, a plurality of pieces of predicted waveform data are generated such that they are continuous by 4) and are shifted by 50 ms. By calculating the covariance value between the multiple predicted waveform data and the input waveform data, the change point indicating the rise from the low level to the high level of the predicted waveform data indicating the optimal covariance value is set to the second pulse position. Judged as (first position of second).

  Next, the CPU 11 detects the leading position of the minute, that is, the leading position of the standard time radio signal of one frame (step 502).

  Thereafter, the CPU 11 executes a code decoding process (step 503). In step 503, various codes of the standard time radio signal (one-digit code (M1), ten-digit code (M10), other codes such as date, day of the week, etc.) Decoding is performed based on the comparison with the input waveform data.

  In the present embodiment, a case where a standard radio signal according to JJY is received and the second synchronization is performed will be described first. However, when a standard radio signal according to another standard, for example, WWVB or MSF is received. It can also be applied to. Here, the symbols according to WWVB and MSF are also briefly described.

  FIG. 7B is a diagram illustrating codes included in WWVB in the United States. As shown in FIG. 7B, WWVB includes three codes indicating “0”, “1”, and “P”, respectively. The sign of WWVB falls from the high level to the low level at the beginning of the second. The code “0” of WWVB becomes a low level only for the first 200 ms, and becomes a high level in the subsequent 800 ms. The code “1” becomes a low level only for the first 500 ms, and becomes a high level in the subsequent 500 ms. Further, the code “P” becomes a low level only for the first 800 ms, and becomes a high level in the subsequent 200 ms.

  FIG.7 (c) is a figure which shows the code | symbol contained in UK MSF. Unlike JJY and WWVB, MSF has five codes, and four of them can represent the values of two bits (A, B). The sign of MSF falls from high level to low level at the beginning of the second. The code corresponding to “A = 0, B = 0” becomes a low level only for the first 100 ms, and becomes a high level in the subsequent 900 ms. The code corresponding to “A = 1, B = 0” becomes a low level only for the first 200 ms, and subsequently becomes a low level in 800 ms. Further, the code “M” corresponding to the marker becomes a low level only for the first 500 ms, and becomes a high level in the subsequent 500 ms. A code corresponding to “A = 0, B = 1” sequentially becomes a low level, a high level, and a low level by 100 ms in the first 300 ms, and then becomes a high level in 700 ms thereafter. Further, the code corresponding to “A = 1, B = 1” becomes a low level only for the first 300 ms, and becomes a high level in the subsequent 700 ms.

  The second pulse position detection process (step 501) according to the present embodiment will be described in detail below. FIG. 8 is a diagram illustrating a portion of predicted waveform data used in the second synchronization according to the present embodiment. In FIG. 8, one second corresponding to the initial unit time length of each predicted waveform data is displayed. A broken line indicated by reference numeral 800 indicates the beginning of the predicted waveform data. Actually, in the present embodiment, four unit time lengths, ie, four unit time lengths, that is, four unit time lengths shown in FIG. 23. Further, in the present embodiment, 20 pieces of predicted waveform data P (1, j) to P (20, j) in which the position of the head of data (rise from low level to high level) is shifted by 50 ms each. Is generated by the predicted waveform data generation unit 23.

  As shown in FIG. 8, the first predicted waveform data P (1, j) rises from a low level to a high level at the beginning of the data (see reference numeral 800). In the predicted waveform data according to the present embodiment, the low level is applied only for a predetermined interval in front of the point rising from the low level to the high level (the point indicated by reference numeral 800 in the first predicted waveform data). And a second value indicating a high level only for a predetermined interval behind the point (a new side in time). Other than the predetermined section before and after the point, another third value indicating “0” is provided. In the example of FIG. 8, “−1” is used as the first value, “1” is used as the second value, and “0” is used as the third value. In the present embodiment, the predetermined interval of the first value indicating the low level and the predetermined interval of the second value indicating the high level are both 50 ms.

  In the actual calculation, in the portion having the first value and the portion having the second value, that is, in the first predicted waveform data P (1, j) (see reference numeral 801), reference numerals 811 and 812 are given. In the portion shown, the second predicted waveform data P (2, j) to the twentieth predicted waveform data P (20, j), only the operations indicated by the reference numerals 821, 831, 841, and 851 are substantially performed. It becomes effective.

  As can be understood from FIG. 8, the second predicted waveform data P (2, j) (see reference numeral 802) rises from the low level to the high level at a position where 50 ms has elapsed from the top of the data. Hereinafter, in the third predicted waveform data P (3, j), the fourth predicted waveform data P (4, j),..., The rising position from the low level to the high level corresponds to 50 ms. Only the position goes back sequentially.

  FIG. 9 is a flowchart showing in more detail the detection of the second pulse position (second synchronization) according to the present embodiment. FIG. 10 is a diagram schematically illustrating the second pulse position detection process according to the present embodiment. As shown in FIG. 9, the predicted waveform data generation unit 23 rises from the low level to the high level in units of 4 unit time lengths (4 seconds) as described above by 50 ms in accordance with instructions from the CPU 11. Twenty pieces of predicted waveform data P (1, j) to P (20, j) whose positions are shifted are generated (step 901, reference numeral 1001 in FIG. 10). As described with reference to FIG. 7, the value of the predicted waveform data is any one of the first value, the second value, and the third value.

  Next, in accordance with an instruction from the CPU 11, the waveform cutout unit 24 cuts out data of 4 unit time length (4 seconds) from the received waveform data buffer 22 to generate input waveform data Sn (j) (step 902, FIG. 10 reference 1011). In this embodiment, since 20 samples of data are acquired per second, Sn (j) is data including 80 samples. In order to increase the processing speed or reduce the size of the received waveform data buffer 22, the waveform cutout unit 24 is configured so that all of the data of four unit time lengths are not stored in the received waveform data buffer 22. Sample data may be taken out in order of (1), Sn (2),.

