Patent Description:
In general, a sparse signal with many component values whose magnitudes can be represented by zero or values small enough to be regarded as zero by selecting a proper basis can be efficiently represented by the values of a small number of components that are not regarded as zero under the selected basis. A technique using compressed sensing is considered as a method using this characteristic to convert sampling sequence data obtained by sampling a sparse signal with an analog-to-digital converter (ADC) into a compressed data format based on the values of a small number of components that are not regarded as zero.

For example, Patent Literature <NUM> discloses a technique called sparse reconstruction to represent a sparse signal with fewer variables by iteratively optimizing the fidelity and sparsity of compressed representation.

<NPL>, discloses generating a sequence x[n] by interleaving the sequences x0[n], x1[n],. , XQ-<NUM>[n], obtained from parallel sub-Nyquist ADCs, and encoding the sequence x[n] through an Under-sampled Analysis Filter Bank (UAFB), wherein the output of every filter is decimated by Q, and then the output samples y[n] are obtained every Cxτ seconds by time-interleaving the UAFB channels.

<CIT> discloses an array-based Compressed sensing Receiver Architecture including an antenna array with two or more antennas connected to two or more ADCs that are clocked at two or more different sampling rates below the Nyquist rate of the incident signals.

However, the above conventional technique has a very large computational load in optimization processing to search for a combination of a proper basis and its component values in compressed sensing. For example, there is a problem that processing of a broadband signal with <NUM> GS/s or more is impractical.

The present disclosure has been made in view of the above, and an object thereof is to provide a data compression apparatus capable of improving the compression ratio of a sparse signal while reducing an increase in computational load.

To solve the problem and achieve the object described above, a data compression apparatus according to the present disclosure is defined in claim <NUM>.

The data compression apparatus according to the present disclosure has the effect of being able to improve the compression ratio of a sparse signal while reducing an increase in computational load.

Hereinafter, a data compression apparatus, a data decompression apparatus, a data compression system, a control circuit, a storage medium, a data compression method, and a data decompression method according to embodiments of the present disclosure will be described in detail with reference to the drawings.

<FIG> is a diagram illustrating a configuration example of a data compression system <NUM> according to a first embodiment. The data compression system <NUM> includes a data compression apparatus <NUM> and a data decompression apparatus <NUM>.

The data compression apparatus <NUM> includes an MCS receiver <NUM> and an MCS encoder <NUM>. In the preceding stage of the data compression apparatus <NUM>, an antenna <NUM> receives an electromagnetic wave signal. An amplifier <NUM> amplifies a target signal that is an electromagnetic wave signal received by the antenna <NUM>. In the data compression apparatus <NUM>, the MCS receiver <NUM> is a receiver that converts a target signal that is an electromagnetic wave signal received by the antenna <NUM> and amplified by the amplifier <NUM> into a plurality of sampling sequences. Specifically, the MCS receiver <NUM> outputs sampling sequences corresponding to signals obtained by adding different delay times to different signals obtained by branching a target signal into a plurality of lines and sampling the signals at a sampling rate less than the Nyquist rate. The MCS encoder <NUM> is an encoder that converts sampling sequences converted by the MCS receiver <NUM> into compressed data and outputs the compressed data to the data decompression apparatus <NUM>.

The data decompression apparatus <NUM> includes an MCS decoder <NUM>. In the data decompression apparatus <NUM>, the MCS decoder <NUM> decodes compressed data acquired from the data compression apparatus <NUM> into an amplitude value corresponding to a frequency before a target signal is folded by the data compression apparatus <NUM>. Here, the expression "a target signal is folded" means that when the target signal is a sparse signal, the target signal is represented by a small number of components that are not regarded as zero under a selected basis.

First, the configuration and operation of the data compression apparatus <NUM> will be described. <FIG> is a diagram illustrating a configuration example of the data compression apparatus <NUM> according to the first embodiment. <FIG> is a flowchart illustrating the operation of the data compression apparatus <NUM> according to the first embodiment. In <FIG>, the antenna <NUM> and the amplifier <NUM> in the preceding stage are also illustrated. The same applies to the drawings of configuration examples of the data compression apparatus in the following embodiments. In <FIG>, for convenience of explanation, the operation of the amplifier <NUM> in the preceding stage of the data compression apparatus <NUM> is included. The same applies to the flowcharts of the data compression apparatus in the following embodiments. As described above, the data compression apparatus <NUM> includes the MCS receiver <NUM> and the MCS encoder <NUM>. The MCS receiver <NUM> includes delay time addition units <NUM>-<NUM> to <NUM>-<NUM> and sub-ADCs <NUM>-<NUM> to <NUM>-<NUM>. The MCS encoder <NUM> includes sub-fast Fourier transforms (FFTs) <NUM>-<NUM> to <NUM>-<NUM>, signal processing units <NUM>-<NUM> to <NUM>-<NUM>, a target frequency estimator <NUM>, and an encoding unit <NUM>.

In the preceding stage of the data compression apparatus <NUM>, the amplifier <NUM> amplifies a target signal that is an electromagnetic wave signal received by the antenna <NUM> (step S101). In the data compression apparatus <NUM>, the MCS receiver <NUM> branches the target signal amplified by the amplifier <NUM> into four lines, that is, four signals (step S102).

The delay time addition units <NUM>-<NUM> to <NUM>-<NUM> add different delay times to the signals, based on the signal in the line output from the amplifier <NUM> to the sub-ADC <NUM>-<NUM> (step S103). For example, the delay time addition units <NUM>-<NUM> to <NUM>-<NUM> may each add a different delay time using a delay element, or may each add a different delay time using a track-and-hold circuit. The delay time addition units <NUM>-<NUM> to <NUM>-<NUM> are collectively referred to as a delay time addition unit <NUM>. The delay time addition unit <NUM> adds different delay times to different signals obtained by branching a target signal into a plurality of lines. The delay time addition unit <NUM> may be configured to be able to add a delay time also to a signal in the line output from the amplifier <NUM> to the sub-ADC <NUM>-<NUM>. In this case, the delay time addition unit <NUM> adds a delay time of zero to the signal in the line output from the amplifier <NUM> to the sub-ADC <NUM>-<NUM>.

