微波散射与辐射模型实战指南

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"《Microwave.Scattering.And.Emission.Models.For.Users.》是一本专为微波遥感领域的专业人员设计的实用散射和发射数据模型指南。书中详细介绍了电磁波在微波频段与地球表面场景相互作用的理论和应用。随书附带的CD-ROM包含了所有散射和发射模型的Mathematica代码，方便读者将其应用于自己的项目中。本书旨在帮助工程师理解和运用这些模型，提升他们在微波遥感工作中的实践能力。" 该书是Artech House Remote Sensing Series系列中的一部作品，专注于数值模拟技术在微波散射和发射模型中的应用。微波遥感是一种利用微波辐射对地表进行非接触式探测的技术，广泛应用于气象预报、环境监测、地质勘查等领域。书中包含的技术描述、程序和计算机算法经过了精心开发，并已在多个实际应用中得到验证。尽管作者在编写过程中已尽最大努力确保准确性和可靠性，但书中的方程式、程序和步骤仍然可能含有错误，或不符合特定的商业标准。因此，读者在使用这些模型解决可能影响人身安全或财产损失的问题时，应谨慎对待。作者、编辑和出版商均不承担因使用书中内容导致的直接、间接或后果性损害的责任。书中的Mathematica代码是将理论转化为实践的关键工具，用户可以利用这些代码对不同的地表特征（如土壤、植被、水体等）进行散射和发射特性的模拟分析。通过这些模型，工程师可以预测微波信号如何被地表反射、吸收和传播，进而解析地表特性，实现遥感图像的解释和分析。《Microwave.Scattering.And.Emission.Models.For.Users.》为微波遥感专业人士提供了一个强大的工具箱，有助于他们深入理解微波遥感的基本原理，以及如何运用数值模拟方法来处理和分析实际问题。通过学习和应用书中内容，读者可以提高其在微波遥感领域的专业技能，从而在各种应用中做出更精确的判断和决策。

Microwave Scattering and Emission Models for Users

xviii

[8] Elachi, C., Introduction to Physics and Techniques of Remote Sensing, New York: John Wiley,

1987.

[9] Elachi, C., Spaceborne Radar Remote Sensing: Applications and Techniques, New York: IEEE

Press, 1988.

[10] Fung, A.K., Microwave Scattering Models and Their Applications, Norwood, MA: Artech House,

1994.

[11] Ishimaru, A., Electromagnetic Wave Propagation, Radiation and Scattering, Upper Saddle River,

NJ: Prentice-Hall, 1991.

[12] Steinberg, B.D., and H.M. Subbaram, Microwave Imaging Techniques, New York: John Wiley,

1991.

[13] Ulaby, F.T., R.K. Moore, and A.K. Fung, Microwave Remote Sensing: From Theory to Applica-

tions, Vol. 3, Norwood, MA: Artech House, 1986.

Chapter 1

Introduction to Microwave Scattering and

Emission Models for Users

1.1 INTRODUCTION

The purpose of this user-oriented book is to provide simple, relatively easy to use

surface and volume scattering and emission models that represent the interaction

between electromagnetic waves and a scene on the Earth surface in the microwave

region. Starting from the simplest kinds of models with limited range of applicabil-

ity, we extend the coverage of the scattering models in several directions: (1) from

low- to high-frequency regions, (2) from geometrically isotropic to anisotropic, (3)

from single to more than one scale of roughness, (4) from surface scattering to sur-

face-volume scattering, and (5) from backscattering to bistatic scattering and emis-

sion. Complex scattering models that require extensive numerical evaluation are

excluded, because they are not useful for most users and are more likely to be mis-

interpreted. Also excluded are the effects of multiple scattering beyond the second

order. The standard moment method (MM) simulation for surface scattering in two

dimensions is provided to readers interested in verifications of wave scattering

from isotropically rough surfaces. The extension of MM to three-dimensional sur-

face scattering is available in the literature but is not included, because it requires

intensive computation. However, a method of extending the two-dimensional

numerical simulation results to three dimensions is given for geometrically, isotro-

pically rough, dielectric surfaces in like polarization, because this method provides

a substantial saving in computation for this special case. Where possible model

predictions are compared with field data to lend credence to its applicability.

In applying a scattering model to a randomly rough surface it is important to

note that at a given frequency and look angle, scattering is dominated by surface

roughness scales over which the scattered signal remains correlated. For surfaces

with a single scale of roughness, there is generally no problem detecting the rele-

Microwave Scattering and Emission Models for Users

vant surface characteristics, regardless of its being large or small compared to the

exploring wavelength. For this special case, the scattered signal will remain corre-

lated over the correlation length of the surface until the high-frequency limit is

reached. In the limiting case, scattering is proportional to the slope distribution

instead of the roughness scale of the surface. In practice, natural surfaces generally

contain many roughness scales. For these multiscale surfaces, the scattered signal

is sensitive to and represents only an effective small-scale roughness with a wave

number, , rms (root mean square) height, , and their product, , smaller than

one. The reason is that the scattering pattern of the larger scale roughness is dis-

torted or completely destroyed by the smaller roughness scales riding on it, so that

the information about its presence is missing in the scattered signal. In other words,

the scattered signal cannot remain correlated over the correlation length of the

large-scale roughness. As a result, the high-frequency limit is rarely reached in

field measurements, and surface parameters in a scattering model are generally

effective parameters which depend on the view angle and the sensing frequency.