  Next, the correlation value calculation unit 25 initializes the parameter p for specifying the predicted waveform data to “1” in accordance with the instruction from the CPU 11 (step 903), the data value of the input waveform data Sn (j), and the predicted waveform data P A correlation value (covariance value) C (p) with the data value of (p, j) is calculated (step 904). In step 904, the correlation value calculation unit 25 calculates an accumulated value Ca (p) of the correlation value C (p). The accumulated value Ca (p) accumulated in the previous processing and stored in the RAM 15 may be read, and C (p) calculated this time may be added to Ca (p).

  In the present embodiment, the correlation value calculation unit 25 uses the data value Sn (j) of the input waveform data and the data value P (p, j) value of the predicted waveform data, and uses the covariance value C (p ) Is calculated. As shown in FIG. 9, by calculating the covariance values of Sn (j) and each of P (1, j), P (2, j),..., P (20, j), C ( 1), C (2),..., C (20) are obtained. The covariance value can be generally obtained by the following mathematical formula.

C (p) = (1 / N) * Σ ((Sn (j) −Sm) * (P (p, j) −Pm))
Sm is the average value of Sn (j), and Pm is the average value of P (p, j). Sm = (1 / N) * Σ (Sn (j)), Pm = (1 / N) * Σ (P (p, j))
The sigma is for j = 1 to N.

The above C (p) is
C (p) = (1 / N) Σ (Sn (j) * P (p, j)) − Sm * Pm
And transformed. Therefore, in general, every time the waveform cutout unit 24 acquires the sample data Sn (j), the correlation value calculation unit 25 calculates Sn (j) * P (p, j), which is a multiplication result. The accumulation of the operation value in the addition result is repeated, and when the last sample data Sn (N) is obtained, the correlation value calculation unit 25 calculates the average value Sm, and from the accumulation result, the Sm * Pm should be subtracted.

  In particular, in the present embodiment, when the output signal out from the average value tracking circuit 19 is at the low level L, the input waveform data generation unit 21 gives the first value “−1” as the data value, and the high level When H, the second value “1” is given as the data value to binarize. The average value of the binarized data can be considered as “0”. Therefore, the average value Sm of the input waveform data Sn (j) can also be considered as “0”. Therefore, in the present embodiment, Sm * Pm = 0.

  Furthermore, as will be described later, in the present embodiment, the covariance value itself is not necessary, and it is only necessary to compare the covariance value for each parameter p or its accumulated value. Therefore, it is only necessary to calculate the sum Σ (Sn (j) * P (p, j) of the product of the sample points (Sn (j) * P (p, j)), and it is necessary to divide the sum by the number N of sample points. Therefore, in this embodiment, Σ (Sn (j) * P (p, j) is calculated as the covariance value C (p).

  In the present embodiment, when Sn (j) is the first value “−1” and P (p, j) is the first value “−1”, Sn (j) * P (p, j ) Becomes “1”. Similarly, when Sn (j) is the second value “1” and P (p, j) is the second value “1”, Sn (j) * P (p, j) is “ 1 ". In other words, when P (p, j) takes the first value or the second value and Sn (j) and P (p, j) match, the predetermined value indicates a positive correlation. (“1” in this embodiment).

  On the other hand, when Sn (j) is the first value “−1” and P (p, j) is the second value “1”, Sn (j) * P (p, j) is “− 1 ". Similarly, when Sn (j) is the second value “1” and P (p, j) is the first value “−1”, Sn (j) * P (p, j) is “−1”. That is, when P (p, j) takes the first value or the second value and Sn (j) and P (p, j) do not match, a negative predetermined value indicating a negative correlation (In this embodiment, “−1”).

  Further, when P (p, j) is the third value “0”, Sn (j) * P (p, j) affects the calculation of the covariance value regardless of the value of Sn (j). The value not to be “0”.

  FIG. 11 is a diagram for explaining an example of calculating a covariance value according to the present embodiment. In the example of FIG. 11, the first one second (j = 1 to 20) is shown in the input waveform data and the predicted waveform data. In the input waveform data Sn (j), when j = 4, 5, the input waveform data Sn (j) is at the high level and indicates the second value “1”. Otherwise, it is at a low level, indicating the first value “−1”.

  In the predicted waveform data P (1, j) to P (3, j), C (1) to C (3) are “0”, respectively. On the other hand, in the predicted waveform data P (4, j) whose waveform rising position matches the waveform rising position of the input waveform data Sn (j), C (4) is “2”. On the other hand, in the predicted waveform data P (6, j) in which the rising position of the waveform matches the falling position of the waveform of the input waveform data Sn (j), C (6) is “−2”. Thus, in this embodiment, when the rising position of the input waveform data matches the rising position of the predicted waveform, a larger covariance value appears to indicate that there is a stronger correlation. In addition, when the falling position of the input waveform data matches the rising position of the predicted waveform, that is, when the waveform has an opposite phase, a negative covariance value indicating a negative correlation appears. On the other hand, a value “0” that does not affect the calculation result appears except for the rising position of the predicted waveform data.

  If the parameter p is smaller than “20” (No in step 905), the parameter p is incremented (step 906) and the process returns to step 904. When the covariance values C (1) to C (20) are acquired for all the parameters p (Yes in step 905), it is determined whether the covariance values have been calculated a predetermined number of times (step 907). If NO is determined in step 907, the process returns to step 902.

  If it is determined Yes in step 907, the correlation value comparison unit 26 compares the accumulated values Ca (1) to Ca (20) of the covariance values C (1) to C (20) to determine the optimum. A value (in this case, the maximum value) C (x) is found (step 908). The CPU 11 receives the optimum value C (x) and determines whether or not the optimum value is valid (step 909).