Each of the sub-ADCs <NUM>-<NUM> to <NUM>-<NUM> independently performs sampling at a sampling rate that is a sub-Nyquist rate of <NUM>/<NUM> of the Nyquist rate. Specifically, the sub-ADC <NUM>-<NUM> samples the signal output from the amplifier <NUM>. The sub-ADC <NUM>-<NUM> samples the target signal in the line output from the delay time addition unit <NUM>-<NUM>. The sub-ADC <NUM>-<NUM> samples the target signal in the line output from the delay time addition unit <NUM>-<NUM>. The sub-ADC <NUM>-<NUM> samples the target signal in the line output from the delay time addition unit <NUM>-<NUM> (step S104). The sub-ADCs <NUM>-<NUM> to <NUM>-<NUM> are collectively referred to as a sub-ADC <NUM>. The sub-ADC <NUM> is a sub-sampling unit that samples signals at a sampling rate less than the Nyquist rate and outputs sampling sequences.

In the MCS encoder <NUM>, the sub-FFTs <NUM>-<NUM> to <NUM>-<NUM> perform processing to convert the sampling sequences sub-Nyquist sampled by the corresponding sub-ADCs <NUM>-<NUM> to <NUM>-<NUM> into signals folded in the frequency domain. Specifically, the sub-FFT <NUM>-<NUM> converts the sampling sequence from the sub-ADC <NUM>-<NUM> from a time-domain signal into a frequency-domain signal. The sub-FFT <NUM>-<NUM> converts the sampling sequence from the sub-ADC <NUM>-<NUM> from a time-domain signal into a frequency-domain signal. The sub-FFT <NUM>-<NUM> converts the sampling sequence from the sub-ADC <NUM>-<NUM> from a time-domain signal into a frequency-domain signal. The sub-FFT <NUM>-<NUM> converts the sampling sequence from the sub-ADC <NUM>-<NUM> from a time-domain signal into a frequency-domain signal (step S105). The sub-FFTs <NUM>-<NUM> to <NUM>-<NUM> are collectively referred to as a sub-FFT <NUM>. The sub-FFT <NUM> is a time-frequency transform unit that converts sampling sequences in different lines from time-domain signals into frequency-domain signals.

The signal processing units <NUM>-<NUM> to <NUM>-<NUM> multiply the frequency-domain signals converted by the corresponding sub-FFTs <NUM>-<NUM> to <NUM>-<NUM> by coefficients for phase compensation for individual sub-Nyquist zones of the number of sub-Nyquist folds K corresponding to twenty, the ratio between the sub-Nyquist rate and the Nyquist rate, and to cancel phase rotation due to the delay time differences (step S106). As illustrated in <FIG>, the coefficients are C<NUM>, k by which the signal processing unit <NUM>-<NUM> multiplies the frequency-domain signal from the sub-FFT <NUM>-<NUM>, C<NUM>, k by which the signal processing unit <NUM>-<NUM> multiplies the frequency-domain signal from the sub-FFT <NUM>-<NUM>, C<NUM>, k by which the signal processing unit <NUM>-<NUM> multiplies the frequency-domain signal from the sub-FFT <NUM>-<NUM>, and C<NUM>, k by which the signal processing unit <NUM>-<NUM> multiplies the frequency-domain signal from the sub-FFT <NUM>-<NUM>. Here, k=<NUM>, <NUM>,. The signal processing units <NUM>-<NUM> to <NUM>-<NUM> are collectively referred to as a signal processing unit <NUM>. The signal processing unit <NUM> performs, at one time, phase compensation processing for the sub-Nyquist zones of sampling sequences converted into frequency-domain signals, and processing to cancel phase rotation due to delay time differences between the sampling sequences.

The target frequency estimator <NUM> calculates the sum total of values obtained by the multiplication by the coefficients C<NUM>, k, C<NUM>, k, C<NUM>, k, and C<NUM>, k for each sub-Nyquist zone, that is, for each identical sub-Nyquist zone number k in the signal processing units <NUM>-<NUM> to <NUM>-<NUM> (step S107). The target frequency estimator <NUM> determines a sub-Nyquist zone in which the target signal is present, that is, folded. Specifically, the target frequency estimator <NUM> determines that the target signal is folded in the sub-Nyquist zone in which the largest sum total is obtained (step S108). Thus, the target frequency estimator <NUM> determines into which sub-Nyquist zone the target signal has been folded, and estimates the frequency of the target signal.

The encoding unit <NUM> converts a value representing the sub-Nyquist zone and the corresponding amplitude value into compressed data in a specified data format, and outputs the compressed data (step S109).

Next, the configuration and operation of the data decompression apparatus <NUM> will be described. <FIG> is a diagram illustrating a configuration example of the MCS decoder <NUM> included in the data decompression apparatus <NUM> according to the first embodiment. <FIG> is a flowchart illustrating the operation of the data decompression apparatus <NUM> according to the first embodiment. In the data decompression apparatus <NUM>, the MCS decoder <NUM> includes a decoding unit <NUM>. The decoding unit <NUM> acquires the compressed data output from the encoding unit <NUM> of the data compression apparatus <NUM>, and extracts the value representing the sub-Nyquist zone number k and the corresponding amplitude value from the compressed data (step S201). The decoding unit <NUM> restores an amplitude value corresponding to a frequency before being folded in the data compression apparatus <NUM>, using the value representing the sub-Nyquist zone number k and the corresponding amplitude value extracted (step S202). The decoding unit <NUM> inserts zeros as component values into amplitude values corresponding to frequencies not specified by the sub-Nyquist zone number k (step S203).

Thus, the MCS decoder <NUM> extracts the value representing the sub-Nyquist zone and the corresponding amplitude value from the compressed data acquired from the data compression apparatus <NUM>, and restores the amplitude value corresponding to the frequency before the target signal is folded in the data compression apparatus <NUM>.

Next, a hardware configuration of the data compression apparatus <NUM> will be described. In the data compression apparatus <NUM>, the MCS receiver <NUM> and the MCS encoder <NUM> are implemented by processing circuitry. The processing circuitry may be a processor that executes a program stored in memory and the memory, or may be dedicated hardware. The processing circuitry is also referred to as a control circuit.

