JP2009238283A - Optical information reproducing system and information reproducing method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an information reproducing system for improving detection performance. <P>SOLUTION: An optical information reproducing system includes a Viterbi detector, and an average level calculator. The Viterbi detector detects a binary signal through Viterbi detection by using 2<SP>M</SP>reference values of branch metrics at maximum based on a reproduced signal reproduced from an information recording medium when a constraint length of Viterbi detection is M (M is an integer of two or more), and the average level calculator includes a low pass filter for updating any one of the 2<SP>M</SP>reference values for each predetermined period based on the reproduced signal and a time series pattern of the binary signal for M clock time points. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to an optical information reproducing apparatus and information reproducing method, and more particularly to an information reproducing apparatus and information reproducing method using a PRML (Partial Response Maximum Likelihood) method.

  A signal processing technique called a PRML (Partial Response Maximum Likelihood) system is used as an information reproducing system in high-density recording such as an optical disk device. The PRML system is a system that combines partial response waveform equalization and maximum likelihood detection. In the PRML system, the maximum likelihood detection is performed after correcting the reproduction signal by waveform equalization in order to maximize the characteristics of the maximum likelihood detector considering the reproduction channel.

The PR method is expressed as PR (h ₀ , h ₁ ,..., H _N−1 ), where N is the constraint length. For the recording data string a _k = “010... 0”, the output value is “0h ₀ h ₁ ... H” by an equalizer represented by a FIR (Finite Impulse Response) filter. Waveform equalization using intersymbol interference is performed so that _N-1 0. Thereby, a random recording data string becomes a multi-valued data string after equalization. The greater the constraint length N, the more multivalue. The constraint length N and h _i (i = 0, 1,..., N−1) are changed according to the characteristics of the reproduced signal due to the difference in recording density and the like. In the early days when the PRML system was adopted, the PR (1, 1) system with a constraint length N = 2 was used. However, in recent optical disk devices aiming at higher density, PR (1, 2, 2, 1) is used. ) Method and PR (1, 2, 2, 2, 1) method are becoming mainstream. FIG. 1 shows output waveforms of the PR (1, 2, 2, 1) system and the PR (1, 2, 2, 2, 1) system for the recording waveform. FIG. 2A shows an eye pattern of the PR (1, 2, 2, 1) system, and FIG. 2B shows an eye pattern of the PR (1, 2, 2, 2, 1) system. In this manner, the PR system output signal is multi-valued based on the recording data string.

Maximum likelihood detector constraint length N, the recording data sequence _{a k-N + 1, a} k-N + 2 of length N-1, _..., with respect to the state at time k-1 based on the pattern of _{a k-1} Then, detection is performed based on the state transition by the input signal sequence y _{k at} time k. Usually, the number of consecutive 1's and the number of consecutive 0's are limited in a recording data string recorded on an information recording medium by appropriate encoding. That is, the encoding method is characterized by a minimum run length d that is the minimum number of consecutive _1s or 0s of the recording data sequence _ak . For example, the state transition in the case of d = 0 in the simplest PR (1, 1) method with a constraint length N = 2 will be described. Assuming that the recording data string a _k = 0 is assigned to the state S ₀ and the recording data string a _k = 1 is assigned to the state S ₁ , the state transition is adjusted to the output of the equalizer as shown in FIG. Two-state transition is performed with a ternary reference value of 0, 1, 2 ″. In general, a reference value from which a DC component is removed is used, and thereafter, “0, 1, 2” is expressed as “−1, 0, 1” according to this notation.

FIG. 4 shows a trellis diagram in which the state transition diagram shown in FIG. 3 is developed on the time axis. The length of the path at each time is called a branch metric. Branch metrics that transition from the state S _i (i = 0, 1) at the time k−1 to the state S _j (j = 0, 1) at the time k are given by Equations 1-1 to 1-4.
l _k ⁰⁰ = (y _k -(-1)) ² ... Formula 1-1
l _k ⁰¹ = (y _k −0) ² ... Formula 1-2
l _k ¹⁰ = (y _k −0) ² ... Formula 1-3
l _k ¹¹ = (y _k −1) ² Formula 1-4