Among the accumulated values Ca (p) of the obtained covariance values C (p), C (x) indicating the maximum value is the most highly correlated predicted waveform, but is obtained from a sample with insufficient parameters. In the covariance value, the maximum value may appear due to an accidental factor due to noise. For the purpose of eliminating such a case, for example, in step 909, for example, the following criteria are provided to avoid erroneous detection.
(1) The number of input waveform data used for the covariance calculation is greater than or equal to a predetermined number.
(2) The value of x indicating C (x) appears a plurality of times, the value of the plurality of times x is equal, and the frequency is higher than others (x is the mode value).
(3) The value of x is continuously equal to or more than a predetermined number of times (continuity of the mode value).
(4) The dispersion of C (p) and Ca (p) is below a specified value.
(5) Calculate kurtosis and skewness, which are statistics of C (p) and Ca (p), or an evaluation function equivalent thereto, and determine whether the result reaches a specified value.

  Of course, the judgment of effectiveness is not limited to the above-described method, and the average value or standard deviation of the covariance values is used, for example, even if the maximum value of the covariance values is smaller than the average value, it is not significant. It may be determined that there is not, or a general significance level (for example, 5 percent) may be used in statistics.

  If the optimum value C (x) is valid (Yes in step 909), the CPU 11 starts from the change point of the signal level in the predicted waveform data indicated by the optimum value C (x), that is, the first value indicating the low level. The position that changes to the second value indicating the high level is determined as the second pulse position (step 910). The CPU 11 stores second pulse position information in the RAM 15. This second pulse position is used in processing such as detection of the leading position as described below.

  When the second pulse position is detected (step 501), that is, when the second synchronization is completed, the minute leading position is detected (step 502). Detection of the minute start position is also referred to as minute synchronization. In step 501, the second pulse position (first position of the second) has already been determined. In JJY, in one frame, a code indicating the position marker “P0” is arranged at the end, and a code indicating the marker “M” is arranged at the top. Therefore, in the minute synchronization, the CPU 11 and the signal comparison circuit 18 indicate that the code indicating the position marker “P0” arranged at the end of the frame and the code indicating the marker “M” arranged at the top of the frame are continuous. to decide.

  Next, the minute leading position detection will be described in detail. Detection of the minute start position is also referred to as minute synchronization. FIG. 12 is a flowchart showing in detail the start position detection (minute synchronization) according to the present embodiment. FIG. 13 is a diagram for explaining input waveform data and predicted waveform data in the detection of the leading position according to the present embodiment. With the second synchronization, the second pulse position (first position of the second) has already been determined. Further, as shown in FIG. 6, at the minute start position, the code “P” with a duty of 20% is continuous before and after (60 seconds and 1 second). Therefore, in the minute synchronization, the prediction waveform data having a unit time length of 2 units in a form in which the code “P” having a duty of 20% is generated is generated. In addition, 60 pieces of input waveform data of 2 unit time length (2 seconds) starting from the second pulse position (second start position) are generated. By calculating the correlation value between the predicted waveform data and each of the 60 input waveform data, 60 correlation values (covariance values) C (1) to C (60) can be obtained.

  As illustrated in FIG. 12, the predicted waveform data generation unit 23 generates predicted waveform data P (j) having a two-unit time length in a form in which two symbols “P” are connected in accordance with an instruction from the CPU 11 (step S <b> 12). 1201). As shown in FIG. 13, this predicted waveform data (see reference numeral 1300) has two waveforms in which the first 200 ms (20%) is high level and the rest is low level in unit time length (1 second). It is a thing.

  The feature section extraction unit 28 extracts data values (feature values) belonging to the feature section of the predicted waveform data P (j) (step 1202). FIGS. 14A and 14B are diagrams illustrating feature sections in each code of JJY. As shown in FIG. 14A, in the code “P” (see the reference 1401), the code “1” (see the reference 1402), and the code “0” (see the reference 1403), the value is the value of another code. There are sections with unique values that are different from For example, in the code “P”, an interval from 200 ms to 500 ms (see reference symbol 1411) is a low level (data value “−1”), and in this interval, a unique value “−1” different from others is included. ing.

  Therefore, in the present embodiment, in the code “P”, a section of 200 ms to 500 ms is a feature section, and the data value (feature value) is “−1”. In the predicted waveform data P (j) shown in FIG. 13, if the number of samples per unit time length is 20, j = 1 to 40. In this case, the feature section extraction unit 28 uses the data values of the sections of 200 ms to 500 ms and the sections of 1200 ms to 1500 ms as the feature values, that is, P (5) to P (10) and P (25) to P ( Only 30) is extracted.

  As will be described later, the feature value of the feature section of the predicted waveform data is also used in the code decoding process. In the code decoding process, it is only necessary to determine whether the code is “0” or “1”. That is, since the minute synchronization has been completed, it is not necessary to determine the code “P”.

  As shown in FIG. 14B, in the code “1”, the section (see the code 1412) from 500 ms to 800 ms is at the low level (data value “−1”). And a unique value “−1”. On the other hand, in the code “0”, an interval from 500 ms to 800 ms (see reference numeral 1413) is a high level (data value “1”). In this interval, a unique value “1” different from other codes “1” is obtained. "have. Therefore, in the codes “1” and “0”, a section of 500 ms to 800 ms is a feature section. Further, the feature value in the feature section with the code “1” is “−1”, and the feature value in the feature section with the code “0” is “1”.

Next, the parameter i for specifying the second head position is initialized, and in accordance with an instruction from the CPU 11, the waveform cutout unit 24 inputs an input waveform having a unit time length (2 seconds) from the second head position from the received waveform data buffer 22. Data Sn (i, j) is generated (step 1204). Further, the feature section extraction unit 27 extracts data values belonging to the feature section of Sn (i, j) so as to correspond to the feature section of the predicted waveform data according to the information from the feature section extraction unit 28 (step 1205). ). The feature section extraction unit 27 extracts Sn (1,5) to Sn (1,10) and Sn (1,25) to Sn (1,30) as data values belonging to the feature section when i = 1. To do. In general,
Sn (i, 5) to Sn (i, 10), and
Sn (i, 25) to Sn (i, 30) are extracted as data belonging to the feature section.