<FIG> is a diagram illustrating a configuration example of processing circuitry <NUM> when the processing circuitry included in the data compression apparatus <NUM> according to the first embodiment is implemented by a processor and memory. The processing circuitry <NUM> illustrated in <FIG> is a control circuit and includes a processor <NUM> and memory <NUM>. When the processor <NUM> and the memory <NUM> constitute the processing circuitry <NUM>, the functions of the processing circuitry <NUM> are implemented by software, firmware, or a combination of software and firmware. The software or firmware is described as a program and stored in the memory <NUM>. In the processing circuitry <NUM>, the processor <NUM> reads and executes the program stored in the memory <NUM>, thereby implementing the functions. That is, the processing circuitry <NUM> includes the memory <NUM> for storing the program that results in the execution of the processing in the data compression apparatus <NUM>. This program can be said to be a program for causing the data compression apparatus <NUM> to execute the functions implemented by the processing circuitry <NUM>. This program may be provided by a storage medium in which the program is stored, or may be provided by other means such as a communication medium.

The program can be said to be a program that causes the data compression apparatus <NUM> to perform a first step of outputting, by the MCS receiver <NUM>, sampling sequences corresponding to signals obtained by adding different delay times to different signals obtained by branching a target signal into a plurality of lines, and sampling the signals at a sampling rate less than the Nyquist rate, and a second step of converting, by the MCS encoder <NUM>, the sampling sequences into compressed data and outputting the compressed data, and causes the data compression apparatus <NUM> to perform, as the second step, a third step of converting, by the sub-FFTs <NUM>-<NUM> to <NUM>-<NUM>, the sampling sequences in the lines from time-domain signals into frequency-domain signals, a fourth step of performing, by the signal processing units <NUM>-<NUM> to <NUM>-<NUM>, at one time, phase compensation processing for the sub-Nyquist zones of the sampling sequences converted into the frequency-domain signals, and processing to cancel phase rotation due to delay time differences between the sampling sequences, a fifth step of determining, by the target frequency estimator <NUM>, into which sub-Nyquist zone the target signal has been folded and estimating, by the target frequency estimator <NUM>, the frequency of the target signal, and a sixth step of converting, by the encoding unit <NUM>, a value representing the sub-Nyquist zone and the corresponding amplitude value into compressed data in a specified data format and outputting, by the encoding unit <NUM>, the compressed data.

Here, the processor <NUM> is, for example, a central processing unit (CPU), a processing unit, an arithmetic unit, a microprocessor, a microcomputer, a digital signal processor (DSP), or the like. The memory <NUM> corresponds, for example, to nonvolatile or volatile semiconductor memory such as random-access memory (RAM), read-only memory (ROM), flash memory, an erasable programmable ROM (EPROM), or an electrically EPROM (EEPROM) (registered trademark), or a magnetic disk, a flexible disk, an optical disk, a compact disk, a mini disk, a digital versatile disc (DVD), or the like.

<FIG> is a diagram illustrating an example of processing circuitry <NUM> when dedicated hardware constitutes the processing circuitry included in the data compression apparatus <NUM> according to the first embodiment. The processing circuitry <NUM> illustrated in <FIG> corresponds, for example, to a single circuit, a combined circuit, a programmed processor, a parallel-programmed processor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a combination of them. The processing circuitry may be implemented partly by dedicated hardware and partly by software or firmware. Thus, the processing circuitry can implement the above-described functions by dedicated hardware, software, firmware, or a combination of them.

The hardware configuration of the data compression apparatus <NUM> has been described. The hardware configuration of the data decompression apparatus <NUM> is the same as the hardware configuration of the data compression apparatus <NUM>.

As described above, according to the present embodiment, in the data compression apparatus <NUM>, the MCS receiver <NUM> adds different delay times to different signals obtained by branching a target signal into a plurality of lines, and outputs sampling sequences obtained by sampling the signals at a sampling rate less than the Nyquist rate. The MCS encoder <NUM> converts the sampling sequences in the lines from time-domain signals into frequency-domain signals, and performs, at one time, phase compensation processing for the sub-Nyquist zones of the sampling sequences converted into the frequency-domain signals, and processing to cancel phase rotation due to delay time differences between the sampling sequences. The MCS encoder <NUM> determines into which sub-Nyquist zone the target signal has been folded, estimates the frequency of the target signal, converts a value representing the sub-Nyquist zone and the corresponding amplitude value into compressed data in a specified data format, and outputs the compressed data. Consequently, when outputting a target signal to the data decompression apparatus <NUM>, the data compression apparatus <NUM> can improve the compression ratio of a sparse signal while reducing an increase in computational load.

A second embodiment describes a case where a data compression apparatus applies Hann windows to time-series data, that is, output signals sub-Nyquist sampled by the sub-ADCs <NUM>-<NUM> to <NUM>-<NUM>.

<FIG> is a diagram illustrating a configuration example of a data compression apparatus 100a according to the second embodiment. <FIG> is a flowchart illustrating the operation of the data compression apparatus 100a according to the second embodiment. The data compression apparatus 100a includes the MCS receiver <NUM> and an MCS encoder 130a. The MCS encoder 130a is obtained by adding window processing units <NUM>-<NUM> to <NUM>-<NUM> to the MCS encoder <NUM> of the first embodiment illustrated in <FIG>.

In the data compression apparatus 100a, the operation up to step S104 is the same as the operation of the data compression apparatus <NUM> in the first embodiment. After the operation in step S104, in the MCS encoder 130a, the window processing units <NUM>-<NUM> to <NUM>-<NUM> multiply the sampling sequences sub-Nyquist sampled by the corresponding sub-ADCs <NUM>-<NUM> to <NUM>-<NUM> by coefficients corresponding to the Hann windows (step S111). As illustrated in <FIG>, the coefficients are W<NUM>, l by which the window processing unit <NUM>-<NUM> multiplies the sampling sequence from the sub-ADC <NUM>-<NUM>, W<NUM>, l by which the window processing unit <NUM>-<NUM> multiplies the sampling sequence from the sub-ADC <NUM>-<NUM>, W<NUM>, l by which the window processing unit <NUM>-<NUM> multiplies the sampling sequence from the sub-ADC <NUM>-<NUM>, and W<NUM>, l by which the window processing unit <NUM>-<NUM> multiplies the sampling sequence from the sub-ADC <NUM>-<NUM>. Let l=<NUM>, <NUM>,.