In the Viterbi algorithm, at a certain time k on the trellis diagram, when each path passes from the sum of the path lengths up to time k−1 and the value of the input signal sequence y _k input at time k The path length of is calculated. Then, an operation for selecting a path having a shorter path length from the paths toward one state is performed. The minimum value of the path length to reach each state at a certain time is called a path metric, and the PR (1, 1) method path metric is given by Expression 2-1 and Expression 2-2.
m _k (S ₀ ) = min {m _k−1 (S ₀ ) + l _k ⁰⁰ , m _n−1 (S ₁ ) + l _k ¹⁰ } Equation 2-1
m _k (S ₁ ) = min {m _k−1 (S ₀ ) + l _k ⁰¹ , m _k−1 (S ₁ ) + l _k ¹¹ } Equation 2-2

m _k (S ₀ ) indicates the minimum value of the length of the path that transitions to the state S ₀ at time k defined by the channel clock. That is, the sum of the path metric until the transition to state S ₀ at time k−1 and the branch metric that transitions from state S ₀ to time S ₀ at time k−1 and state S _{1 at} time k− _1. Of the path metric until the transition to, and the sum of the branch metric that transitions from state S ₁ to time S ₀ at time k−1 at time k−1, the one that is the smallest is selected. At each time, only the paths having the metrics shown in Expressions 2-1 and 2-2 are left as paths having the possibility of becoming the maximum likelihood paths, and the path metrics are updated. If the path left in this way is called a surviving path, and the surviving path is hit in the past, the probability that the paths merge into one at a certain point increases. The merged path is detected as the maximum likelihood path, and detection data is obtained. Even when the constraint length increases, detection data can be obtained by obtaining the maximum likelihood path based on the same principle only by increasing the number of branches.

If the distortion of the pit shape on the information recording medium increases due to the increase in density, nonlinear distortion such as asymmetry occurs in the reproduced waveform. For example, asymmetry occurs mainly depending on the recorded mark shape. FIG. 5 shows an example of a reproduced waveform with asymmetry. In the reproduced waveform with asymmetry, as shown in FIG. 5, a phenomenon in which the positive and negative peak levels corresponding to the pattern density are not symmetrical with respect to the central reference value, that is, the center of the positive and negative peak levels is the pattern. A non-linear phenomenon occurs depending on the density of the material. If the reproduction waveform values for the longest mark and space are I _11H and I _11L, and the reproduction waveform values for the shortest mark and space are I _2H and I _2L , respectively, the asymmetry is
0.5 * [( _I11H + _I11L )-( _I2H + _I2L )] / ( _{I11H- I11L} ) ... Formula 3
Is defined.

  A linear filter such as an FIR filter generally used as an equalizer cannot reduce this non-linearity. Further, the reference value of the Viterbi detector is not set so as to cope with nonlinear distortion such as asymmetry. Therefore, for example, in the PR (1, 1) ML system, the input reference level of the Viterbi detector is “−1, 0, 1”, but in the case of a waveform having asymmetry, the input waveform is “−0.8. , 0.1, 1.2 ". In this case, the errors are different from “0.2, 0.1, 0.2” with respect to the correct reference value, and complete correction cannot be performed by offset correction. If there is an error at each time, there is a high possibility that an incorrect path is selected, and the detection accuracy is deteriorated. Furthermore, since the intersymbol interference of the reproduction signal increases as the recording density increases, a higher-order PRML method may be used to suppress a decrease in detection accuracy. In this case, since the reference value of the Viterbi detector increases and the interval becomes narrow, the deviation becomes relatively large even with the same asymmetry amount, and the reproduction performance deteriorates.

  In order to suppress such deterioration, an adaptive PRML method has been proposed. As for the adaptive PRML system, for example, “ODS '02 Technical Digest, pp 269-271,“ Adaptive Partial-Response Maximum-Likelium Detection Detection in Optical Recording Media ”p. "Detection for High-Density Optical Recording" ".

  An example of the configuration of an information reproducing apparatus using the adaptive PRML method is shown in FIG. The adaptive PRML type information reproducing apparatus includes an optical head 12, an A / D converter (ADC) 14, a PLL circuit 16, an equalizer 22, a Viterbi detector 47, an average level calculator 37, a tap. A coefficient calculator 24 and an equalization target calculator 57 are provided to reproduce information recorded on the optical disc medium 10. As shown in FIG. 7, the average level calculator 37 includes a discriminator 35 and an averaging circuit 38.

