WO2024053724A1

WO2024053724A1 - Signal processing device, signal processing method, and program

Info

Publication number: WO2024053724A1
Application number: PCT/JP2023/032792
Authority: WO
Inventors: 誠竹内; 晴雄齋藤
Original assignee: 国立大学法人東京大学
Priority date: 2022-09-09
Filing date: 2023-09-08
Publication date: 2024-03-14

Abstract

The present invention measures phase noise of a device under test while reducing at least one among the measurement cost and measurement time. This signal processing device comprises: an acquisition unit that acquires a plurality of signals to be measured, which are obtained by signals to be measured outputted from a device under test each being independently subjected to analog-to-digital conversion by a plurality of measuring instruments; and a derivation unit that derives a plurality of zero-crossing fluctuations (ZCFs), which is the time difference between the zero-crossing time of each of the plurality of signals to be measured and the zero-crossing time of an ideal sinusoidal signal; and a calculation unit that calculates phase noise of the device under test on the basis of the plurality of ZCFs.

Description

Signal processing device, signal processing method and program

Cross-reference of related applications

This application is based on US Provisional Application No. 63/404974 filed on September 9, 2022, the contents of which are hereby incorporated by reference.

The present invention relates to a signal processing device, a signal processing method, and a program.

Conventionally, phase noise has been known as one of the evaluation indicators of the performance (e.g. frequency stability) of devices to be measured such as crystal oscillators, audio equipment, digital equipment, communication equipment, etc. Various methods of measurement are being considered.

To measure the phase noise of a device under test (DUT: Device Under Test), the signal to be measured output from the device under test is measured using two independent measuring instruments, and each of the two measuring instruments is A cross-correlation spectrum method is known in which the phase noise of the DUT is measured by removing the phase noise of each of the two measuring instruments by taking the cross-correlation spectrum of the measurement signal of the DUT (for example, Patent Document 1). Note that the cross-correlation spectrum is also called a cross spectrum.

Japanese Patent Application Publication No. 2020-148544

However, in the above-mentioned cross-correlation spectrum method, if the phase noise of each of the two measuring devices is large or the number of measurements is small, there is a risk that the accuracy of measuring the phase noise of the device to be measured may decrease. In order to improve the measurement accuracy of the phase noise of the device to be measured using the cross-correlation spectrum method described above, it is necessary to use two expensive, low-noise measuring devices or to lengthen the measurement time. However, there is a problem in that the cost and time required to measure the phase noise of the device increases.

Therefore, one of the objects of the present disclosure is to provide a signal processing device, a signal processing method, and a program that can measure the phase noise of a device to be measured while reducing at least one of measurement cost and measurement time.

A signal processing device according to an aspect of the present disclosure includes an acquisition unit that acquires a plurality of measurement target signals obtained by independently analog-to-digital conversion of a measurement target signal output from a measurement target device by a plurality of measuring instruments; a derivation unit that derives a plurality of zero-crossing fluctuations (ZCF), which are time differences between the zero-crossing time of each measurement target signal and the zero-crossing time of an ideal sine wave signal; A calculation unit that calculates phase noise of the device to be measured.

In a signal processing method according to an aspect of the present disclosure, a signal processing device acquires a plurality of measurement target signals output from a measurement target device and each independently analog-to-digital converted by a plurality of measuring instruments, Deriving a plurality of zero-crossing fluctuations (ZCFs), which are time differences between the zero-crossing times of each of the plurality of measurement target signals and the zero-crossing time of an ideal sine wave signal, and based on the plurality of ZCFs, performing the measurement. Calculate the phase noise of the target device.

A program according to an aspect of the present disclosure includes an acquisition unit that causes a computer to acquire a plurality of measurement target signals outputted from a measurement target device and independently analog-to-digital converted by a plurality of measurement devices; a derivation unit that derives a plurality of zero-crossing fluctuations (ZCFs), which are time differences between the zero-crossing times of each of the plurality of measurement target signals and the zero-crossing time of an ideal sine wave signal; and based on the plurality of ZCFs, It functions as a calculation unit that calculates the phase noise of the device to be measured.

According to one aspect of the present disclosure, it is possible to measure the phase noise of a device to be measured while reducing at least one of measurement cost and measurement time.