The window processing units <NUM>-<NUM> to <NUM>-<NUM> are collectively referred to as a window processing unit <NUM>. The window processing unit <NUM> multiplies sampling sequences in the lines output from the MCS receiver <NUM> by coefficients corresponding to the Hann windows. The window processing unit <NUM> outputs the sampling sequences in the lines multiplied by the coefficients corresponding to the Hann windows to the sub-FFT <NUM>.

The sub-FFTs <NUM>-<NUM> to <NUM>-<NUM> convert the sampling sequences multiplied by the coefficients corresponding to the Hann windows by the corresponding window processing units <NUM>-<NUM> to <NUM>-<NUM>, that is, the sampling sequences in the lines output from the window processing unit <NUM> from time-domain signals into frequency-domain signals (step S105). That is, the sub-FFTs <NUM>-<NUM> to <NUM>-<NUM> perform processing to convert the sampling sequences output from the corresponding window processing units <NUM>-<NUM> to <NUM>-<NUM> into signals folded in the frequency domain. In the data compression apparatus 100a, the operation in after step S106 is the same as the operation of the data compression apparatus <NUM> in the first embodiment.

<FIG> is a diagram illustrating an example of a spectrogram as a comparative example. In <FIG>, the horizontal axis represents time, the vertical axis represents frequency, and differences in shades of color in the graph represent amplitude absolute values. The spectrogram illustrated in <FIG> is obtained when a data compression apparatus of the comparative example receives a signal on which a continuous wave (CW) signal, a pulse signal, and a chirp signal are superimposed, performs sampling at a sampling rate equal to the Nyquist rate, and performs signal processing by an FFT.

<FIG> is a diagram illustrating an example of a spectrogram obtained through encoding and decoding by a data compression system consisting of the data compression apparatus 100a illustrated in <FIG> and the data decompression apparatus <NUM> illustrated in <FIG>. In <FIG>, the horizontal axis represents time, the vertical axis represents frequency, and differences in shades of color in the graph represent amplitude absolute values. A comparison between <FIG> and <FIG> shows that the spectrogram obtained by the data compression system consisting of the data compression apparatus 100a illustrated in <FIG> and the data decompression apparatus <NUM> illustrated in <FIG> has a high degree of coincidence with the spectrogram of the comparative example obtained when sampling is performed at the sampling rate equal to the Nyquist rate and signal processing is performed by the FFT.

As for the hardware configuration of the data compression apparatus 100a, the MCS receiver <NUM> and the MCS encoder 130a are implemented by processing circuitry. The processing circuitry may be a processor that executes a program stored in memory and the memory, or may be dedicated hardware.

As described above, according to the present embodiment, in the data compression apparatus 100a, the MCS encoder 130a performs window processing on sampling sequences. Consequently, compared with the first embodiment, the data compression apparatus 100a reduces side lobes in a spectrogram to be compressed and increases sparsity, and thus can compress data more effectively.

In a third embodiment, the MCS encoder <NUM> of the data compression apparatus <NUM> in the first embodiment performs processing only on sub-Nyquist zones in which a valid signal can be present.

The data compression apparatus <NUM> uses a target signal that is an electromagnetic wave signal received by the antenna <NUM> and amplified by the amplifier <NUM>. However, the fractional bandwidth of the antenna <NUM> is, for example, only about <NUM>, and a valid signal can be present in limited sub-Nyquist zones of the K sub-Nyquist zones. Therefore, the MCS encoder <NUM> can perform the signal processing on limited sub-Nyquist zones, according to the characteristics of the antenna <NUM>.

As described above, according to the present embodiment, in the data compression apparatus <NUM>, the MCS encoder <NUM> performs the signal processing only on sub-Nyquist zones of the K sub-Nyquist zones in which a valid signal can be present. Consequently, the data compression apparatus <NUM> can reduce the processing load of the signal processing.

In a fourth embodiment, the MCS encoder 130a of the data compression apparatus 100a in the second embodiment performs the signal processing only on sub-Nyquist zones in which a valid signal can be present.

The data compression apparatus 100a uses a target signal that is an electromagnetic wave signal received by the antenna <NUM> and amplified by the amplifier <NUM>. However, the fractional bandwidth of the antenna <NUM> is, for example, only about <NUM>, and a valid signal can be present in limited sub-Nyquist zones of the K sub-Nyquist zones. Therefore, the MCS encoder 130a can perform the signal processing on limited sub-Nyquist zones, according to the characteristics of the antenna <NUM>.

As described above, according to the present embodiment, in the data compression apparatus 100a, the MCS encoder 130a performs the signal processing only on sub-Nyquist zones of the K sub-Nyquist zones in which a valid signal can be present. Consequently, the data compression apparatus 100a can reduce the processing load of the signal processing.

In the first to fourth embodiments, the MCS receiver <NUM> samples a target signal branched with the sub-ADCs <NUM>-<NUM> to <NUM>-<NUM>. In a fifth embodiment, an MCS receiver samples a target signal by one ADC before branching the target signal.

<FIG> is a diagram illustrating a configuration example of a data compression apparatus 100b according to the fifth embodiment. <FIG> is a flowchart illustrating the operation of the data compression apparatus 100b according to the fifth embodiment. The data compression apparatus 100b includes an MCS receiver 120b and the MCS encoder <NUM>. The MCS receiver 120b is a receiver that converts a target signal that is an electromagnetic wave signal received by the antenna <NUM> and amplified by the amplifier <NUM> into a plurality of sampling sequences. The MCS receiver 120b includes the amplifier <NUM>, an ADC <NUM> as a sampling unit, and signal extraction units <NUM>-<NUM> to <NUM>-<NUM>.