  Next, the correlation value calculation unit 25 calculates a correlation value (covariance value) C (i) between the input waveform data Sn (i, j) belonging to the feature section and the predicted waveform data P (j) belonging to the feature section. (Step 1206). The calculation of the covariance value is the same as the second synchronization process. Only the trade-off with the feature section will be described below. In the present embodiment, for input waveform data, Sn (i, 5) to Sn (i, 10) and Sn (i, 25) to Sn (i, 30) are data values belonging to the feature section. Extracted. Further, P (5) to P (10) and P (25) to (P30) are also extracted from the predicted waveform data.

Therefore, when calculating the covariance value C (i), in the sum ΣSn (i, j) * P (j) of the multiplication value of the data value of the input waveform data and the data value of the predicted waveform data, j = 5-10, 25-30. Here, as described with reference to FIG. 14A, the data value (feature value) of the feature section with the symbol “P” is “−1”. Therefore, the prediction waveform data P (j) (j = 5 to 10, 25 to 30) in the prediction section is “−1”. Therefore, when calculating the total sum of the multiplication values, Sn (i, j) (j = 5 to 10, 25 to 30) may be obtained and multiplied by the feature value “−1”.

  Next, the CPU 11 determines whether or not the parameter i is 60 (step 1207). If it is determined No in step 1207, the CPU 11 increments the parameter i (step 1208). In the subsequent step 1204, according to the instruction from the CPU 11, the waveform cutout unit 24 sets the length of 2 unit times (2) from the next second start position (that is, a position 20 samples after the second start position of the previous input waveform data). Second) input waveform data Sn (i, j). Hereinafter, a covariance value is calculated between the newly acquired input waveform data Sn (i, j) and the predicted waveform data P (j).

  As shown in FIG. 13, the input waveform data Sn (1, j) is composed of data 1301, 1302 having a length of 2 unit time from a certain second head position. The next input waveform data Sn (2, j) is composed of data 1302 and 1303 having a length of 2 unit time from the next second head position. Thus, Sn (n-1, j) and Sn (n, j) are data in which the second head position is shifted by the unit time length (1 second). The last input waveform data Sn (60, j) is composed of data 1359 and 1360 of 2 unit time length shifted by 59 seconds from the first input waveform data Sn (1, j).

  The data value belonging to the feature section of the input waveform data Sn (1, j), Sn (2, j), Sn (3, j),..., Sn (60, j) and the feature section space of the predicted waveform data Are used to calculate the respective covariance values. In FIG. 13, for the convenience of illustration, the prediction for calculating the covariance among Sn (1, j), Sn (2, j), Sn (3, j),..., Sn (60, j). The waveform data is P (1, j), P (2, j), P (3, j),..., P (60, j), but these are actually the same value P (j). It is.

  As described in the second pulse position detection process, the average value Sm of the input waveform data Sn (j) can be considered as “0”. Therefore, in the detection processing of the leading position of the minute, as the covariance value, the data value of the sample point of the input waveform data Sn (i, j) and the data value of the corresponding sample point of the predicted waveform data P (j) And the average value Pm of the predicted waveform data P (j) and the average value Sm of the input waveform data Sn (i, j) need not be calculated.

  When all the correlation values (covariance values) C (1) to C (60) are acquired, the correlation value comparison unit 26 compares the covariance values C (1) to C (60) to determine the optimum value. (Maximum value in this case) C (x) is found (step 1209). The CPU 11 receives the optimum value C (x) and determines whether or not the optimum value is valid (step 1210). Whether it is valid or not is also the same as in the case of the second synchronization process (step 909 in FIG. 9). Note that when applying the criteria (1) to (3) described in step 909, steps 1203 to 1209 in FIG. 12 are repeated a predetermined number of times.

  If NO is determined in step 1210, the process returns to step 1203, and the waveform cutout unit 24 is different from the data used for the previous processing stored in the reception waveform buffer 22 in accordance with the instruction from the CPU 11. Get input waveform data.

  If it is determined Yes in step 1210, the CPU 11 changes the head position of the second code “P” in the input waveform data indicated by the optimum value C (x), that is, from the second low level to the high level. Is determined to be the leading position of the minute (step 1211). The CPU 11 stores information on the start position of the minute in the RAM 15.

  Next, the decoding process (step 503) of the code constituting the time code will be described. By determining the start position of the minute, the position of various codes such as year, day, day of the week, hour, minute in the time code is determined.

  FIG. 15 is a flowchart showing an example of a fractional detection process according to the embodiment of the present invention. In this embodiment, the waveform cutout unit 24 acquires the input waveform data Sn (j) having a length of 4 unit time from the head position of the code (fractional place) (step 1501). If it is 20 samples per second, input waveform data of 80 samples (j = 1 to 80) can be obtained.

Next, the waveform cutout unit 24 extracts a feature section of the input waveform data Sn (j) (step 1502). As shown in FIG. 14B, the feature section for the codes “0” and “1” based on JJY is a position 800 ms from a position 500 ms from the top of the code. Therefore, the characteristic section of the input waveform data Sn (j) is
It is a section of data values of Sn (10) to Sn (16), Sn (30) to Sn (36), Sn (50) to Sn (56), and Sn (70) to Sn (76).

Next, the parameter BCD that specifies the value of the fractional part represented by BCD is initialized to “0000” (step 1503). The predicted waveform data generation unit 23 generates predicted waveform data P (j) having a 4-unit time length corresponding to the code indicated by the parameter BCD (step 1504). Further, the predicted waveform data generation unit 23 extracts a feature section of the predicted waveform data P (j) (step 1505). This feature section is
This is a section of data values P (10) to P (16), P (30) to P (36), P (50) to P (56), and P (70) to P (76).

