JPH0666852A - Spectrum measuring device - Google Patents

Abstract

PURPOSE:To determine a measuring condition within a shorter time while ensuring sure reproducibility by fuzzy inference and neural net at the time of determining optimum measuring conditions such as the band width, sweep speed and video band of a spectrum analyzer. CONSTITUTION:A wireless equipment 1 is controlled, to be in the operating state with the operation control signal 105 of a control part 4 to provide a desired wireless output 102. A neural net 50 outputs a condition signal 102 according to a preliminarily learned network from a priority signal 104 weighted by the inspection system or inspection speed from the control part 4. Under the condition according to the condition signal 102, a spectrum analyzer 2 measures the spectrum of the wireless equipment 11 under an optimum measuring condition.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a spectrum measuring device.

[0002]

2. Description of the Related Art A conventional spectrum measuring apparatus includes a spectrum analyzer for inputting a radio signal output from a radio device and a condition signal for determining its own operating condition, and an operation control signal for inputting to the radio device to determine its operation. The control unit outputs a register designation signal, and the register unit outputs the condition signal by inputting the register designation signal output from the control unit.

Next, a conventional spectrum measuring apparatus will be described in detail with reference to the drawings.

FIG. 5 is a block diagram showing a conventional example. The wireless device 1 is set to an inspectable state by receiving output control of the transmitter and channel designation by the operation control signal 105 output from the control unit 4. The wireless device 1 set to the inspectable state outputs the wireless signal 101. The spectrum analyzer 2 sets the sweep speed, the decomposition bandwidth, and the video bandwidth specified by the condition signal 102 output from the register unit 3. On the other hand, the control unit 4 determines the optimum measurement condition according to information obtained by trial and error by an expert in advance, and the register designation signal 1 for selecting the optimum measurement condition.
03 is output. The register unit 3 has a register designation signal 10
3 outputs a condition signal 102 such as a sweep speed, a decomposition bandwidth, a video band, which is held in the register unit 3 in advance. In this way, the spectrum analyzer 2 described above measures the transmission spurious present in the radio signal 101. Here, as described above, the spectrum measurement of the wireless device 1 is performed most efficiently, in other words, in order to complete the measurement at high speed without overlooking the spurious, it is necessary to combine the optimum sweep speed, decomposition bandwidth, and video bandwidth. is there. However, in the conventional spectrum measuring apparatus, it is necessary to expect the know-how of a skilled person to make this determination, and to determine the measurement condition through trial and error, which causes a problem that it takes time to start the measurement. Moreover, the difference due to the know-how among the individual experts is unavoidable, and each judgment varies, resulting in a problem in the stability of the spurious measurement conditions. In addition, there are many parts that are left to the expert's individual know-how, in other words, the individual's judgment, and there is a risk of variations in inspection quality from this aspect as well.

[0005]

The above-described conventional spectrum measuring apparatus needs to optimally set the sweep speed, the decomposition bandwidth, and the video band in order to detect spurious that varies variously according to the characteristics of the radio equipment. However, there is a drawback that the optimum combination is found from trial and error based on the know-how of the skilled person, so that it takes time to set it and it is not possible to meet the demand for improving the efficiency of the inspection. In determining the condition, the same condition is not always defined due to the difference in know-how between skilled persons, and there is a problem in ensuring the quality of the inspection.

[0006]

A spectrum measuring apparatus according to a first aspect of the present invention includes a spectrum analyzer for inputting a radio signal output from a radio device and a condition signal for determining its own operating condition, and a spectrum analyzer input to the radio device. The control unit includes an operation control signal for determining an operation and a priority signal, and a reasoning unit for inputting the priority signal and outputting a condition signal.

The spectrum measuring apparatus of the second invention comprises a spectrum analyzer for inputting a radio signal output from a wireless device and a condition signal for determining its own operating condition, and operation control for inputting to the wireless device and determining its operation. A control unit for outputting a signal and a priority signal, and inputting the priority signal,
And an inference unit that outputs a condition signal.

[0008]

Embodiments of the present invention will now be described in detail with reference to the drawings.

FIG. 1 is a block diagram showing a first embodiment of the present invention. The wireless device 1 is set to an inspectable state by receiving output control of the transmitter and channel designation by the operation control signal 105 output from the control unit 4. The wireless device 1 set to the inspectable state outputs the wireless signal 101.
The spectrum analyzer 2 sets the sweep speed, the decomposition bandwidth, and the video bandwidth specified by the condition signal 102 output from the inference unit 5. On the other hand, the control unit 4 outputs the weighted priority signals to the inference unit 5 when the emphasis is placed on detecting spurious reliably and when the measurement is completed at high speed. The inference unit 5 performs a fuzzy inference on the input priority signal 104 and outputs the above-mentioned condition signal 02.
Is output. In this way, the spectrum analyzer 2 described above measures the transmission spurious present in the radio signal 101.