In the preceding stage of the data compression apparatus 100b, the amplifier <NUM> amplifies a target signal that is an electromagnetic wave signal received by the antenna <NUM> (step S101). In the data compression apparatus 100b, the ADC <NUM> of the MCS receiver 120b samples the target signal amplified by the amplifier <NUM> at a sampling rate of the Nyquist rate (step S121). The signal extraction units <NUM>-<NUM> to <NUM>-<NUM> each extract a signal corresponding to a specified delay time difference from the signal sampled by the ADC <NUM> to give the delay time difference to the sampling timing of the ADC <NUM> (step S122). The signal extraction units <NUM>-<NUM> to <NUM>-<NUM> are collectively referred to as a signal extraction unit <NUM>. The operation of the MCS encoder <NUM> after that is the same as the operation of the MCS encoder <NUM> in the first embodiment. The data compression apparatus 100b may replace the MCS encoder <NUM> with the MCS encoder 130a of the second embodiment.

As for the hardware configuration of the data compression apparatus 100b, the MCS receiver 120b and the MCS encoder <NUM> are implemented by processing circuitry. The processing circuitry may be a processor that executes a program stored in memory and the memory, or may be dedicated hardware.

As described above, according to the present embodiment, in the data compression apparatus 100b, the MCS receiver 120b extracts signals corresponding to the specified delay time differences after sampling a target signal. Also in this case, the data compression apparatus 100b can obtain the same effects as the data compression apparatus <NUM> in the first embodiment.

In the first to fifth embodiments, the target frequency estimator <NUM> takes the sum totals of values obtained by multiplication by the corresponding coefficients in the signal processing units <NUM>-<NUM> to <NUM>-<NUM>, and determines that the signal is folded in a sub-Nyquist zone in which the largest sum total is obtained. A sixth embodiment describes a method by which the target frequency estimator <NUM> determines a sub-Nyquist zone in which a signal is folded by another method. The description uses the first embodiment as an example, but the method is also applicable to the second to fifth embodiments.

<FIG> is a flowchart illustrating the operation of the data compression apparatus <NUM> according to the sixth embodiment. In the flowchart illustrated in <FIG>, the operation from step S101 to step S106 and the operation in step S109 are the same as the operation from step S101 to step S106 and the operation in step S109 in the flowchart in the first embodiment illustrated in <FIG>. The target frequency estimator <NUM> checks variations in values obtained by multiplication by the coefficients C<NUM>, k, C<NUM>, k, C<NUM>, k, and C<NUM>, k for each sub-Nyquist zone, that is, for each identical sub-Nyquist zone number k in the signal processing units <NUM>-<NUM> to <NUM>-<NUM> (step S131). The target frequency estimator <NUM> determines a sub-Nyquist zone in which the target signal is folded. Specifically, the target frequency estimator <NUM> determines that the target signal is folded in a sub-Nyquist zone having the smallest variations (step S132).

As described above, according to the present embodiment, in the data compression apparatus <NUM>, the MCS encoder <NUM> determines that a target signal is folded in a sub-Nyquist zone having the smallest variations in values obtained by multiplication by the coefficients for each sub-Nyquist zone. Also in this case, the data compression apparatus <NUM> can obtain the same effects as the data compression apparatus <NUM> of the first embodiment.

A seventh embodiment describes a case where a data compression apparatus performs encoding processing in two stages in a data compression system. The description uses the first embodiment as an example, but the case is also applicable to the second to sixth embodiments.

<FIG> is a diagram illustrating a configuration example of a data compression system 1c according to the seventh embodiment. The data compression system 1c includes a data compression apparatus 100c and a data decompression apparatus 200c. The data compression apparatus 100c is obtained by adding an encoder <NUM> to the data compression apparatus <NUM>. The data decompression apparatus 200c is obtained by adding a decoder <NUM> to the data decompression apparatus <NUM>.

In the data compression apparatus 100c, the encoder <NUM> further compresses compressed data output from the encoding unit <NUM> and outputs the further compressed data to the data decompression apparatus 200c. The encoder <NUM> may use, for example, entropy coding such as a Huffman code or an arithmetic code, or may use logarithmic transformation, floating-point return, or the like, or may use a combination of them. In the following description, the MCS encoder <NUM> is sometimes referred to as a first encoder, and the encoder <NUM> is sometimes referred to as a second encoder.

In the data decompression apparatus 200c, the decoder <NUM> decodes the compressed data acquired from the data compression apparatus 100c using a decoding scheme corresponding to an encoding scheme of the encoder <NUM>, and outputs the decoded data to the MCS decoder <NUM>. In the following description, the MCS decoder <NUM> is sometimes referred to as a first decoder, and the decoder <NUM> is sometimes referred to as a second decoder.

As for the hardware configuration of the data compression apparatus 100c, the MCS receiver <NUM>, the MCS encoder <NUM>, and the encoder <NUM> are implemented by processing circuitry. The processing circuitry may be a processor that executes a program stored in memory and the memory, or may be dedicated hardware. Likewise, as for the hardware configuration of the data decompression apparatus 200c, the MCS decoder <NUM> and the decoder <NUM> are implemented by processing circuitry. The processing circuitry may be a processor that executes a program stored in memory and the memory, or may be dedicated hardware.

As described above, according to the present embodiment, the data compression apparatus 100c includes the encoder <NUM> to further compress compressed data, and the data decompression apparatus 200c includes the decoder <NUM> to decode the compressed data compressed, that is, encoded by the encoder <NUM>. Consequently, the data compression apparatus 100c can output compressed data compressed further than in the data compression apparatus <NUM> of the first embodiment.

An eighth embodiment describes a case where a data decompression apparatus includes a storage in a data compression system. The description uses the first embodiment as an example, but the case is also applicable to the second to sixth embodiments.

<FIG> is a diagram illustrating a configuration example of a data compression system 1d according to the eighth embodiment. The data compression system 1d includes the data compression apparatus <NUM> and a data decompression apparatus 200d. The data decompression apparatus 200d is obtained by adding a storage <NUM> to the data decompression apparatus <NUM>.

In the data decompression apparatus 200d, the storage <NUM> stores compressed data acquired from the data compression apparatus <NUM>. Using the compressed data stored in the storage <NUM>, the MCS decoder <NUM> restores an amplitude value corresponding to a frequency before being folded in the data compression apparatus <NUM>. In the example of <FIG>, an example in which the data decompression apparatus 200d includes the storage <NUM> has been described, but the data compression apparatus <NUM> may also include a storage in the subsequent stage of the MCS encoder <NUM>.