Next, the correlation value calculation unit 25 obtains an operation value by multiplying the data value of the feature section of Sn (j) and the corresponding data value (feature value) of the feature section of P (j). A covariance value C (p) is calculated based on the calculated value (step 1506). Note that there are four characteristic sections of the predicted waveform data P (j), and each data value is “1” or “0”. Therefore, the multiplication of data values can be obtained as follows.
(Feature value of feature section (P (10) to P (16))) × Σ (Sn (10) to Sn (16)) + (Feature value of feature section (P (30) to P (36))) × Σ (Sn (30) to Sn (36)) + (feature value of feature section (P (50) to P (56))) × Σ (Sn (50) to Sn (56)) + (feature section ( Characteristic value of P (70) to P (76)) × Σ (Sn (70) to Sn (76))
Therefore, there is no need to obtain the sum of the multiplication values of all data values.

  Further, as described in the second pulse position detection process, the average value Sm of the input waveform data Sn (j) can be considered as “0”. Accordingly, even in the fractional detection process, the average value Pm of the predicted waveform data P (j) and the average value Sm of the input waveform data Sn (i, j) are calculated when calculating the covariance value. There is no need.

  If the parameter is smaller than “BCD = 1001” (step 1507), the parameter BCD is incremented (step 1508) and the processing returns to step 1504. If YES is determined in step 1507, the process proceeds to step 1509.

  When all the correlation values (covariance values) C (1) to C (10) are acquired, the correlation value comparison unit 26 compares the covariance values C (1) to C (10) to determine the optimum value. C (x) is found (maximum value in this case) (step 1509). The CPU 11 receives the optimum value C (x) and determines whether or not the optimum value is valid (step 1510). Whether it is valid or not is also the same as in the case of the second synchronization process (step 909 in FIG. 9). If NO in step 1510, the process returns to step 1501. On the other hand, if it is determined Yes in step 1510, the CPU 11 determines that the value (BCD) indicated by the predicted waveform data indicated by the optimum value C (x) is a fractional value (step 1511). ). The CPU 11 stores a fractional value in the RAM 15.

  Decoding of other codes such as the tenths of a minute, the hours of the hour, the tens of the digits, and the day of the week can also be realized by the same processing as that of the ones of the minutes. When the time information including the current date and time, the day of the week, the current time, and the like is acquired by decoding the code, the CPU 11 stores the obtained time information in the RAM 15. In addition, the CPU 11 corrects the current time measured by the internal clock circuit 17 based on the current time obtained from the code, and displays the obtained current time on the display unit 13 (step 504).

  Although second synchronization, minute synchronization, and code decoding have been described for the JJY signal, second synchronization, minute synchronization, and code decoding are also possible for other standards such as WWVB and MSF.

  Second synchronization in the case of WWVB or MSF will be described. As shown in FIGS. 7B and 7C, WWVB and MSF fall from the high level to the low level at the beginning of the second. The case where the predicted waveform data applied to JJY is applied to the signal that falls at the head in this way will be described.

  FIGS. 16A to 16C are diagrams for explaining the covariance values between the input waveform data and the predicted waveform data. In FIG. 16A, the input waveform data Sn (j) rises from a low level to a high level at the first position of the second (see reference numeral 1600). Predicted waveform data P (j) that takes a first value corresponding to a low level before the rising point and takes a second value corresponding to a high level after the rising point; Considering the covariance value C with the input waveform data Sn (j), the maximum value is “2”.

  On the other hand, as shown in FIG. 16B, consider input waveform data S′n (j) that falls from a high level to a low level at the start position of the second. Considering the covariance value C between the input waveform data S′n (j) and the predicted waveform data P (j), the minimum value is “−2”. That is, in order to detect the leading position of the second of data that falls from the high level to the low level at the leading position of the second, such as WWBV and MSF, for example, in the process of FIG. The minimum value of the covariance value (accumulation class) may be selected as x).

  Alternatively, the above-described predicted waveform data P (j) is inverted in order to detect the leading position of the second of the data that falls from the high level to the low level at the leading position of the second, such as WWVB or MSF. Other predicted waveform data may be applied. In FIG. 16C, the input waveform data S′n (j) is the same as that in FIG. The predicted waveform data P ′ (j) is obtained by inverting the predicted waveform data P (j) shown in FIG. In this case, the covariance value C (2) when p = 2 takes the maximum value. Therefore, the second position of the second may be determined based on the predicted waveform data P (2) and the input waveform data Sn (2).

  Next, minute synchronization and code decoding in the case of WWVB and MSF will be described. Also in WWVB, it is possible to calculate a covariance value using only the data value of the feature section by extracting the data value belonging to the feature section. FIG. 17 is a diagram for explaining a feature section in each code of WWVB. As shown in FIG. 17, in the WWVB code, the value of the marker (see reference numeral 1701), the reference numeral “0” (refer to reference numeral 1702), and the reference numeral “1” (refer to reference numeral 1703) There are different sections with unique values. In the marker, an interval from 500 ms to 800 ms (see reference numeral 1711) is a low level (data value “−1”), and this interval has a unique value “−1” different from others. In the present embodiment, a section of 500 ms to 800 ms is a feature section in the WWVB marker. Further, the data value (feature value) of the feature section is “−1” indicating a low level.

  In addition, in the code “0”, the section (see the code 1712) extending from 200 ms to 500 ms is the high level (data value “1”). In this section, the unique value “1” that is different from the other codes “1”. have. On the other hand, in the code “1”, an interval from 200 ms to 500 ms (refer to the symbol 1713) is a low level (data value “−1”). In this interval, a unique value “ -1 ". Therefore, in the codes “0” and “1”, a section of 500 ms to 800 ms is a feature section. The data values (feature values) in the feature section are “1” and “−1”, respectively.