When executing the fuzzy inference, the fuzzy inference is performed by a predetermined manbassian function. As the Mambassian function, as shown in FIG. 2, L, M, and H functions may be prepared for each fuzzy set. Also, priority signals used for fuzzy inference, specifically inspection speed priority signals, inspection system priority signals and condition signals, specifically sweep speed, decomposition bandwidth,
The fuzzy rules for determining the video bandwidth are prepared according to the standardized large and small concept, and are shown in FIG.
It shows in (a)-(c). Here, SL, SM, SH are speed priority signals, PL, PM, PH are decomposition bandwidths, WS,
WM and WH are fuzzy sets of sweep rate, DL, DM, DH, video band, that is, a condition signal. Furthermore, the final method of determining the condition signal may be performed by using the center of gravity method or the like.

As described above, the optimum condition signal can be always determined by using fuzzy reasoning with respect to a specific request at the time of spurious measurement, without depending on trial and error of an expert.

FIG. 4 is a block diagram showing a second embodiment of the present invention. The wireless device 1 is set to an inspectable state by receiving output control of the transmitter and channel designation by the operation control signal 105 output from the control unit 4. The wireless device 1 set to the inspectable state outputs the wireless signal 101.
The spectrum analyzer 2 sets the sweep speed, the decomposition bandwidth, and the video bandwidth specified by the condition signal 102 output from the neural network 5. On the other hand, the control unit 4 outputs the weighted priority signals to the inference unit 5 when the emphasis is placed on detecting spurious reliably and when the measurement is completed at high speed. The neural network 50 performs fuzzy inference 104 on the input priority signal 104 and outputs the above-mentioned condition signal 102. In this way, the above-mentioned spectrum analyzer 2 operates as the radio signal 1
Measure the transmit spurious present in 01.

In the spectrum measuring apparatus of the second embodiment, the neural network 6 is used to output the condition signal 102.
It is necessary to realize the evaluation function that is placed in advance. Of the many combinations of measurement conditions, in other words, the output condition signal 102 is evaluated with respect to various combinations of priority signals 104. Evaluation is performed by a skilled worker. In this way, the judgment criteria of the expert are realized in the neural network of this spectrum measuring apparatus.

As described above, the neural network can always determine the optimum condition signal for a specific request at the time of spurious measurement, without depending on the trial and error of an expert.

[0015]

According to the spectrum measuring apparatus of the present invention, when the optimum measurement condition is specified according to the characteristics of each radio, instead of determining the measurement condition by trial and error by the know-how of a skilled worker. Since the measurement conditions are determined by a fuzzy reasoning and a pre-learned neural network, the inspection can be performed in a short time without wasting the trial and error time for determining the conditions without being influenced by the skill level of the individual. There is an effect that can start. In addition, since spurious measurement and inspection are performed under clear and reproducible conditions that are not buried in the senses of the individual, there is an effect that an inspection error does not occur.

[Brief description of drawings]

FIG. 1 is a block diagram showing a first embodiment of the present invention.

FIG. 2 is a diagram showing an example of a membership function.

3A to 3C are diagrams showing an example of a fuzzy rule.

FIG. 4 is a block diagram showing a second embodiment of the present invention.

FIG. 5 is a block diagram showing a conventional example.

[Explanation of symbols]

 1 wireless device 2 spectrum analyzer 3 register unit 4 control unit 50 neural network 101 wireless signal 102 condition signal 103 register designation signal 104 priority signal 105 operation control signal

Claims (2)

[Claims] 1. A spectrum analyzer for inputting a radio signal output from a wireless device and a condition signal for determining its own operating condition, and control for outputting an operation control signal and a priority signal input to the wireless device for determining its operation. A spectrum measuring apparatus comprising: a unit and an inference unit that inputs the priority signal and outputs a condition signal. 2. A spectrum analyzer for inputting a radio signal output from a wireless device and a condition signal for determining its own operating condition, and a control for outputting an operation control signal and a priority signal input to the wireless device for determining its operation. A spectrum measuring apparatus comprising: a unit and a neural network which inputs the priority signal and outputs a condition signal.