FIG. 1 is a diagram showing an example of the configuration of a measurement system according to the present embodiment. 1 is a diagram illustrating an example of the configuration of a signal processing device according to an embodiment. FIG. 3 is a diagram showing an example of zero-crossing time of a signal to be measured according to the present embodiment. It is a figure showing an example of ZCF concerning this embodiment. It is a figure showing an example of setting for ZCF derivation concerning this embodiment. It is a figure showing other examples of settings for ZCF derivation concerning this embodiment. It is a flowchart which shows an example of operation of the measurement system concerning this embodiment. FIG. 3 is a diagram illustrating an example of a comparison between phase noise measured by the signal processing device 50 according to the present embodiment and phase noise measured using a cross-correlation spectrum method. 1 is a diagram illustrating an example of generalization of the configuration of a measurement system according to the present embodiment.

Embodiments of the present invention will be described with reference to the accompanying drawings. In addition, in each figure, those with the same reference numerals have the same or at least partially common configurations.

(composition)
The measurement system according to this embodiment includes a device to be measured (hereinafter referred to as "DUT: Device Under Test"), a divider that distributes a signal to be measured output from the DUT, and a divider connected to the divider. It includes a plurality of measuring instruments and a signal processing device connected to the plurality of measuring instruments. The following explanation will focus on the case where the number of multiple measuring devices is N=2, but the present invention is not limited to this, and it is sufficient if N≧2.

FIG. 1 is a diagram showing an example of the configuration of a measurement system according to the present embodiment. For example, in FIG. 1, N=2, and the measurement system 1 includes a DUT 10, a distributor 20, two independent analog-to-digital converters (ADCs) 30a and 30b, and an ADC 30a. and 30b, and a signal processing device 50.

As shown in FIG. 1, for example, the measuring device MDa includes an ADC 30a and a clock circuit 40a, and the measuring device MDb includes an ADC 30b and a clock circuit 40b. Hereinafter, if the measuring devices MDa and b are not distinguished, they will simply be collectively referred to as measuring devices MD. Further, when the

ADCs

30a and 30b are not distinguished, they are collectively referred to as the ADC 30, and when the

clock circuits

40a and 40b are not distinguished, they are collectively referred to as the clock circuit 40. Note that FIG. 1 is merely an example, and some configurations may be omitted, configurations not shown may be added, or the arrangement of some configurations may be changed. For example, a plurality of measuring devices MD may be connected in parallel without providing the distributor 20.

The DUT 10 is an oscillator that outputs a periodic signal such as a sine wave or a rectangular wave as a signal to be measured. The DUT 10 includes, for example, a crystal oscillator, a voltage controlled oscillator (VCO), a temperature compensated crystal oscillator (TCXO), and an oven controlled crystal oscillator (OCXO). ), audio equipment such as audio players and music players with earphone output terminals, communication equipment such as wireless communication terminals or base stations, arbitrary waveform generators with BNC (Bayonet Neill Concelman) output terminals, etc. be.

The distributor 20 is, for example, a power splitter, and distributes the measurement target signal output from the DUT 10 and outputs the distributed measurement target signal to each ADC 30.

Each ADC 30 measures the measurement target signal output from the distributor 20. Specifically, each ADC 30 samples the measurement target signal output from the distributor 20 based on the clock signal output from the corresponding clock circuit 40, and converts it from an analog signal to a digital signal (discrete data). You may.

Each clock circuit 40 generates a clock signal and outputs the generated clock signal to the corresponding ADC 30. Each clock circuit 40 may be, for example, an oscillator such as a crystal oscillator, a VCO, a TCXO, or an OCXO. The clock signal may be a periodic signal with a predetermined frequency (eg, 27 MHz). A clock signal is also called a reference signal or a local signal.

Each measuring device MD including the ADC 30 and the clock circuit 40 may be, for example, an audio device such as an audio recorder, or a communication device such as a base station or a wireless communication terminal. Note that each measuring device MD does not need to include the clock circuit 40, but may include at least the ADC 30. The measurement of the measurement target signal in each measuring device MD may include conversion from an analog signal to a digital signal by the ADC 30.

The signal processing device 50 calculates the phase noise of the DUT 10 based on the measurement target signal output from each measuring device MD. The signal processing device 50 is composed of a device including at least a processor. Here, phase noise is a variation in phase or frequency of a signal to be measured. Note that jitter is a fluctuation in a signal waveform in the time direction. The phase noise calculated by the signal processing device 50 may include at least one of PI (Phase independent) noise, jitter, and amplitude modulation (AM).