  The optical disk medium 10 is rotated at a constant angular velocity rotation or a constant linear velocity rotation by a spindle motor (not shown). In the optical head 12, the distance between the disk surface and the objective lens and the radial position of the disk guide groove and the focused spot are accurately controlled by a servo circuit (not shown). The information mark recorded on the screen is irradiated. Reflected light from the recording surface of the optical disk medium 10 changes in reflectance or polarization depending on the presence or absence of an information mark, and this is detected by a detector (not shown) mounted on the optical head 12 to obtain a reproduction signal. .

  The reproduction signal is converted into a digital signal by the A / D converter 14. The PLL circuit 16 performs phase control so as to synchronize with the input channel frequency based on the output of the A / D converter 14, and equalizes the data sequence of the resampling signal interpolated from the data sequence of the fixed sampling rate 22 for output. The equalizer 22 equalizes the output of the PLL circuit 16 so as to have a predetermined PR characteristic by the tap coefficient calculated by the tap coefficient calculator 24. The output of the equalizer 22 is supplied to a Viterbi detector 47 and an average level calculator 37. The Viterbi detector 47 performs maximum likelihood detection using the output of the equalization target calculator 57 as a reference value at the time of branch metric calculation in the Viterbi detector 47, and detects a detection data string (record data string) that is a binary signal. .

  In the average level calculator 37, the output of the equalizer 22 is input to the averaging circuit 38, and the detection data string that is the output of the Viterbi detector 47 is input to the discriminator 35. Each discriminator 35 receives a data pattern corresponding to the detected data string (recorded data string). The discriminator 35 compares and determines the detected data string and the data pattern, and outputs the determination result to the averaging circuit 38. The averaging circuit 38 calculates and outputs the average of the output of the equalizer 22 only when a determination result indicating that the detected data string and the data pattern match is output.

  The equalization target calculator 57 receives the detection data string, generates an equalization target signal by convolution of the detection data string and the PR method coefficient, and outputs it to the tap coefficient calculator 24. The tap coefficient calculator 24 calculates and outputs a tap coefficient that minimizes the square error between the output of the PLL circuit 16 and the output of the equalization target calculator 57.

  In the normal PRML system, the reference value used when the Viterbi detector 47 calculates the branch metric is the same value as the target value of the equalizer 22 calculated by convolution of the PR system coefficient and the recording data string. On the other hand, in the adaptive PRML system, the average of the output of the equalizer 22 corresponding to the recording data string calculated by the average level calculator 37, that is, the output value of the equalizer is fixedly used. For example, the reference value at the time of branch metric calculation is “−1, 0, 1” in the normal PR (1, 1) ML system, whereas “−0.8, 0 in the adaptive PRML system. .1, 1.2 ". As a result, maximum likelihood detection is performed with a reference value adapted to a reproduction signal having nonlinearity, and an improvement in reproduction performance is obtained with respect to a normal PRML system.

Further, as shown in FIG. 8, the adaptive PRML information reproducing apparatus includes an optical head 12, an A / D converter 14, a PLL circuit 16, an equalizer 22, a Viterbi detector 47, an average A level calculator 37, a tap coefficient calculator 24, and an equalization target calculator 57 may be provided to reproduce information recorded on the optical disc medium 10. The average level calculator 37 includes a discriminator 35 and an averaging circuit 38. The apparatus as shown in the apparatus and Figure 8 shown in FIG. 6, an input signal W _k of the averaging circuit 38, a method of generating the equalization target signal is different. In the information reproducing apparatus shown in FIG. 6, the input signal of the averaging circuit 38 is the output of the equalizer 22. On the other hand, in the information reproducing apparatus shown in FIG. 8, the input signal of the averaging circuit 38 becomes the output of the PLL circuit 16. The equalization target signal in the information reproducing apparatus shown in FIG. 8 is recorded by the equalization target calculator 58 on the basis of the output of the average level calculator 37 which is the output of the averaging circuit 38 and the recording data string. The output of the average level calculator 37 corresponding to the pattern is generated as an equalization target value and output to the tap coefficient calculator 24.