  Therefore, in each of the minute head position detection and code decoding processes, it is possible to execute the process using the data value of the feature section as in the case of JJY.

  FIG. 18 is a diagram for explaining a feature section in each code of MSF. As shown in FIG. 18, also in the MSF code, the marker (see reference numeral 1801), the reference numeral “00” (see reference numeral 1802), the reference numeral “01” (see reference numeral 1803), the reference numeral “10” (see reference numeral 1804), and In the code “11” (see the code 1805), there is a section having a unique value whose value is different from the values of other codes.

  In the marker, an interval from 300 ms to 500 ms (see reference numeral 1811) is a low level (data value “−1”), and this interval has a unique value “−1” different from others. In the present embodiment, a section of 300 ms to 500 ms is a feature section in the MSF marker. Further, the data value (feature value) of the feature section is “−1” indicating a low level.

  In addition, in the code “00”, the section (see the code 1812) from 100 ms to 300 ms is the high level (data value “1”), and has a unique value “1” different from other codes in this section. ing. In the code “01”, the high level (data value “1”) in the section from 100 ms to 200 ms (refer to the code 1813), and the low level (data value “−1”) in the section from 200 ms to 300 ms (see the code 1814). In the above section, there are combinations of values different from other codes (the first half is “1” and the second half is “−1”). In the code “10”, the low level (data value “−1”) in the section from 100 ms to 200 ms (refer to the code 1815), and the high level (data value “1”) in the section from 200 ms to 300 ms (see the code 1816). In the above section, there is a combination of values different from other codes (the first half is “−1” and the second half is “1”). Further, in the code “11”, the section (refer to the code 1817) from 100 ms to 300 ms is the low level (data value “−1”). In this section, the unique value “−1” different from the other codes is set. Have. Therefore, a section extending from 100 ms to 300 ms is a feature section. Each data value is as shown in FIG.

  In the MSF, the data values of the feature sections of the code “00” to the code “11” are not constant. For example, for the code “01”, the first half data value of the feature section is “1” and the second half data value is “−1”. Therefore, in the decoding process of the code according to the MSF standard, the data value belonging to the feature section of the input waveform data and the corresponding data value belonging to the feature section of the predicted waveform data, as in the detection of the minute start position, To obtain a calculated value, find a sum of the calculated values, and obtain a covariance value based on the obtained sum.

  Next, a second embodiment of the present invention will be described. In the above-described embodiment, when the second pulse position is detected, the first value “−1” indicating the low level only for a predetermined interval in front of the point rising from the low level to the high level (the oldest side in time). And a second value “1” indicating a high level only for a predetermined section behind the point (a new side in time), and “0” for other than the predetermined section before and after the point. Predicted waveform data having another third value indicating the above is used. However, the present invention is not limited to this, and predicted waveform data in a form in which a code constituting a time code, for example, a code “0” is repeated may be used.

  FIG. 19 is a flowchart showing in more detail the detection of the second pulse position (second synchronization) according to the second embodiment of the present invention. FIG. 20 is a diagram schematically illustrating second pulse position detection processing according to the second embodiment. As shown in FIG. 19, the predicted waveform data generation unit 23, according to the instruction of the CPU 11, has a unit time length of 4 units (4 seconds) as described above, 50 ms each, and the head of the code “0” (low level). 20 pieces of predicted waveform data P (1, j) to P (20, j) whose positions are shifted from each other (step 1901, reference numeral 2001 in FIG. 20).

  Next, the feature section extraction unit 28 extracts feature sections of the predicted waveform data P (1, j) to P (20, j) (step 1902). As described above, in the code “0”, as shown in FIG. 14B, the feature section extends from the head of the code to the position of 500 ms to the position of 800 ms, and the feature value in the feature section is “1”. Is. Therefore, the feature section extraction unit 28 specifies the position of 500 ms to 800 ms from the beginning of the code “0” in each of the predicted waveform data P (1, j) to P (20, j).

For example, the feature section of the predicted waveform data P (1, j) is
P (1,10) -P (1,16), P (1,30) -P (1,36), P (1,50) -P (1,56), and P (1,70) To P (1,76), and the characteristic section of the predicted waveform data P (2, j) is
P (2,11) -P (2,17), P (2,31) -P (2,37), P (2,51) -P (2,57), and P (2,71) It becomes a section of data values of .about.P (2,77).

In general, the characteristic section of the predicted waveform data (p, j) is
P (p, 10 + (p-1)) to P (p, 16 + (p-1)), P (p, 30 + (p-1)) to P (p, 36 + (p-1)), P ( p, 50 + (p-1)) to P (p, 56 + (p-1)) and P (p, 70 + (p-1)) to P (p, 76 + (p-1)) It becomes the section. In P (p, j), when the right number j> 80, (j−80) is obtained. Also, the data value (feature value) of the feature section is “1” as shown in FIG.

  Further, in accordance with an instruction from the CPU 11, the waveform cutout unit 24 cuts out data of 4 unit time length (4 seconds) from the received waveform data buffer 22 to generate input waveform data Sn (j) (step 1903, FIG. 20 code 2011). Also in the second embodiment, since 20 samples of data are acquired per second, Sn (j) is data including 80 samples. Next, the CPU 11 initializes a parameter p for specifying the predicted waveform data to “1” (step 1904).

Next, the feature section extraction unit 27 acquires the data value of the feature section corresponding to the feature section of the predicted waveform data in the input waveform data Sn (j) (step 1905). In step 1905, corresponding to the predicted waveform data P (p, j), the data value of the feature section of the input waveform data Sn (j) is
Sn (10+ (p-1)) to Sn (16+ (p-1)), Sn (30+ (p-1)) to Sn (36+ (p-1)), Sn (50+ (p-1)) to Sn (56+ (p-1)) and Sn (70+ (p-1)) to Sn (76+ (p-1)).