FIG. 2 is a diagram showing an example of the configuration of the signal processing device 50 according to the present embodiment. As shown in FIG. 2, the signal processing device 50 includes an acquisition section 501, a derivation section 502, and a calculation section 503. Note that the configuration of the signal processing device 50 is realized by, for example, at least one of a processor and a program executed by the processor.

The acquisition unit 501 acquires a plurality of measurement target signals respectively output from a plurality of measuring devices MD. For example, in FIG. 1, the acquisition unit 501 acquires two measurement target signals output from measuring instruments MDa and MDb, respectively.

The derivation unit 502 calculates a plurality of zero-crossing fluctuations, which are time differences between the zero-crossing time of each of the plurality of measurement target signals acquired by the acquisition unit 501 and the zero-crossing time of an ideal sine wave signal. (ZCF: Zero-Crossing Fluctuations) is derived. The derivation of the plurality of ZCFs is also called zero-crossing analysis (ZCA). Since ZCA is a type of time domain analysis (TDA), it is useful for measuring jitter, which is impossible with frequency domain analysis (FDA). Here, if the phase noise of the measuring device MD is negligible, it can be said that the ZCF of the signal to be measured outputted from the measuring device MD indicates the phase noise of the DUT 10.

FIG. 3 is a diagram illustrating an example of the zero crossing time of the signal to be measured according to the present embodiment. In FIG. 3, the horizontal axis is time t, the vertical axis is voltage V, and voltage V(t) of the signal to be measured at time t is shown. Further, the time when the voltage V of the measurement target signal becomes 0 is indicated as a zero crossing time s _k (k=1, 2, 3, . . . , M). where k is the zero-crossing time index and M is the number of zero-crossing times. The zero crossing time may also be referred to as a zero crossing point (ZCP).

As shown in FIG. 3, the intervals between the zero crossing times _sk of the signal to be measured are not equal due to the influence of noise of the DUT 10 and each measuring device MD. On the other hand, the zero crossing times s _{' k} (not shown) of the ideal sine wave signal are equally spaced. The ideal zero-crossing time of a sine wave signal is expressed, for example, by the function s'(k) of Equation 1 below.

Here, f'c is the frequency of an ideal sine wave signal (for example, the average frequency of period T). Further, the zero crossing time _s'k of the index k of the ideal sine wave signal can be set to the value of the function s'(k) shown in Equation 1.

ZCFΔs _k , which is the time difference between the zero-crossing time _s _k of the signal to be measured shown in FIG. Represented by

FIG. 4 is a diagram showing an example of the ZCF according to this embodiment. In FIG. 4, the horizontal axis is the index k of the zero crossing time, and the vertical axis is the time t, and the zero crossing time s _k of the signal to be measured at the index k and the zero crossing time s' _k of the ideal sine wave signal at the index k. and the zero-crossing time function s'(k) of an ideal sinusoidal signal.

As shown in FIG. 4, the zero-crossing time s _k of the signal to be measured deviates slightly from the zero-crossing time s' _k of the ideal sine wave signal. Therefore, the difference between the zero-crossing time s _k of the signal to be measured and the zero-crossing time s' _k of the ideal sine wave signal is ZCFΔs _k (k = 1, 2, 3, 4, 5 in Fig. 4). shown. Such ZCF may be derived for each measuring device MD.

FIG. 5 is a diagram illustrating an example of setup for ZCF derivation according to the present embodiment. For example, in FIG. 5, an audio player is used as the DUT 10, a first audio recorder is used as the measuring device MDa including the ADC 30a and the clock circuit 40b, and a second audio recorder is used as the measuring device MDb including the ADC 30b and the clock circuit 40b. shall be taken as a thing.

Furthermore, in FIG. 5, it is assumed that the measurement target signal output from the DUT 10 is a playback signal c(t) of the audio player. The reproduced signal c(t) may be, for example, a signal in a relatively low frequency region such as 12 kHz (hereinafter referred to as a "low frequency signal"). Note that the formula shown below is of course applicable not only to the audio player and the first and second audio recorders, but also to any DUT 10 and measuring device MD.

The audio player as DUT 10 includes a digital-to-analog converter (DAC) and a clock circuit. For example, in FIG. 5, the audio player is configured as a dual channel player including two single channel players corresponding to the left channel and right channel respectively, two DACs and two low pass players corresponding to the left channel and right channel respectively. It may also include a filter (LPF: Low Pass Filter). In the audio player, a playback waveform v[i] corresponding to each of the left channel and right channel is converted into an analog signal by a DAC, and the jitter n _jitter and amplitude from the clock circuit are converted into the analog signal via the LPF. (Amplitude Modulation) A reproduced signal c(t) which is the sum of n _AM and PI noise n _PI is generated and output.