  Thereby, in the information reproducing apparatus shown in FIG. 8, unlike the information reproducing apparatus shown in FIG. 6, the equalization target value matches the reference value at the time of branch metric calculation. Further, the tap coefficient of the equalizer 22 is calculated based on the output of the PLL circuit 16 and the equalization target value. Since the target value itself is closer to the signal before equalization than in the case of the information reproducing apparatus shown in FIG. 6, good equalization is possible and detection performance can be further improved.

In the adaptive PRML system described above, the output of the average level calculator 37 is calculated by a simple addition average. For example, when the data length of the recording data string referred to in the state transition in the Viterbi detector 47 is 5, the reference value x [00000] for the recording data string pattern “00000” is equal to that of the equalizer 22 in FIG. output, when the output of the PLL circuit 16 in FIG. 8 and an input _{w k} of the average level computing unit 37, is determined by equation 4.

X [00000] = E [w _k (00000)] ... Formula 4
The detected data sequence detected by the Viterbi detector 47 is not necessarily the same as the recorded data sequence recorded on the optical disc medium 10, but is the same. Here, E [w _k (00000)] is an operator that means taking a time average of w _k (00000). In such a method calculated by simple addition averaging, the detection performance may be deteriorated when amplitude fluctuation or offset occurs.

  Japanese Patent Laid-Open No. 2003-263746 discloses a technique related to an information reproducing apparatus for reproducing information recorded on a recording medium. The information reproducing apparatus includes detection means, conversion means, correction means, equalization means, maximum likelihood decoding means, ideal waveform generation means, target waveform generation means, and optimization means. The detection means detects information recorded on the recording medium and outputs a detection signal. The conversion means converts the detection signal output from the detection means into a digital signal. The correction unit corrects the digital signal converted by the conversion unit according to the parameter. The equalization means performs a partial response equalization process on the corrected digital signal corrected by the correction means based on a predetermined coefficient, and outputs an equalization signal. The maximum likelihood decoding unit performs a maximum likelihood decoding process on the equalized signal output by the equalizing unit based on the reference level, and outputs a decoded signal. The ideal waveform generation means generates and outputs an ideal waveform signal in accordance with the equalization signal output from the equalization means. The target waveform generation means generates and outputs a target waveform signal that is a target of the equalization means by changing at least one of the levels of the ideal waveform signal output by the ideal waveform generation means. The optimization means calculates an error between the target waveform signal output from the target waveform generation means and the equalization signal output from the equalization means, and corrects the parameters of the correction means and the predetermined coefficient of the equalization means so that the error is minimized. And at least one of the reference levels of the maximum likelihood decoding means is optimized.

  Japanese Unexamined Patent Application Publication No. 2006-221719 discloses a technique of a PRML decoding device. The PRML decoding device includes input means, waveform equalization means, PRML decoding means, conversion means, and adjustment means. The input means inputs a data signal including fixed pattern data. The waveform equalization means performs waveform equalization processing corresponding to a predetermined partial response class on the data signal input by the input means. The PRML decoding means sets each reference level data according to the predetermined partial response class, and performs a partial response maximum likelihood decoding process using the reference level data for the data signal input through the waveform equalizing means. Thus, binarized data is generated. The conversion means converts the fixed pattern data into ideal level fixed pattern data expressed by ideal reference level data assumed in a predetermined partial response class by performing predetermined calculation on the fixed pattern data prepared in advance. To do. The adjustment unit is configured to input fixed pattern data input based on a result of comparing each value of the fixed pattern data input via the waveform equalization unit with each value of the ideal level fixed pattern data obtained by the conversion unit. Is assigned to each value of ideal reference level data. Then, the adjusting means adjusts the value of each reference level data set in the PRML decoding means based on the result of performing predetermined statistical processing for each distributed value.

