无线电频率测试与测量实用手册：技术员必备

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《实用无线电频率测试与测量：技术员手册》是一本深入浅出的指南，专为从事无线电频率系统安装、性能验证、维护和故障排查的专业人员而设计。作者约瑟夫·J·卡特是一位在该领域有着丰富经验的专家，他带领读者探索无线电频率测试与测量的世界。本书首先介绍各种测量仪器的基础理论，涵盖了不同类型的测量设备及其用途。卡特详细讲解了测试设备的选择、设置和操作流程，强调了理解基本原理的重要性。无论是工程技术人员、业余无线电爱好者还是对RF技术感兴趣的业余人士，都能从中受益匪浅。书中特别关注实际应用，提供了一系列实用的步骤和案例，帮助读者掌握如何进行有效的测试与测量，确保无线通信系统的性能稳定。无论是初学者、中级用户还是高级专业人士，都能在书中找到适合自己的内容，从而提升技能和解决问题的能力。作者以其丰富的专业知识，将复杂的理论知识转化为易于理解的操作指导，使得这本书成为RF技术领域不可或缺的参考工具。此外，版权方面，本书受到严格保护，任何复制、存储或未经许可的传播行为都需要事先获得Elsevier出版社的书面许可。《实用无线电频率测试与测量：技术员手册》是一本全面而实用的手册，不仅有助于技术人员提升专业素养，也是所有无线电频率技术从业人员和兴趣者的宝贵参考资料。无论是为了学习新技能，还是解决工作中遇到的问题，这本书都是一个理想的起点。

Measurement

Errors

values, or

(255)

different segments. The resolution of that system depends

on the value of the measured parameter change that must occur in order to change

the least significant bit in the data word. For example, if

bits are used to repre-

sent a voltage range of

volts, then the resolution is

(10

0)/255,

or 0.039

(e.g., 39 mV) per bit. This resolution is often specified as the

”1-LSB”

resolution of

the instrument.

MEASUREMENT ERRORS

measurement is perfect, and measurement apparatus are never ideal,

there

will always be some

error

in all forms of measurement.

error is a deviation be-

tween the actual value of a measurand and the indicated value produced by the

sensor or instrument used to measure the value.

Error

is inherent and is not thefault

of the person making the measurement.

Error is not the same as a mistake! Under-

standing error can greatly improve our effectiveness in making measurements.

Error can be expressed in either ”absolute” terms or using a relative scale.

absolute error would be expressed in terms of “X-Volts

Y-mV,” or some other

such unit, while a relative error expression would be

“X

Volts.”

an electri-

cal circuit, a voltage might be stated as

“4.5

volts

1%”

(or

“4.5

Volts

0.010

volts”). Which expression to use may be a matter of custom, convention, personal

choice, or best utility, depending on the situation.

There are four general categories of error:

theoretical error, static error, dynamic

error,

and

instrument insertion error.

Theoretical Error

All measurements are based on some measurement theory that predicts how a

value will behave when a certain measurement procedure is applied. The mea-

surement theory is usually based on some theoretical model of the phenomenon

being measured, or an intellectual construct that tells us something of how that

phenomenon works. It is often the case that the theoretical model is valid only over

a specified range of the phenomenon. For example, nonlinear phenomena that

have a quadratic, cubic, or exponential function can be treated as a straight line lin-

ear function over small, carefully selected sections of the range.

This

would be a

first-order approximation. Electronic sensor outputs often fall into this class.

Alternatively, the actual phenomenon may be terribly complex, or even

chaotic, under the right conditions,

the model is therefore simplified for many

practical measurements.

equation that is used as the basis for a measurement

theory may be only a first-order approximation of the actual situation. For exam-

ple, consider an example from the medical world: the

mean arterial pressure

(MAP)

that is often measured in clinical medicine and medical sciences research situa-

tions. The

MAP

approximation equation used by clinicians is:

Systolic

Diastolic

INTRODUCTION TO RADIO FREQUENCY ELECTRONICS AND MEASUREMENT THEORY

This

equation is really only an approximation (and holds true mostly for well

people, not some sick people on whom it is applied) of the equation that expresses

the mathematical integral of the blood pressure over a cardiac cycle: that is, the

time average of the arterial pressure. The actual expression is written

the nota-

tion of calculus, which is beyond the math abilities of many of the people who use

the clinical version above:

2P(t)dt

The approximation works well, but is subject to greater error than the actual

function due to the theoretical simplification of the first equation. What’s funny

about the first-order approximation of

MAP

blood pressure is that it often fails

most on a very specific group of patients:

sick

peopZe!

Static

Errors

Static errors include a number of different subclasses that are all related in that they

are always present even

unchanging systems (thus, they are not dynamic errors).

These errors are not functions of the time or frequency variation.

Reuding

Stutic

Errors

These errors result from misreading the display output of the sensor system. An

analog meter uses a pointer to indicate the measured value. If the pointer is read at

an angle other than straight on, then a

puralZax

reading

error

occurs. Another read-

ing error is the

interpolation

error,

an error made

judging or estimating the correct

value between two calibrated marks on the meter scale (Figure

1.8).