The first audio recorder as the measuring device MDa includes an ADC 30a and a clock circuit 40a. For example, in FIG. 5, the first audio recorder is configured as a dual channel recorder (pseudo single channel recorder) including two single channel recorders corresponding to the left channel and right channel, respectively. It may also include two corresponding ADCs 30a and two LPFs. In the first audio recorder, an analog signal obtained by adding jitter a _jitter from the clock circuit 40a, amplitude a _AM , and PI noise a _PI to the playback signal c(t) output from the audio player passes through an LPF. , converted into a digital signal x[i] by the ADC 30a and output. Note that i is the index of the signal recorded by the first audio recorder.

The second audio recorder as measuring device MDb includes an ADC 30b and a clock circuit 40b. For example, in FIG. 5, the second audio recorder is configured as a dual channel recorder (pseudo single channel recorder) including two single channel recorders corresponding to the left channel and right channel, respectively. It may also include two corresponding ADCs 30b and two LPFs. In the second audio recorder, an analog signal obtained by adding jitter b _jitter from the clock circuit 40b, amplitude b _AM , and PI noise b _PI to the playback signal c(t) output from the audio player is passed through an LPF. , and is converted into a digital signal y[i] by the ADC 30b and output. Note that i is the index of the signal recorded by the second audio recorder.

The derivation unit 502 calculates the time difference between the zero crossing time s _k of the measurement target signal x[i] outputted from the first audio recorder as the measuring device MDa and the zero crossing time s' _k of the ideal sine wave signal. Perform ZCA to derive a certain ZCFΔs _k . ZCFΔs _k (k=1 to M) is expressed, for example, by the following equation 3.

Here, k is the zero-crossing time index, ω is the angular frequency, A ₀ is the amplitude, n _jitter (s' _k ) is the jitter of index k added by the audio player as DUT 10, n _PI ( s' _k ) is the PI noise of index k added by the audio player, a _PI (s' _k ) is the PI noise of index k added by the first audio recorder as the measuring device MDa, a _jitter (s ' _k ) is the jitter of index k added by the first audio recorder.

Further, the derivation unit 502 calculates the difference between the zero crossing time r k of the measurement target signal y[i] output from the second audio recorder as the measuring device MDb and the zero crossing time r _{' k} _of the ideal sine wave signal. ZCA is performed to derive the time difference _ZCFΔrk . ZCFΔr _k (k=1 to M) is expressed, for example, by the following equation (4).

Here, k, ω, A ₀ , n _jitter (s' _k ), and n _PI (s' _k ) are as explained in Equation 3. b _PI (s' _k ) is the PI noise of index k added by the second audio recorder as the measuring device MDb, and b _jitter (s' _k ) is the jitter of index k added by the first audio recorder. It is. Since the first and second audio recorders simultaneously sample the playback signal c(t) output from the audio player, the ideal sine wave signal zero-crossing time s' _k of the first and second audio recorders and _r'k are the same. Therefore, the deriving unit 502 can replace r _{' k} in Equation 4 with s _{' k} to obtain Equation 5.

Note that in FIG. 5, the reproduction signal c(t) corresponding to the left channel is input to the first and second audio recorders as measuring devices MDa and MDb, respectively, but the invention is not limited to this. For example, as shown in FIG. 6, a composite signal c(t) of reproduction signals corresponding to the left channel and the right channel may be input to the first and second audio recorders, respectively. As described above, the derivation unit 502 derives a plurality of ZCFs corresponding to each of the plurality of measuring devices MD (for example, the first and second audio recorders in FIG. 5).

The calculation unit 503 calculates the phase noise of the DUT 10 based on the plurality of ZCFs derived by the derivation unit 502. The calculation unit 503 may calculate the phase noise of the DUT 10 based on the difference between the first ZCF and the second ZCF of the plurality of ZCFs. Further, the calculation unit 503 may calculate the phase noise of the DUT 10 based on the sum of the first ZCF and the second ZCF of the plurality of ZCFs. Further, the calculation unit 503 may calculate the phase noise of each of the measuring devices MDa and MDb as well as the phase noise of the DUT 10.