  Japanese Patent Application Laid-Open No. 9-330565 discloses a recording / encoding unit, a precoding unit, a recording / reproducing unit, an amplifying unit, a removing unit, an A / D converting unit, and a PR equalizing unit. A digital magnetic recording / reproducing apparatus including means for performing maximum likelihood decoding and means for restoring is disclosed. The digital recording / reproducing apparatus further includes a delay unit, a D / A conversion unit, and a subtracting unit. The recording and encoding means records and encodes the input digital signal. The means for precoding precodes the code. The recording / reproducing means records the precode output signal on the recording medium and reproduces the recorded signal. The amplifying means amplifies the analog signal from the recording / reproducing means. The removing means removes unnecessary noise from the output signal of the amplifying means. The A / D conversion means converts the analog signal from which unnecessary noise has been removed into a digital signal. The PR equalization means equalizes the digital signal into a partial response response waveform. The means for performing maximum likelihood decoding performs maximum likelihood decoding using the reproduced signal obtained by the PR equalizing means. The restoring means restores the original data even if the result obtained by the maximum likelihood decoding means is recorded and decoded. The delay means delays the equalized output for a predetermined time. The D / A conversion means includes a nonlinear distortion / TA compensation means to convert the expected value of the level fluctuation component output from the nonlinear distortion / TA compensation means into an analog signal. The subtracting means subtracts the analog signal from the analog signal from which unnecessary noise has been removed on the input side of the A / D conversion means. On the other hand, the reproduced signal including the expected value of the nonlinear distortion component is output from the nonlinear distortion / TA compensation means to the maximum likelihood decoding means, and the maximum likelihood decoding means performs a metric calculation using this as a reference signal.

JP 2003-263746 A JP 2006-221719 A JP-A-9-330565 ODS '02 Technical Digest, pp 269-271, “Adaptive Partial-Response Maximum-Likelihood Detection in Optical Recording Media” ISO'07 Technical Digest, pp 150-151, “New Adaptive PRML Detection for High-Density Optical Recording”

  An object of the present invention is to provide an information reproducing apparatus with improved detection performance.

In an aspect of the present invention, the optical information reproducing apparatus includes a Viterbi detector and an average level calculator. The Viterbi detector uses a reference value of a maximum of 2 ^M branch metrics based on a reproduction signal reproduced from an information recording medium when the constraint length of Viterbi detection is M (M is an integer of 2 or more). Viterbi detection is performed to detect a binary signal. The average level calculator includes a low-pass filter that updates any one of 2 ^M reference values for each predetermined period based on a reproduction signal and a time-series pattern for M times of a binary signal.

In another aspect of the present invention, an information reproducing method is an information reproducing method for reproducing information recorded on an information recording medium in an optical information reproducing device, and includes a reproducing step, a Viterbi detecting step, and an average level calculating step. It comprises. In the reproducing step, a reproduction signal is reproduced from the information recording medium. In the Viterbi detection step, when the constraint length of Viterbi detection is M (M is an integer equal to or greater than 2), Viterbi detection is performed using reference values of up to 2 ^M branch metrics based on the reproduction signal, A binary signal is detected. In the average level calculating step, any one of 2 ^M reference values is updated every predetermined period based on the reproduction signal and the time-series pattern for M times of the binary signal.

  According to the present invention, it is possible to provide an information reproducing apparatus with improved detection performance. In particular, the detection performance can be improved in the case where the amplitude variation or offset of the reproduction signal occurs.

(First embodiment)
A first embodiment of the present invention will be described with reference to the drawings. FIG. 9 shows the configuration of an adaptive PRML information reproducing apparatus according to the first embodiment of the present invention. The information reproducing apparatus includes an optical head 12, an A / D converter 14, a PLL circuit 16, an equalizer 22, a Viterbi detector 41, an average level calculator 31, a tap coefficient calculator 24, and the like. And a computerized target calculator 51.

  The optical disk medium 10 is rotated at a constant angular velocity rotation or a constant linear velocity rotation by a spindle motor (not shown). In the optical head 12, the distance between the disk surface and the objective lens and the radial position of the disk guide groove and the focused spot are accurately controlled by a servo circuit (not shown). The information mark recorded on the screen is irradiated. Reflected light from the recording surface of the optical disk medium 10 changes in reflectance or polarization depending on the presence or absence of an information mark, and this is detected by a detector (not shown) mounted on the optical head 12 to obtain a reproduction signal. .

  The reproduction signal is converted into a digital signal by the A / D converter 14. The PLL circuit 16 performs phase control based on the output of the A / D converter 14 so as to synchronize with the input channel frequency. The PLL circuit 16 outputs the data sequence of the resampling signal interpolated from the data sequence of the fixed sampling rate to the equalizer 22. The equalizer 22 equalizes the output of the PLL circuit 16 so as to have a predetermined PR characteristic and outputs it to the Viterbi detector 41. In the equalizer 22, the tap coefficient calculated by the tap coefficient calculator 24 is used. The predetermined PR characteristic is preferably set from the outside of the apparatus. The Viterbi detector 41 performs maximum likelihood detection using the output of the equalizer 22 as a reference value at the time of branch metric calculation in the Viterbi detector 41, and detects and outputs a detection data string (recording data string) that is a binary signal. To do.