As for the hardware configuration of the data decompression apparatus 200d, the MCS decoder <NUM> and the storage <NUM> are implemented by processing circuitry. The processing circuitry may be a processor that executes a program stored in memory and the memory, or may be dedicated hardware.

As described above, according to the present embodiment, the data decompression apparatus 200d stores compressed data acquired from the data compression apparatus <NUM> in the storage <NUM> and then performs decoding. For example, if the state of communication between the data compression apparatus <NUM> and the data decompression apparatus 200d deteriorates, and it takes time to acquire compressed data from the data compression apparatus <NUM>, the data decompression apparatus 200d can store compressed data in the storage <NUM> to store a required amount of compressed data, and then perform decoding.

A ninth embodiment describes a case where the storage <NUM> is added to the data decompression apparatus 200c of the data compression system 1c in the seventh embodiment.

<FIG> is a diagram illustrating a configuration example of a data compression system 1e according to the ninth embodiment. The data compression system 1e includes the data compression apparatus 100c and a data decompression apparatus 200e. The data decompression apparatus 200e is obtained by adding the storage <NUM> to the data decompression apparatus 200c.

In the data decompression apparatus 200e, the storage <NUM> stores compressed data acquired from the data compression apparatus 100c. The decoder <NUM> decodes the compressed data stored in the storage <NUM> using a decoding scheme corresponding to an encoding scheme of the encoder <NUM>, and outputs the decoded data to the MCS decoder <NUM>. In the example of <FIG>, an example in which the data decompression apparatus 200e includes the storage <NUM> has been described, but the data compression apparatus 100c may also include a storage in the subsequent stage of the encoder <NUM>.

As for the hardware configuration of the data decompression apparatus 200e, the MCS decoder <NUM>, the decoder <NUM>, and the storage <NUM> are implemented by processing circuitry. The processing circuitry may be a processor that executes a program stored in memory and the memory, or may be dedicated hardware.

As described above, according to the present embodiment, the data decompression apparatus 200e stores compressed data acquired from the data compression apparatus 100c in the storage <NUM> and then performs decoding. Also in this case, the data decompression apparatus 200e can obtain the same effects as the data decompression apparatus 200d of the eighth embodiment.

A tenth embodiment describes a case where a data decompression apparatus includes an inverse discrete Fourier transform (IDFT). The description uses the first embodiment as an example, but the case is also applicable to the second to ninth embodiments.

<FIG> is a diagram illustrating a configuration example of a data compression system 1f according to the tenth embodiment. The data compression system 1f includes the data compression apparatus <NUM> and a data decompression apparatus 200f. The data decompression apparatus 200f is obtained by adding an IDFT <NUM> to the data decompression apparatus <NUM>.

In the data decompression apparatus 200f, the IDFT <NUM> is a frequency-time transform unit that converts a value restored by the MCS decoder <NUM>, that is, a frequency amplitude value from a frequency-domain signal into a time-domain signal and outputs the time-domain signal.

As for the hardware configuration of the data decompression apparatus 200f, the MCS decoder <NUM> and the IDFT <NUM> are implemented by processing circuitry. The processing circuitry may be a processor that executes a program stored in memory and the memory, or may be dedicated hardware.

As described above, according to the present embodiment, the data decompression apparatus 200f converts a restored frequency amplitude value from a frequency-domain signal into a time-domain signal and outputs the time-domain signal. Consequently, the data decompression apparatus 200f can output, to an apparatus in the subsequent stage (not illustrated), decoded information in a time-domain signal form similar to that of the target signal acquired by the data compression apparatus <NUM>.

An eleventh embodiment describes a case where a data compression apparatus includes a plurality of antennas. The description uses the first embodiment as an example, but the case is also applicable to the second to tenth embodiments.

<FIG> is a diagram illustrating a configuration example of a data compression system <NUM> according to the eleventh embodiment. The data compression system <NUM> includes a data compression apparatus <NUM> and the data decompression apparatus <NUM>. The data compression apparatus <NUM> includes an array antenna element group <NUM> consisting of a primary antenna <NUM>-<NUM> and one or more secondary antennas <NUM>-<NUM> and <NUM>-<NUM>, a primary MCS receiver <NUM>-<NUM>, one or more secondary MCS receivers <NUM>-<NUM> and <NUM>-<NUM>, an MCS encoder <NUM>, and one or more MCS synthesizers <NUM>-<NUM> and <NUM>-<NUM>. The primary MCS receiver <NUM>-<NUM> is connected to the primary antenna <NUM>-<NUM>, the secondary MCS receiver <NUM>-<NUM> is connected to the secondary antenna <NUM>-<NUM>, and the secondary MCS receiver <NUM>-<NUM> is connected to the secondary antenna <NUM>-<NUM>. The antennas <NUM>-<NUM> to <NUM>-<NUM> have the same configuration as the above-described antenna <NUM>. The MCS receivers <NUM>-<NUM> to <NUM>-<NUM> have the same configuration as the above-described MCS receiver <NUM>.

In the following description, the antennas <NUM>-<NUM> to <NUM>-<NUM> are sometimes referred to as antennas <NUM> when not distinguished, and the MCS receivers <NUM>-<NUM> to <NUM>-<NUM> are sometimes referred to as MCS receivers <NUM> when not distinguished. The data compression apparatus <NUM> includes a plurality of MCS receivers <NUM>, and each of the plurality of MCS receivers <NUM> is connected to a different antenna <NUM>. The MCS receiver <NUM>-<NUM> is sometimes referred to as a first receiver, and the MCS receivers <NUM>-<NUM> and <NUM>-<NUM> are sometimes referred to as second receivers. In the present embodiment, the MCS receiver <NUM>-<NUM>, a first receiver of the plurality of MCS receivers <NUM>, outputs sampling sequences of a target signal received by the primary antenna <NUM>-<NUM>. The MCS receivers <NUM>-<NUM> and <NUM>-<NUM>, one or more second receivers of the plurality of MCS receivers <NUM>, output sampling sequences of the target signal received by the secondary antennas <NUM>-<NUM> and <NUM>-<NUM>.