For example, as shown in FIG. 5, a first ZCF (Δs _k ) corresponding to the first audio recorder as the measuring device MDa and a second ZCF (Δr _k ) is derived by ZCA, the calculation unit 503 calculates the first ZCF (Δs _k ), the second ZCF (Δr _k ), the difference between the first and second ZCFs (Δs _k −Δr _k ), Based on the sum of the first and second ZCFs (Δs _k +Δr _k ), the phase noise (σ _n2 ) of the DUT 10, the phase noise (σ _a2 ) of the measuring device MDa, and the phase noise (σ _b2 ) of the measuring device MDb are calculated. It may be calculated. For example, the four parameters (i.e., Δs _k , Δr _k , Δs _k −Δr _k , Δs _k +Δr _k ) used to calculate the phase noises σ _n2 , σ _a2 , and σ _b2 are, for example, the following equations 6 to 9. It is expressed as

Here, σ _n2 is the root mean square (RMS) of the ZCF of the audio player as the DUT 10, σ _a2 is the RMS of the ZCF of the first audio recorder as the measuring device MDa, and σ _b2 is the RMS of the ZCF of the second audio recorder as measuring device MDb. V{} indicates dispersion. Note that σ _n2 , σ _a2 and σ _b2 can also be considered as phase noise of the audio player and the first and second audio recorders.

Based on Equations 6 to 9, the calculation unit 503 can evaluate the phase noise of the audio player as the DUT 10 by distinguishing it from the phase noise of the first and second audio recorders as the measuring devices MDa and MDb. Note that since Equation 9 is used to verify the calculation, the phase noises σ _n2 , σ _a2 and σ _b2 may be calculated based on Equations 6 to 8 without using Equation 9. Equations 10 to 12 below are relational expressions based on the model.

Here, σ _{n2 ,} σ _a2 , and σ _b2 can also be said to be the phase noise of the audio player and the first and second audio recorders, as explained in Equations 6 to 9. k, ω, and A ₀ are as explained in Equation 3. j (s' _k ) indicates the jitter (n _jitter (s' _k )) input to the audio player as the DUT 10, and n _PI (s' _k ) indicates the PI noise (n _PI ( _s'k )). V{} indicates dispersion. In addition, a _jitter (s' _k ) indicates the jitter input to the first audio recorder as the measuring device MDa, and a _PI (s' _k ) is the PI noise added by the first audio recorder. be. b _jitter (s' _k ) indicates the jitter input to the second audio recorder as the measuring device MDb, and b _PI (s' _k ) is the PI noise added by the second audio recorder.

Note that, as shown in FIG. 6, in the case of a configuration in which the composite signal c(t) of the reproduction signals corresponding to the left channel and the right channel is input to the first and second audio recorders, respectively, the calculation unit 503 The jitter may be separated from the phase noise of the audio player. In the configuration shown in FIG. 6, the phase noise σ _n3 of the audio player may be expressed by Equation 13 below.

The calculation unit 503 may calculate the jitter j (s' _k ) of the audio player as the DUT 10 based on Equations 10 and 13 above. For example, the jitter may be expressed by Equation 14.

Here, dev{} indicates the standard deviation. j (s' _k ) is as explained in Equation 10, σ _n3 is the phase noise of the audio player as DUT 10 in the configuration shown in FIG. 6, and σ _n2 is the phase noise of the audio player as DUT 10 in the configuration shown in FIG. is the phase noise of

(motion)
FIG. 7 is a flowchart showing an example of the operation of the measurement system according to this embodiment. Note that the steps shown in FIG. 7 are only an example, and some steps (for example, step S107) may not be performed, or steps not shown may be added.

In step 101, the DUT 10 outputs the signal to be measured. The measurement target signal output from the DUT 10 includes phase noise in the DUT 10. In step S102, the distributor 20 distributes the measurement target signal output from the DUT 10 into N signals.

In step S103, N (N≧2) measurement devices MD independently convert the N measurement target signals distributed by the distributor 20 from analog signals to digital signals and output the converted signals. For example, in FIG. 1, N=2, and the measuring device MDa converts the signal to be measured from the distributor 20 from an analog signal to a digital signal using the ADC 30a, based on the clock signal from the clock circuit 40a, and outputs the converted signal. . Similarly, the measuring device MDb converts the signal to be measured from the distributor 20 from an analog signal to a digital signal using the ADC 30b, based on the clock signal from the clock circuit 40b, and outputs the converted signal.

In step S104, the signal processing device 50 acquires N measurement target signals respectively output from the N measurement devices MD. Each signal to be measured includes phase noise in the DUT 10 and phase noise in each measuring device. For example, in FIG. 1, the signal processing device 50 acquires the measurement target signal output from the measuring device MDa and the measuring target signal from the measuring device MDb.