  The average level calculator 31 takes in the data string output from the equalizer 22 and the detected data string (recorded data string) output from the Viterbi detector 41, and determines the branch metric corresponding to the pattern of the detected data string. A reference value is calculated and output to the Viterbi detector 41. As shown in FIG. 10, the average level calculator 31 includes a discriminator 35 and a low-pass filter (LPF: Low Pass Filter) 36. The number of discriminators 35 and low-pass filters 36 is the maximum number of branch metric reference values of the Viterbi detector.

  The equalization target calculator 51 takes in the detection data string (recording data string) output from the Viterbi detector 41, and generates an equalization target signal by convolution of the detection data string (recording data string) and the PR method coefficient. And output to the tap coefficient calculator 24. The tap coefficient calculator 24 calculates a tap coefficient based on the resampled data string output from the PLL circuit 16 and the equalization target signal output from the equalization target calculator 51 to thereby equalize the equalizer. 22 for output. This tap coefficient is calculated so that the square error between the resampled data string and the equalization target signal is minimized. A configuration in which the order of the A / D converter 14 and the PLL circuit 16 is reversed may be employed. A pre-equalizer that corrects the frequency characteristics of the signal may be provided in the signal path that reaches the equalizer 22.

  Next, the operation of the average level calculator 31 will be described. The average level calculator 31 calculates a reference value when the Viterbi detector 41 calculates a branch metric based on the data string output from the equalizer 22 and the recording data string output from the Viterbi detector 41. . The detection data string detected by the Viterbi detector 41 is not necessarily the same as the recording data string recorded on the optical disc medium 10, but will be described here as being the same.

  As shown in FIG. 10, the average level calculator 31 includes a data string output from the equalizer 22 and a detection data string (hereinafter referred to as a recording data string) output from the Viterbi detector 41. It is input with the period of. The discriminator 35 takes in the detection data string output from the Viterbi detector 41 and the pattern of the recording data referred to in each state transition. The discriminator 35 discriminates whether or not the data pattern of the data length M in the recording data string output from the Viterbi detector 41 matches the recording data pattern referenced in each state transition. The discriminator 35 outputs the discrimination result to the low pass filter 36. The low-pass filter 36 takes in the data string output from the equalizer 22 and the discrimination result output from the discriminator 35. When it is shown that the discrimination results of the discriminator 35 match, the low pass filter 36 performs a filter operation based on the data string output from the equalizer 22.

If the recording data length M is 5 and the minimum run length d is 1, there are 16 patterns of recording data strings, and the Viterbi detector 41 makes a state transition as shown in FIG. In FIG. 11, the subscript of the state S indicates the pattern “a _k−4 , a _k−3 ,..., A _k−1 ” of the recording data string in each state. The output of the equalizer 22 with respect to the pattern “a _{k−M + 1} , a _{k−M + 2} ,..., A _k−1 ” of the recording data string is _represented as w _k ( _{ak−M + 1} a _{k−M + 2} ... A _k−1 ). When the update coefficient is α (0 <α ≦ 1), the reference value x _{n, k} for the pattern n of the recording data sequence is
_{xn, k} = [alpha] _{.xn, k-1} + (1- [alpha]). _wk (when pattern matches) Equation 5-1
_{xn, k} = _{xn, k-1} (when pattern does not match) Equation 5-2
It is calculated by.

By appropriately setting the update coefficient α, it is possible to control the follow-up speed when the amplitude variation or offset of the reproduction signal occurs. That is, the reference value x _k is easily affected by a change in the value of the output pattern w _k of the equalizer 22 by reducing the value of the update coefficient α. Further, an update coefficient α may be provided for each pattern of the recording data string so that a plurality of values can be set as the update coefficient α _n .