<FIG> is a diagram illustrating a configuration example of the data compression apparatus <NUM> according to the eleventh embodiment. Here, for ease of explanation, a case where the data compression apparatus <NUM> includes one secondary antenna <NUM>-<NUM>, one secondary MCS receiver <NUM>-<NUM>, and one MCS synthesizer <NUM>-<NUM> will be described.

Like the MCS receiver <NUM> of the first embodiment etc., the MCS receiver <NUM>-<NUM> performs sub-Nyquist sampling on an electromagnetic wave signal received by the antenna <NUM>-<NUM> in a plurality of sequences in parallel. The MCS encoder <NUM> includes the sub-FFT <NUM>, the signal processing unit <NUM>, a target frequency estimator <NUM>, and an encoding unit <NUM>. As in the MCS encoder <NUM> of the first embodiment, in the MCS encoder <NUM>, the sub-FFT <NUM> converts the sub-Nyquist-sampled sampling sequences into signals folded in the frequency domain, and the signal processing unit <NUM> performs phase compensation for each sub-Nyquist zone. In the present embodiment, the target frequency estimator <NUM> calculates the sum totals of amplitude components each phase-compensated by the signal processing unit <NUM>, and searches for a sub-Nyquist zone corresponding to one of the sum totals whose absolute value is the largest value. The target frequency estimator <NUM> outputs, to the encoding unit <NUM>, the value of the sum total of the amplitude components corresponding to the one whose absolute value is the largest value, and sub-Nyquist zone information that is the value of the sub-Nyquist zone corresponding to the one whose absolute value is the largest value. The target frequency estimator <NUM> outputs the sub-Nyquist zone information to the MCS synthesizer <NUM>-<NUM>.

Like the MCS receiver <NUM> of the first embodiment etc., the MCS receiver <NUM>-<NUM> performs sub-Nyquist sampling on an electromagnetic wave signal received by the antenna <NUM>-<NUM> in a plurality of sequences in parallel. The MCS synthesizer <NUM>-<NUM> includes the sub-FFT <NUM>, a signal processing unit <NUM>, and an amplitude synthesis unit <NUM>. As in the MCS encoder <NUM> of the first embodiment etc., in the MCS synthesizer <NUM>-<NUM>, the sub-FFT <NUM> converts the sub-Nyquist-sampled sampling sequences into signals folded in the frequency domain. In the present embodiment, the signal processing unit <NUM> performs phase compensation for a sub-Nyquist zone according to the sub-Nyquist zone information on a primary element line that is a line of the primary antenna <NUM>-<NUM> acquired from the target frequency estimator <NUM> of the MCS encoder <NUM>. The amplitude synthesis unit <NUM> calculates the sum total of amplitude components phase-compensated by the signal processing unit <NUM>, according to the sub-Nyquist zone information on the primary element line acquired from the target frequency estimator <NUM> of the MCS encoder <NUM>, and outputs the value of the sum total of the amplitude components to the MCS encoder <NUM>.

Thus, the MCS synthesizer <NUM>-<NUM> is a synthesizer that is connected to a different second receiver, calculates the sum total of amplitude components corresponding to a sub-Nyquist zone, using the sub-Nyquist zone information acquired from the MCS encoder <NUM>, and outputs the sum total to the MCS encoder <NUM>. For the secondary antenna <NUM>-<NUM>, the MCS synthesizer <NUM>-<NUM>, which uses the sub-Nyquist zone information acquired from the target frequency estimator <NUM> of the MCS encoder <NUM>, thus only needs to perform phase compensation for a single sub-Nyquist zone, allowing a reduction in the amount of computation to determine the sum total of amplitude components after that, and the elimination of computation to search for the largest value of absolute values. Consequently, the MCS synthesizer <NUM>-<NUM> allows a signal processing circuit to be reduced in size, power consumption, and cost and increased in speed, for example, as compared with the MCS encoder <NUM>.

Furthermore, the encoding unit <NUM> of the MCS encoder <NUM> can share sub-Nyquist zone information on a secondary element line that is a line of the secondary antenna <NUM>-<NUM>, the value of the exponent portion of a floating point, etc. with the primary element line, and thus can improve code compression efficiency. The encoding unit <NUM>, which shares values between the primary element line and the secondary element line, thus has processing details different from those of the above-described encoding unit <NUM>. As described above, the MCS encoder <NUM> is connected to the MCS receiver <NUM>-<NUM>, and outputs the sub-Nyquist zone information on the sampling sequences of the target signal received by the primary antenna <NUM>-<NUM>. Using the sum total of the amplitude components acquired from the MCS synthesizer <NUM>-<NUM>, the MCS encoder <NUM> outputs compressed data obtained by compressing the sampling sequences of the target signal received by the primary antenna <NUM>-<NUM> and the secondary antenna <NUM>-<NUM>.

Even when there is a plurality of secondary antennas <NUM>-<NUM> and <NUM>-<NUM>, the data compression apparatus <NUM> can obtain the same effects. The shorter the distance between the primary antenna <NUM>-<NUM> and the secondary antennas <NUM>-<NUM> and <NUM>-<NUM>, the stronger the correlation between a signal in the primary element line and signals in the secondary element lines, and the better the compression accuracy becomes. For example, if the distance between the primary antenna <NUM>-<NUM> and the secondary antennas <NUM>-<NUM> and <NUM>-<NUM> is about <NUM> or less, the data compression apparatus <NUM> can obtain favorable characteristics.

For the circuit configuration of the MCS receivers <NUM>-<NUM> to <NUM>-<NUM> that perform sub-Nyquist sampling, for example, a track-and-hold circuit may be used as described above, or sampling data may be thinned out at a sub-Nyquist rate from an ADC at the Nyquist rate. It is only required that sub-Nyquist sampling can be performed in different phases in parallel.

The MCS receivers <NUM>-<NUM> and <NUM>-<NUM> of the secondary element lines and the MCS receiver <NUM>-<NUM> of the primary element line may be equal or different in phase difference or delay time difference in sub-Nyquist sampling, and may be equal or unequal in the number of parallel sub-Nyquist sampling sequences. In either case, the MCS synthesizers <NUM>-<NUM> and <NUM>-<NUM> of the secondary element lines can perform phase compensation for the sub-Nyquist zone in the primary element line and the respective phase differences or delay time differences of the parallel sub-Nyquist sampling sequences in the secondary element lines.