In step S105, the signal processing device 50 derives N ZCFs, which are the time differences between the zero-crossing time of each of the N measurement target signals acquired in step S104 and the zero-crossing time of an ideal sine wave signal. do. For example, in FIG. 5, the signal processing device 50 uses an index of the zero-crossing time of the measurement target signal x[i] output from the first audio recorder as the measuring device MDa and the zero-crossing time of the ideal sine wave signal. ZCFΔs _k , which is the time difference of k, is derived. Further, the signal processing device 50 calculates the time difference of index k between the zero crossing time of the signal to be measured y[i] output from the second audio recorder as the measuring device MDb and the zero crossing time of the ideal sine wave signal. A certain _ZCFΔrk is derived.

In step S106, the signal processing device 50 may measure the phase noise of the N measurement devices MD as well as the phase noise of the DUT 10 based on the N ZCFs derived in step S105. For example, in the configuration shown in FIG. 5, the signal processing device 50 calculates ZCFΔs _k of the first audio recorder as the measuring device MDa, ZCFΔr _k of the second audio recorder as the measuring device MDb, and ZCFΔs _k and ZCFΔr _k Based on the difference between them, the phase noise σ _a2 of the measuring device MDa and the phase noise σ _b2 of the measuring device MDb are calculated together with the phase noise σ _n2 of the DUT 10. Further, the signal processing device 50 may verify the calculated phase noises σ _n2 , σ _a2 and σ _b2 based on the sum of ZCFΔs _k and _ZCFΔrk .

In step S107, the signal processing device 50 calculates the phase noise of the N measurement devices MD calculated in step S106, but evaluates only the phase noise of the DUT 10. Therefore, the phase noise of the N measuring devices MD can be removed analytically, rather than being removed due to the uncorrelation of the signals to be measured from the N measuring devices MD as in the cross-correlation spectrum method.

As described above, according to the measurement system 1 according to the present embodiment, the signal processing device 50 processes N measurement target signals (for example, in FIG. 5, x[i] and y[i]), it is possible to calculate not only the phase noise σ _n2 of the DUT 10 but also the phase noise of the N measurement devices MD (for example, in FIG. 5, the phase noises σ _n2 , σ _a2 and σ _b2 ). Only the phase noise of DUT 10 can be evaluated. Therefore, the phase noise of the DUT 10 can be measured with high precision even if an inexpensive measuring device MD that does not necessarily have low noise is used.

In addition, the signal processing device 50 detects not only the phase noise of the DUT 10 but also the phase noise of the N measuring devices MD (for example, in FIG. 5, the phase noise Since only the phase noise of the DUT 10 can be evaluated by calculating σ _n2 , σ _a2 , and σ _b2 ), the phase noise of the DUT 10 can be measured with high precision without increasing the measurement time unlike the cross-correlation spectrum method.

(evaluation)
Generally, when the signal to be measured is a low frequency signal (for example, a 12 kHz sine wave signal), it is difficult to apply the conventional cross-correlation spectrum method because down conversion cannot be applied to the low frequency signal. be. Therefore, by using the signal processing device 50 according to the present embodiment, even for low frequency signals to which down-conversion cannot be applied (for example, audio signals, etc.), the phase noise of the measuring device MD can be computationally removed and the DUT 10 It becomes possible to calculate phase noise with high accuracy.

On the other hand, when the signal to be measured is a signal in a relatively high frequency domain (hereinafter referred to as "high frequency signal", for example, a 27 MHz sine wave signal), down conversion can be applied to the high frequency signal, so conventional The cross-correlation spectrum method can be applied. Therefore, the phase noise measured by the signal processing device 50 and the phase noise measured using the conventional cross-correlation spectrum method will be compared and evaluated. Note that the high frequency signal is not limited to, for example, the above-mentioned 27 MHz, but may be a frequency signal of several MHz to several tens of GHz, etc.

FIG. 8 is a diagram showing an example of a comparison between the phase noise measured by the signal processing device 50 according to the present embodiment and the phase noise measured using the cross-correlation spectrum method. In FIG. 8, the DUT 10 is a commercially available crystal oscillator, and the measurement target signal output from the DUT 10 is a 27 MHz periodic signal. Furthermore, in FIG. 8, it is assumed that an inexpensive product with a relatively simple circuit configuration is used as the measuring device MD. In FIG. 8, the horizontal axis indicates frequency, and the vertical axis indicates power spectral density (PSD) of phase noise.