The reference values x _{n, k} for all the state transitions are obtained by the respective low-pass filters 36 and are output from the average level calculator 31. In the normal PRML system, for example, the reference value of the pattern “00111” and the reference value of “11100” match the recording data string, and the reference values are degenerated in nine ways. In the case of the present invention, for example, an OR circuit is arranged in the preceding stage of the discriminator 35 for the patterns “00111” and “11100” of the recording data string, and the reference values for both patterns are calculated, so that nine reference values are obtained. It can also be reduced.

(Second Embodiment)
As shown in FIG. 12, the information reproducing apparatus according to the second embodiment of the present invention has an input signal to the average level calculator 31 as compared with the information reproducing apparatus according to the first embodiment, The method for generating the equalization target signal is different. That is, in the information reproducing apparatus according to the first embodiment, the average level calculator 31 receives the equalized signal output from the equalizer 22, whereas the average level calculator 31 relates to the second embodiment. In the information reproducing apparatus, a signal output from the PLL circuit 16 is input. In the information reproducing apparatus according to the second embodiment, the equalization target signal is generated by the equalization target calculator 52 that inputs the output of the average level calculator 31 and the recording data string. The equalization target calculator 52 selects the output of the average level calculator 31 corresponding to the recording data string pattern and outputs it as an equalization target value.

  As described above, in the second embodiment, unlike the first embodiment, the equalization target value coincides with the reference value at the time of branch metric calculation. Further, the tap coefficient calculator 24 calculates the tap coefficient of the equalizer 22 using the output data string of the PLL circuit 16 and the equalization target value. Since the target value itself is close to the signal before equalization, good equalization is possible, and detection performance can be further improved.

  Next, an example is shown about the detection performance of the information reproduction apparatus of this invention. FIG. 13 shows the relationship (error rate characteristic) between the update coefficient α and the error rate. In FIG. 13, the update coefficient α is shown converted into a cutoff frequency. Two types of reproduction signals are given to the information reproducing apparatus according to the first embodiment and the information reproducing apparatus according to the second embodiment, respectively, and the relationship between the cut-off frequency and the error rate (BER: bit error rate) Was measured. The two types of reproduction signals are a reproduction signal obtained by reproducing information recorded on a rewritable recordable optical disk medium having a capacity of 22 gigabytes with an optical head having a wavelength of 405 nm and a lens numerical aperture of 0.65, and a reproduction signal having a capacity of 15 gigabytes This is a reproduction signal obtained by super-resolution reproduction of information recorded on the optical disk medium with an optical head having a wavelength of 405 nanometers and a lens numerical aperture of 0.32.

  As shown in FIG. 13, the optimum cut-off frequency differs depending on the reproduction waveform and the configuration of the information reproduction apparatus, but a good error rate performance can be obtained if it is 10 kHz or more and 3 MHz or less.

  As described above, according to the present invention, the reference value at the time of branch metric calculation of the Viterbi detector 41 and the equalization target value of the equalizer 22 are set for each channel clock according to the characteristics of the reproduced signal instead of a fixed value. calculate. Therefore, detection performance can be improved in the case where an amplitude variation or offset of the reproduction signal occurs.

These are output waveforms of the PR (1, 2, 2, 1) method and the PR (1, 2, 2, 2, 1) method for the recording waveform. It is a PR (1, 2, 2, 1) type eye pattern. This is an eye pattern of the PR (1, 2, 2, 2, 1) system. It is a state transition diagram of a Viterbi detector in the PR (1, 1) system. It is a trellis diagram of a Viterbi detector in the PR (1, 1) system. It is a figure which shows the example of the reproduction | regeneration waveform with asymmetry. It is a figure which shows the structure of the information reproduction apparatus of a related adaptive PRML system. It is a figure which shows the structure of the average level calculator of the information reproduction apparatus of a related adaptive PRML system. It is a figure which shows the other structure of the information reproduction apparatus of a related adaptive PRML system. It is a figure which shows the structure of the information reproduction apparatus which concerns on the 1st Embodiment of this invention. It is a figure which shows the structure of the average level calculator of the information reproduction apparatus which concerns on the 1st Embodiment of this invention. It is a state transition diagram of the Viterbi detector according to the first embodiment of the present invention. It is a figure which shows the structure of the information reproduction apparatus which concerns on the 2nd Embodiment of this invention. It is a figure which shows the example which measured the relationship between the cutoff frequency and error rate of the low-pass filter in this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Optical disk medium 12 Optical head 14 A / D converter 16 PLL circuit 22 Equalizer 24 Tap coefficient calculator 31, 37 Average level calculator 35 Discriminator 36 Low pass filter 38 Average circuit 41, 47 Viterbi detectors 51, 52 , 57, 58 Equalization target calculator