Even when the number of secondary antennas <NUM>-<NUM> and <NUM>-<NUM> is two or more, the data compression apparatus <NUM> can obtain the same effects by the same processing.

The MCS encoder <NUM> may output, in addition to the value of a sub-Nyquist zone corresponding to a one whose absolute value takes the largest value, the values of a relatively small number of sub-Nyquist zones corresponding to a one whose absolute value is the largest next to the largest value and a one the largest next to that, that is, ones whose absolute values are the second largest and below. From the MCS encoder <NUM>, the MCS synthesizers <NUM>-<NUM> and <NUM>-<NUM> of the secondary element lines acquire the values of the relatively small number of sub-Nyquist zones corresponding to the ones whose absolute values are the second largest and below, thereby performing phase compensation for the relatively small number of sub-Nyquist zones. The MCS synthesizers <NUM>-<NUM> and <NUM>-<NUM> of the secondary element lines may calculate the sum totals of amplitude components each phase-compensated, search for a sub-Nyquist zone corresponding to one of the sum totals whose absolute value takes the largest value, and output the value of the sum total of the amplitude components corresponding to the one whose absolute value takes the largest value. Consequently, the data compression apparatus <NUM> can also balance the amounts of computation, compression accuracy, etc. between the MCS encoder <NUM> and the MCS synthesizers <NUM>-<NUM> and <NUM>-<NUM>.

<FIG> is a flowchart illustrating the operation of the data compression apparatus <NUM> according to the eleventh embodiment. In <FIG>, the operation from step S101 to step S108 is the same as the operation of the data compression apparatus <NUM> in the first embodiment. The target frequency estimator <NUM> outputs sub-Nyquist zone information to the MCS synthesizer <NUM>-<NUM> (step S141). The amplitude synthesis unit <NUM> calculates the sum total of amplitude components in the secondary element line phase-compensated by the signal processing unit <NUM>, according to the sub-Nyquist zone information on the primary element line acquired from the target frequency estimator <NUM> (step S142). The amplitude synthesis unit <NUM> outputs the value of the sum total of the amplitude components to the encoding unit <NUM>. Based on the information acquired from the target frequency estimator <NUM> and the amplitude synthesis unit <NUM>, the encoding unit <NUM> converts a value representing the sub-Nyquist zone and the corresponding amplitude values into compressed data in a specified data format and outputs the compressed data (step S143).

<FIG> is a flowchart illustrating the operation of the data decompression apparatus <NUM> according to the eleventh embodiment. The decoding unit <NUM> acquires the compressed data output from the encoding unit <NUM> of the data compression apparatus <NUM>, and extracts, from the compressed data, the value representing the sub-Nyquist zone number k and the same number of the corresponding amplitude values as the number of the antennas <NUM> (step S211). Using the value representing the sub-Nyquist zone number k and the same number of the corresponding amplitude values as the number of the antennas <NUM> extracted, the decoding unit <NUM> restores the same number of amplitude values as the number of the antennas <NUM> corresponding to frequencies before being folded in the data compression apparatus <NUM> (step S212). The decoding unit <NUM> inserts zeros as component values into amplitude values corresponding to frequencies not specified by the sub-Nyquist zone number k (step S203). Thus, the decoding unit <NUM> is different in processing details from the above-described decoding unit <NUM>.

The eighth embodiment has described the case where the data decompression apparatus 200d includes the storage <NUM>, and the ninth embodiment has described the case where the data decompression apparatus 200e includes the storage <NUM>. A data compression apparatus may include a storage as described above.

<FIG> is a first diagram illustrating a configuration example of a data compression system <NUM> according to a twelfth embodiment. The data compression system <NUM> includes a data compression apparatus <NUM> and the data decompression apparatus <NUM>. The data compression apparatus <NUM> is obtained by adding a storage <NUM> to the data compression apparatus <NUM>. The storage <NUM> stores compressed data output from the MCS encoder <NUM>. Thus, the data compression apparatus <NUM> can also store compressed data converted by the MCS encoder <NUM> in the storage <NUM> and then output the compressed data to the data decompression apparatus <NUM>.

<FIG> is a second diagram illustrating a configuration example of a data compression system 1i according to the twelfth embodiment. The data compression system 1i includes the data compression apparatus <NUM> and the data decompression apparatus 200d. The data compression system 1i may have the configuration in which the data compression apparatus <NUM> includes the storage <NUM>, and the data decompression apparatus 200d includes the storage <NUM>.

Claim 1:
A data compression apparatus (<NUM>) comprising:
a receiver (<NUM>) configured to output sampling sequences corresponding to signals obtained by adding different delay times to different signals obtained by branching a target signal into a plurality of lines, and sampling the signals at a sampling rate less than a Nyquist rate; and
an encoder (<NUM>) configured to convert the sampling sequences into compressed data and output the compressed data,
the encoder (<NUM>) including
a time-frequency transform unit (<NUM>) configured to convert the sampling sequences in the lines from time-domain signals into frequency-domain signals,
a signal processing unit (<NUM>) configured to perform, at one time, phase compensation processing for sub-Nyquist zones of the sampling sequences converted into the frequency-domain signals by multiplying the frequency-domain signals by coefficients (C<NUM>,k ...C<NUM>,k), and processing to cancel phase rotation due to delay time differences between the sampling sequences,
a target frequency estimator (<NUM>) configured to calculate a sum total of values obtained by the multiplication by the coefficients for each sub-Nyquist zone and determine into which sub-Nyquist zone the target signal has been folded and estimate a frequency of the target signal, wherein the target frequency estimator (<NUM>) is configured to determine that the target signal is folded in the sub-Nyquist zone in which the largest sum total is obtained, wherein the target signal is folded means that when the target signal is a sparse signal, the target signal is represented by a small number of components that are not regarded as zero under a selected basis, and
an encoding unit (<NUM>) configured to convert a value representing the sub-Nyquist zone and a corresponding amplitude value into the compressed data in a specified data format and output the compressed data.