In FIG. 8, the transition of the PSD of the phase noise of the DUT 10 using the cross-correlation spectrum method (CSM) is shown. ◯ indicates the PSD of the phase noise of the DUT 10 calculated by the signal processing device 50.

As shown in FIG. 8, when a crystal oscillator is used as the DUT 10, the PSD (straight line) of the phase noise of the DUT 10 using the conventional cross-correlation spectrum method is the PSD (straight line) of the phase noise of the DUT 10 calculated by the signal processing device 50 ( 〇). This shows that the present embodiment can accurately measure the PSD of the phase noise of the crystal oscillator for high frequency signals to which the conventional cross-correlation spectrum method can be applied. As described above, according to the present embodiment, the phase noise of the DUT 10 can be measured with at least the same degree of accuracy as the conventional cross-correlation spectrum method, while reducing the measurement time using the relatively inexpensive measuring device MD. Note that FIG. 8 is merely an example, and the evaluation of the PSD of the phase noise of the DUT 10 according to this embodiment is not limited to the evaluation shown in FIG. 8. For example, in FIG. 8, both measurement cost and measurement time can be reduced by measuring the phase noise of the DUT 10 with the signal processing device 50 using a relatively inexpensive product as the measuring device MD of the measurement system 1 of this embodiment. We have achieved this, but are not limited to this. At least the measurement time may be reduced by using a relatively inexpensive product as the measuring device MD of the measuring system 1 of this embodiment and measuring the phase noise of the DUT 10 with the signal processing device 50.

Furthermore, while the phase noise of the DUT 10 using the conventional cross-correlation spectrum method is an asymptotic autocorrelation spectrum, the signal processing device 50 can calculate the phase noise of the DUT 10 as an absolute value.

As described above, according to the measurement system 1 according to the present embodiment, it is possible to measure the phase noise of the DUT 10 while reducing at least one of measurement cost and measurement time.

(Other embodiments)
In the above embodiment, the case where the number N of measuring devices is 2 has been mainly described, but the measurement system 1 according to the present embodiment is not limited to this, and can also be applied when N is 2 or more. . The case where N≧2 will be described below.

FIG. 9 is a diagram showing an example of a generalized configuration of the measurement system according to this embodiment. FIG. 9 differs from FIG. 1 where N=2 in that the number N of multiple measuring devices is generalized to any integer greater than or equal to 2. Below, differences from FIG. 1 will be mainly explained. As shown in FIG. 9, the measurement system 1 differs from FIG. 1 in that it includes N measuring devices MD _n (1≦n≦N) instead of the two measuring devices MDa and MDb. The measuring device MD _n has an ADC 30 _n and a clock circuit 40 _n .

As shown in FIG. 9, in the measuring device MD _n , the measurement target signal output from the DUT 10 is converted from an analog signal to a digital signal by the ADC 30 _n based on the clock signal from the corresponding clock circuit 40 _n , and is output. be done.

The acquisition unit 501 of the signal processing device 50 acquires the measurement target signal x _k ⁽ⁿ⁾ (1≦n≦N) output from the measuring device MD _n . The measurement target signal x _k ⁽ⁿ⁾ includes the phase noise of the DUT 10 and the phase noise of the measuring device MD _n .

The derivation unit 502 of the signal processing device 50 uses ZCA to calculate ZCFΔs k which is the time difference between the zero crossing time of the measurement target signal x _k ⁽ⁿ⁾ acquired by the acquisition unit 501 and the zero crossing time of the ideal sine wave _signal. ⁽ⁿ⁾ (1≦n≦N) is derived.

The calculation unit 503 of the signal processing device 50 calculates the phase noise of the DUT 10 based on the ZCFΔs _k ⁽ⁿ⁾ derived by the derivation unit 502. The calculation unit 503 may calculate the phase noise of the measuring device MD _n as well as the phase noise of the DUT 10 based on ZCFΔs _k ⁽ⁿ⁾ .