  Next, the correlation value calculation unit 25 obtains a calculated value by multiplying the data value of the feature section of Sn (j) and the corresponding data value (feature value) of the feature section of P (p, j). Based on the calculated value, a covariance value is calculated (step 1906). As described above, the data value of the feature section of the predicted waveform data P (p, j) is “1”. Therefore, in the multiplication of the data value of the feature section of Sn (j) and the corresponding data value (feature value) of the feature section of P (p, j), the data value of the feature section of Sn (j) is accumulated. It is only necessary to calculate and obtain ΣSn (j).

  Further, since the average value Sm of the input waveform data can be considered as “0”, Sm * Pm can be considered as “0”. Therefore, the covariance value C (p) can be obtained simply by ΣSn (j). In step 1906, the correlation value calculation unit 25 calculates an accumulated value Ca (p) of the correlation value C (p).

  Next, it is determined whether the parameter p is smaller than “20” (step 1907). If the parameter p is smaller than “20” (No in step 1907), the parameter p is incremented (step 1908), and the process returns to step 1905. . When the covariance values C (1) to C (20) are acquired for all parameters p (Yes in step 1907), it is determined whether the covariance values have been calculated a predetermined number of times (step 1909). If it is determined No in step 1909, the process returns to step 1902. Steps 1910 to 1912 in FIG. 19 are the same as steps 908 to 910 in FIG.

  In the present embodiment, the direct current component is removed from the input signal from the receiving circuit 16, and the output indicating either the value larger than the average value or the value smaller than the average value is centered on the average value of the input signal. By providing the average value tracking circuit 19 that generates a signal, the correlation value calculation unit 25 multiplies the data value of the input waveform data by the data value of the predicted waveform data to calculate the calculated value, and The sum can be calculated as a correlation value corresponding to the covariance value between the input waveform data and the predicted waveform data, and calculation of the average value of the input waveform data and the average value of the predicted waveform data can be omitted. . Therefore, it is possible to reduce the amount of calculation in calculating the covariance value and reduce the calculation time.

  Further, in the present embodiment, the average value tracking circuit 19 generates a signal corresponding to the average value Vth of the input signal, a filter circuit including the resistor 301 and the capacitor 302, and a signal corresponding to the average value and the input. A comparator 303 that compares the signal and outputs an output signal indicating the comparison result. According to the present embodiment, it is possible to generate an output signal from which the DC component of the input signal is removed with a circuit having a simple configuration.

  Further, in the embodiment, the predicted waveform data generation unit 23 is configured such that each sample point is a first value indicating a low level in any predetermined section before and after the signal level change point, and before and after the change point. It takes any one of the second value indicating the high level in any other predetermined section and the third value in other sections other than the predetermined section, and has the same time length as the input waveform data, and A plurality of predicted waveform data whose waveform shapes are sequentially shifted by a predetermined sample are generated. Here, the calculated value of the third value and the first value or the second value is a value that does not affect the correlation value, for example, “0”. Further, the CPU 11 specifies the second start position in the time code based on the predicted waveform data indicating the optimum value.

  Therefore, according to the present embodiment, it is possible to accurately specify the second head position while realizing the reduction of the calculation amount and the calculation time.

  Also, according to the present embodiment, the input waveform data generation unit 21 generates a plurality of input waveform data having a plurality of unit time lengths starting from each of the start positions of seconds, and generates predicted waveform data. The unit 23 generates predicted waveform data having the same time length as the input waveform data, the waveform shape including a predetermined code before and after the start position of the minute in the time code. In addition, the feature section extraction unit 28 acquires, from the predicted waveform data, a feature value of a feature section having a specific and constant data value different from other codes in a predetermined code, and the feature section extraction unit 27 receives the input waveform. The data value of the feature section corresponding to the feature section of the predicted waveform data is acquired from the data. The correlation value calculation unit 25 calculates a calculated value by multiplying the data value of the feature section of each of the plurality of input waveform data by the feature value of the feature section of the predicted waveform data, and the CPU 11 indicates the optimum value. Based on the input waveform data, the minute start position in the time code is specified.

  According to the present embodiment, when calculating the covariance value, in addition to omitting the calculation of the average value, it is only necessary to multiply the data value in the feature section, so that the amount of calculation can be further reduced. Become.

  Furthermore, in the present embodiment, the input waveform data generation unit 21 has a plurality of unit time lengths starting from a position corresponding to the start position of a predetermined code sequence that constitutes time information included in the time code. Is generated, and the predicted waveform data generation unit 23 generates a plurality of predicted waveform data having the same time length as the input waveform data and indicating a predetermined code string. Further, the feature section extraction unit 28 acquires, from the predicted waveform data, the feature value of the feature section having a unique and constant data value different from other codes in each of the codes constituting the predetermined code sequence, The section extraction unit 27 acquires the data value of the feature section corresponding to the feature section of the predicted waveform data from the input waveform data. The correlation value calculation unit 25 calculates a calculated value by multiplying the data value of the feature section of the input waveform data by the feature value of each of the plurality of predicted waveform data, and the CPU 11 indicates the optimum value. The time information included in the time code is acquired based on the sequence of codes.

  Therefore, according to the present embodiment, in calculating the covariance value, in addition to omitting the calculation of the average value, it is only necessary to multiply the data value in the feature section, so that the amount of calculation can be further reduced. It becomes possible.

  The present invention is not limited to the above embodiments, and various modifications can be made within the scope of the invention described in the claims, and these are also included in the scope of the present invention. Needless to say.