Still another

reading error occurs if the pointer on a meter scale is too broad and covers several

marks at once.

related error seen in digital readouts is the

last

digit

bobble

error,

or the

count error.

digital displays, it is often the case that the least significant digit on

the display will flip back and forth between two values. For example, a digital volt-

meter might read

”12.24”

and

”12.25”

alternately, depending on when you looked

at it, despite the fact that absolutely no change occurred in the voltage being mea-

sured. This phenomenon occurs when the actual voltage is midway between the

two indicated voltages. Error, noise, and uncertainty

the system will make a volt-

age close to

12.245

volts bobble back and forth between the

two

permissible output

Figure

1.8

Analog meter indicating reading resolution problem.

Measurement Errors

states (12.24 and 12.25) on the meter.

example where “bobble” is of significant

concern is the case where some action is taken when a value changes above or be-

low a certain quantity-and the digital display bobbles above and below the criti-

cal threshold.

Environmental Static Errors

All sensors and instruments operate in an environment, which sometimes affects

the output states. Factors such as temperature (perhaps the most common error-

producing agent), electromagnetic fields, and radiation

must

considered

elec-

tronic measurement systems.

Characteristic Static Errors

These static errors are still left after reading errors and environmental errors are ac-

counted for. When the environment is well within the allowable limits and is

un-

changing, and when there is no reading error, there will be a residual error

remaining that is a function of the measurement instrument or process itself. Er-

rors found under this category include zero offset error, gain error, processing er-

ror, linearity error, hysteresis error, repeatability error, resolution error, and

forth. Also included in the characteristic error is any design or manufacturing de-

ficiencies that lead to error. Not all of the ”ticks” on the ruler are truly 1.0000 mm

apart at all points along the ruler. While it is hoped that the errors are random,

that the overall error is small, there is always the possibility of a distinct bias or er-

ror trend in any measurement device.

For digital systems one must add to the resolution error a

quantization

error

that emerges from the fact that the output data can only take on certain discrete val-

ues. For example, an 8-bit analog-to-digital converter allows 256 different states,

volt range is broken into 256 discrete values in 39.06 mV steps. A poten-

tial that is between two of these steps is assigned to one or the other according to

the rounding protocol used in the measurement process.

example is the weight

sensor that outputs 8.540 volts, on a 10-volt scale, to represent a certain weight. The

actual &bit digitized value may represent 8.502,8.541, or 8.580 volts because of the

0.039 volt quantization error.

Dynamic Errors

Dynamic errors arise when the measurand is changing or in motion during the

measurement process. Examples of dynamic errors include the inertia of mechan-

ical indicating devices (such as analog meters) when measuring rapidly changing

parameters. There are a number of limitations in electronic instrumentation that

fall into this category, especially cases where a frequency, phase, or slew rate limi-

tation is present.

Instrument Insertion Error

The fundamental rule of making measurements is that

the measurement

process

should not significantly alter the phenomenon being measured.

Otherwise, the measur-

and is actually the altered situation, not the original situation that is of true inter-

est. Examples

this error are

found

many

places.

For example,

voltmeter

with

INTRODUCTION TO RADIO FREQUENCY ELECTRONICS AND MEASUREMENT THEORY

a low impedance of its own could alter resistance ratios in an electrical circuit and

produce a false reading. This problem is especially seen when using cheap analog

volt-ohm-milliammeters that have a low sensitivity, hence a low impedance, to

measure a voltage in a circuit. The meter resistance

is effectively shunted across

the circuit resistance across which the voltage appears.

Instrument insertion

errors

can usually be minimized by good instrument de-

sign and good practices.

measurement device has zero effect on the system be-

ing measured, but one can reduce the error to a very small value by appropriate

selection

methods and devices.

DEALING

WITH

MEASUREMENT

ERRORS

Measurement error can be minimized through several methods, some of which

are lumped together under the rubric "procedure" and others under the legend

"statistics."

Under "procedure" one can find methods that will reduce, or even minimize,

error contributions to the final result. For example, in an electrical circuit, use a volt-

meter that has an extremely high input impedance compared with circuit resis-

tances. The idea is to use an instrument that least disturbs the thing being

measured.

significant source of measurement error in some electronic circuits is

ground loop voltage drops and ground plane noise. This voltage may add or sub-

tract from the reading of output voltage

V,,

depending on its phase and polarity.

way to reduce total error is to use several different instruments to measure

the same parameter.

Figure 1.9 we see an example where the current flow in a

circuit is being measured by three different ammeters:

M1,

M2, and M3. Each of

these instruments will produce a result that contains a small error term decorre-

lated from the error of the others and not biased (unless, by selecting three identi-

cal model meters, we inherit some characteristic error of that particular type of

instrument). We can estimate the correct value of the current flow rate by taking

the average of the three:

One must be careful to either randomize the system in cases where the sen-

sor or instruments used tend to have large error terms biased in one direction, or

calibrate the average error

that it may be subtracted out of the final result.

Error

Contributions Analysis

error

analysis

can be performed in order to identify and quantify all contribut-

ing sources of error in the system.

determination is then made regarding the ran-

domness

those errors, and a

worst

case

analysis

made. Under the

worst

case,

one assumes that all of the component errors are biased in a single direction and

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