Specifically, the calculation unit ₅₀₃ calculates the first ZCFΔs _k ⁽ⁱ⁾ (1≦i≦N−1 ⁾ and the second ZCFΔs _k ^{(j )} The phase noise of the DUT 10 may be calculated based on the difference of (i+1≦j≦N) and the sum of the first ZCFΔs _k ⁽ⁱ⁾ and the second ZCFΔs _k ^(j) . For example, the calculation unit 503 calculates the first ZCFΔs _k ⁽ⁱ⁾ (1≦i≦N-1) of the measuring device MD _i (1≦i≦N-1) and the first ZCFΔs k (i) (1≦i≦N-1) and the measuring device MD _j (i+1≦j≦N). Based on the difference and the sum of the second ZCFΔs _k ^(j) , the phase noise σ _n2 ^{(i, j)} of the DUT 10 may be calculated from the measuring instruments MD _i and MD _j , for example, using Equation 15 below. . As shown in FIG. 9, when 1≦i≦N−1 and i+1≦j≦N, according to Equation 15, N(N−1)/2 σ _n2 ^{(i, j)} are calculated.

The calculation unit 503 may calculate the phase noise σ _n2 of the DUT 10 based on N(N−1)/2 phase noises σ _n2 ^{(i, j)} . For example, the calculation unit 503 may calculate the phase noise σ _n2 of the DUT 10 using Equation 16, Equation 17, or Equation 18 below. Note that the calculation unit 503 may calculate the phase noise of the measuring device MD _n (1≦n≦N) as well as the phase noise σ _n2 of the DUT 10, but the description of the equation will be omitted.

In Equation 16, Equation 17, or Equation 18 below, M is the number of zero crossing times, and 1≦k≦M. N is the number of measuring devices MD as described above, Δs _k ⁽ⁱ⁾ is the first ZCF of measuring devices MD _j (1≦i≦N−1), and Δs _k ^(j) is the number of measuring devices MD It is the second ZCF of MD _j (i+1≦j≦N). V{} indicates dispersion.

E ₁ , E ₂ and E ₄ in Equation 19 are represented by Equations 20, 21 and 22 below. dev{} indicates standard deviation.
(Formula 20)
E ₁ =dev{Δs _k }
(Formula 21)
E ₂ =dev{Δr _k }
(Formula 22)
E ₄ =dev{Δs _k +Δr _k }

The embodiments described above are intended to facilitate understanding of the present invention, and are not intended to be interpreted as limiting the present invention. Each element included in the embodiment, as well as its arrangement, material, conditions, shape, size, etc., are not limited to those illustrated, and can be changed as appropriate. Further, it is possible to partially replace or combine the structures shown in different embodiments.

DESCRIPTION OF SYMBOLS 1... Measurement system, 10... DUT, 20... Distributor, 30... ADC, 40... Clock circuit, 50... Signal processing device, MD... Measuring instrument, 501... Acquisition part, 502... Derivation part, 503... Calculation part

Claims

an acquisition unit that acquires a plurality of measurement target signals obtained by independently analog-to-digital conversion of the measurement target signals output from the measurement target device by the plurality of measuring instruments;
a derivation unit that derives a plurality of zero-crossing fluctuations (ZCF), which are time differences between zero-crossing times of each of the plurality of measurement target signals and a zero-crossing time of an ideal sine wave signal;
a calculation unit that calculates phase noise of the device to be measured based on the plurality of ZCFs;
A signal processing device comprising:
The calculation unit calculates phase noise of the measurement target device based on a difference between a first ZCF and a second ZCF of the plurality of ZCFs.
The signal processing device according to claim 1.
The calculation unit calculates the phase noise of the measurement target device based on the sum of the first ZCF and the second ZCF of the plurality of ZCFs.
The signal processing device according to claim 2.
The calculation unit calculates the phase noise of each of the plurality of measurement devices as well as the phase noise of the measurement target device.
The signal processing device according to any one of claims 1 to 3.
The calculation unit calculates jitter of the device to be measured based on the phase noise of the device to be measured.
The signal processing device according to claim 4.
The signal processing device
The measurement target signal output from the measurement target device is independently analog-to-digital converted by multiple measuring instruments to obtain multiple measurement target signals,
Deriving a plurality of zero-crossing fluctuations (ZCF), which are time differences between the zero-crossing time of each of the plurality of measurement target signals and the zero-crossing time of an ideal sine wave signal,
calculating phase noise of the device to be measured based on the plurality of ZCFs;
Signal processing method.
computer,
an acquisition unit that acquires a plurality of measurement target signals obtained by independently analog-to-digital conversion of the measurement target signals output from the measurement target device by the plurality of measuring instruments;
a derivation unit that derives a plurality of zero-crossing fluctuations (ZCF), which are time differences between zero-crossing times of each of the plurality of measurement target signals and a zero-crossing time of an ideal sine wave signal;
a calculation unit that calculates phase noise of the device to be measured based on the plurality of ZCFs;
A program to make it work.