In the embodiment, in the detection of the second pulse position, the first value indicating the low level of the input waveform data and the predicted waveform data is set to “−1”, and the second value indicating the high level is set to “1”. The third value other than the above was set to “0”. In the calculation of the minute head position and the decoding of the code, the first value indicating the low level of the input waveform data and the predicted waveform data is set to “−1”, and the second value indicating the high level is set to “1”. . However, it is not limited to these values. The first value and the second value may be as follows.
(1) When the first value appears in the input waveform data and the first value appears in the predicted waveform data, or the second value appears in the input waveform data and the second value in the predicted waveform data A predetermined positive calculation value indicating that there is a positive correlation by calculating the first value and the first value or the second value and the second value when the value of Is calculated. That is, when the same value appears in the input waveform data and the predicted waveform data, a predetermined positive calculation value is calculated.
(2) When the first value appears in the input waveform data and the second value appears in the predicted waveform data, or the second value appears in the input waveform data and the first value in the predicted waveform data When a value of 現 れ appears, a predetermined negative calculation value indicating that there is a negative correlation is calculated by calculating the first value and the second value. That is, when different values appear in the input waveform data and the predicted waveform data, a predetermined negative calculation value is calculated. Further, it is desirable that the predetermined negative calculation value is obtained by setting the sign of the predetermined positive value to “− (minus)”.

  In the calculation of the second pulse position, the third value may not be “0”, but when the first value is calculated and when the second value is calculated, the correlation such as the covariance value is correlated. It must be a value that does not affect the value.

10 radio time clock 11 CPU
12 Input unit 13 Display unit 14 ROM
15 RAM
DESCRIPTION OF SYMBOLS 16 Reception circuit 17 Internal clock circuit 18 Signal comparison circuit 19 Average value tracking circuit 21 Input waveform data generation part 22 Received waveform data buffer 23 Predicted waveform data generation part 24 Waveform extraction part 25 Correlation value calculation part 26 Correlation value comparison part 27, 28 Feature section extraction unit 29 Data value accumulation unit 30 Accumulation value buffer

Claims (6)

Receiving means for receiving a standard time radio wave including a time code representing time information;
An average value follow-up signal that removes a DC component from the input signal from the receiving means and generates an output signal indicating either a value larger than the average value or a value smaller than the average value around the average value of the input signal Generating means;
The output signal including the time code output from the average value tracking signal generation means is sampled at a predetermined sampling period, and the data value at each sample point indicates a first value indicating a low level and a high level. Input waveform data generating means for generating any one of the second values and generating input waveform data having one or more unit time lengths;
The data value of each sample point takes either the first value or the second value, has the same time length as the input waveform data, and the waveform shape is a predetermined code in the time code Predicted waveform data generating means for generating predicted waveform data including:
A calculated value is calculated by multiplying the data value of the input waveform data and the data value of the predicted waveform data, and the sum of the calculated values is equivalent to a covariance value between the input waveform data and the predicted waveform data. Correlation value calculating means for calculating as a correlation value;
A correlation value comparison unit that compares the correlation value calculated by the correlation value calculation unit and calculates an optimum value thereof;
And a control unit that acquires time information represented by the time code based on the optimum value.   The average value follow-up signal generation means compares the average value signal generation means for generating a signal corresponding to the average value of the input signal, the signal corresponding to the average value and the input signal, and shows the comparison result The time information acquisition apparatus according to claim 1, further comprising a comparison unit that outputs an output signal. The predicted waveform data generation means is configured such that each sample point has a first value indicating a low level in any predetermined section before and after the change point of the signal level, and in any other predetermined section before and after the change point. It takes either a second value indicating a high level and a third value in a section other than the predetermined section, has the same time length as the input waveform data, and the waveform shape is Generate multiple predicted waveform data that are sequentially shifted by a predetermined sample,
In the calculation by the correlation value calculating means, the calculation value of the third value and the first value or the second value is a value that does not affect the correlation value,
3. The time information acquisition apparatus according to claim 1, wherein the control unit specifies a second head position in the time code based on predicted waveform data indicating the optimum value. 4. The input waveform data generating means generates a plurality of input waveform data having a plurality of unit time lengths starting from each of the first positions of the seconds;
The predicted waveform data generating means generates predicted waveform data having the same time length as the input waveform data, the waveform shape including a predetermined code before and after the start position of the minute in the time code,
Predicted waveform feature section extracting means for acquiring feature values of feature sections having unique and constant data values different from other codes in the predetermined code from the predicted waveform data;
Input waveform feature section extraction means for obtaining a data value of a feature section corresponding to the feature section of the predicted waveform data from the input waveform data,
The correlation value calculating means multiplies each of the plurality of input waveform data by the data value of the feature section and the feature value of the feature section of the predicted waveform data to calculate a calculated value,
4. The item information acquisition apparatus according to claim 3, wherein the control unit specifies a minute start position in the time code based on input waveform data indicating the optimum value. The input waveform data generation means generates input waveform data having a plurality of unit time lengths, starting from a position corresponding to a start position of a predetermined code sequence, which constitutes time information included in the time code. ,
The predicted waveform data generation means generates a plurality of predicted waveform data having the same time length as the input waveform data, indicating the predetermined code sequence,
In each of the codes constituting the predetermined code string, a predicted waveform feature section extracting means for acquiring a feature value of a feature section having a unique and constant data value different from other codes from the predicted waveform data;
Input waveform feature section extraction means for obtaining a data value of a feature section corresponding to the feature section of the predicted waveform data from the input waveform data,
The correlation value calculation means calculates the operation value by multiplying the data value of the feature section of the input waveform data by the feature value of each of the plurality of predicted waveform data,
5. The time information acquisition apparatus according to claim 3, wherein the control unit acquires time information included in the time code based on the code string indicating the optimum value. 6. The time information acquisition device according to claim 5;
An internal time measuring means for measuring the current time by an internal clock;
Time correction means for correcting the current time measured by the internal time measurement means according to the current time acquired by the time information acquisition device;
A radio-controlled timepiece comprising: time display means for displaying the current time measured by the internal time measuring means or corrected by the time adjusting means.

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