Claims (10)

When the constraint length of Viterbi detection is M (M is an integer equal to or greater than 2), Viterbi detection is performed using reference values of up to 2 ^M branch metrics based on a reproduction signal reproduced from an information recording medium. A Viterbi detector for detecting a binary signal;
An average level calculator that updates any one of the 2 ^M reference values at predetermined intervals based on the reproduction signal and a time-series pattern of the binary signal for M times. Optical information reproducing device. And an equalizer for equalizing a reproduction signal reproduced from the information recording medium and outputting an equalized reproduction signal,
The Viterbi detector performs the Viterbi detection based on the equalized reproduction signal,
The average level calculator updates any one of the ^2M reference values for each predetermined period based on the equalized reproduction signal and a time-series pattern for M times of the binary signal. The optical information reproducing apparatus according to claim 1. The time defined by the predetermined period is k, the value determined based on the binary signal pattern is n, the equalized reproduction signal or the reproduction signal is w _k , and the update coefficient is α (0 <α ≦ 1), the reference value x _{n, k} of the branch metric is
x _{n, k} = α · x _{n, k−1} + (1−α) · w _k
The optical information reproducing device according to claim 1 or 2, calculated by: The time defined by the predetermined cycle is k, the value determined based on the binary signal pattern is n, the equalized reproduction signal or the reproduction signal is w _k , and the update coefficient is α _n (0 < When α _n ≦ 1), the reference value x _{n, k} of the branch metric is
x _{n, k} = α · x _{n, k−1} + (1−α) · w _k
The optical information reproducing device according to claim 1 or 2, calculated by: The average level calculator operates as a low-pass filter that inputs the reproduction signal or the equalized reproduction signal and outputs a reference value of the branch metric,
The optical information reproducing apparatus according to claim 1, wherein 0.00015 <f1 / f2 <0.046, where f1 is a cutoff frequency of the low-pass filter and f2 is an input channel frequency. An information reproducing method for reproducing information recorded on an information recording medium in an optical information reproducing apparatus,
Reproducing a reproduction signal from the information recording medium;
When the constraint length of Viterbi detection is M (M is an integer equal to or greater than 2), a binary signal is detected by performing Viterbi detection using a reference value of a maximum of 2 ^M branch metrics based on the reproduction signal. A Viterbi detection step;
An average level calculating step of updating any one of the ^2M reference values for each predetermined period based on the reproduction signal and a time-series pattern corresponding to M times of the binary signal. Information reproduction method. Furthermore, an equalization step for equalizing a reproduction signal reproduced from the information recording medium and outputting an equalized reproduction signal is provided,
The Viterbi detection step includes the step of performing the Viterbi detection based on the equalized reproduction signal,
The average level calculating step updates one of the 2 ^M reference values at predetermined intervals based on the equalized reproduction signal and a time-series pattern for M times of the binary signal. The information reproducing method according to claim 6. The time defined by the predetermined period is k, the value determined based on the binary signal pattern is n, the equalized reproduction signal or the reproduction signal is w _k , and the update coefficient is α (0 <α ≦ 1), the average level calculating step sets the reference value x _{n, k} of the branch metric to x _{n, k} = α · x _{n, k−1} + (1−α) · w _k
The information reproducing method according to claim 6, further comprising a step of calculating by the following. The time defined by the predetermined cycle is k, the value determined based on the binary signal pattern is n, the equalized reproduction signal or the reproduction signal is w _k , and the update coefficient is α _n (0 < When α _n ≦ 1), the average level calculation step sets the branch metric reference value x _{n, k} as
x _{n, k} = α · x _{n, k−1} + (1−α) · w _k
The information reproducing method according to claim 6, further comprising a step of calculating by the following. The updating process of the reference value of the branch metric in the average level calculating step indicates a low-pass filter operation. When the cutoff frequency of the low-pass filter is f1 and the input channel frequency is f2, 0.00015 <f1 / f2 <0. 10. The information reproducing method according to claim 6, wherein the information reproducing method is .046.

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