From a remote sensing standpoint this means that one can only retrieve roughness

scales corresponding to surface spectral components to which the radar signal is

responding with some degree of coherency. In summary, the point to keep in mind

is that while a scattering model must approach the optical limit mathematically as

the sensing wavelength gets smaller, this is generally not observed experimentally

in the field. In most practical situations, as the sensing wavelength gets smaller, the

radar simply sees a smaller scale of roughness, because natural scenes usually con-

tain many scales of roughness. This is why measured surface parameters may not

agree with the parameters in a scattering model and a scattering model based on

geometric optics does not find many applications in a natural environment.

The frequency and angle dependence concept discussed above has general

applicability in microwave remote sensing. A target is recognized through its scat-

tering pattern. Once a significant portion of this pattern is distorted for whatever

reason, the presence of the target may no longer be detectable.

To help the reader select a model of special interest we have categorized the

scattering models in terms of scattering geometry, scale size normalized to the

exploring wave number, and surface with or without cover. Each chapter deals with

a scattering model with many choices of scene structure or properties. For each

choice there is a computer program to generate the scattering coefficient with scene

and system parameters specified by the user. As an example, the standard small

perturbation model for rough surface scattering will form a chapter for surfaces

with small scales of roughness. The type of surface is determined by choosing a

surface correlation function (or a surface roughness spectrum) from a number of

available correlation functions. Once a choice is made, the user can specify system

and scene parameters to calculate the scattering coefficient.

k σ kσ

Introduction to Microwave Scattering and Emission Models for Users

1.2 ORGANIZATION

Surface scattering is caused by dielectric discontinuities at all points on a surface

boundary; while volume scattering is caused by dielectric discontinuities distrib-

uted throughout a volume. Thus, a bare Earth surface can generate surface scatter-

ing but when it is covered by vegetation, snow or a layer of loose dirt, there will be

volume scattering as well. It is important to note that to an electromagnetic wave, a

true surface is a continuous surface relative to the electromagnetic wavelength, for

example, any crack in the surface or pebbles standing on a surface must be small

compared to the wavelength. Thus, a plowed field may act as a soil surface or as a

collection of objects (soil clots) sitting on a soil surface depending on the exploring

frequency. In the latter case, the problem is no longer a pure surface scattering

problem. Hence, two types of models are discussed in this book: one type deals

exclusively with surface scattering and emission models with a variety of surface

conditions, and the other type provides scattering or emission models for surfaces

with some kind of cover, which requires the consideration of volume scattering and

surface-volume interaction.

In choice of models, preference is given to simple scattering and emission

models that are easy to evaluate, have an algebraic form, or have a wide range of

applicability in frequency, angular range, polarization, and/or roughness scales. In

surface scattering, each chapter deals with only one scattering model and a variety

of scene conditions. For example, in Chapter 2 we present the small perturbation,

surface backscattering model (SPMB) by giving explicit expressions of the model.

This model is for small-scale roughness. We consider five different surface types

defined by five different surface correlation functions. A correlation function nor-

malized to the surface variance, , usually contains only one parameter, the corre-

lation length, , for example, the exponential correlation function, .

Other correlation functions such as the x-power correlation function,

, represents a class of surfaces instead of just one

type of surface. This is because we have an additional parameter to choose in the x-

power correlation by selecting different values of x. Associated with each scatter-

ing model a computer program in Mathematica 5.0 is prepared as a package, which

has a functional name, . The arguments of this function

are the surface, geometric, physical, and system parameters along with the symbol,

sp, which specifies one of the five correlation functions to be selected by the user.

The program is set up to evaluate this function with outputs in backscattering coef-

ficients. It can also plot the model results along with experimental data, which have

to be entered separately in a list format to allow comparisons between model pre-

dictions and measurements.

LrL⁄–[]exp

ρ r() 1 rL⁄()

+[]

x–

x 1>,=

SPMB f σ L θε

sp x,,,,,,[]

Microwave Scattering and Emission Models for Users

In Chapter 3, we present the simplified integral equation surface backscatter-

ing model (IEM) which does not fully account for the phase in Green’s function. It

is more complex than the SPMB, but it allows surfaces with larger rms height and

correlation length. The main restriction here is that the rms slope of the surface

should be less than 0.3. This is imposed to avoid excessive contribution from mul-

tiple scattering which requires a much more complex scattering model containing

several two-dimensional integrations. The format of presentation is similar to

Chapter 2, but it has many more successful comparisons with moment method sim-

ulations, laboratory, and field data.

In Chapter 4, we present the integral equation surface scattering model that

includes fully the phase of Green’s function ignored in the simplified IEM devel-

opment. This inclusion improves bistatic scattering calculations and contains an

additional term which accounts for surface multiple scattering calculation. Hence,

we refer to this model as IEM-B. It is a more complex model than the one given in

Chapter 3. For simplicity we drop the multiple scattering term here in like polariza-

tion calculation. The restriction that the rms slope of the surface should be less than

0.3 is imposed also to avoid the computation of the multiple scattering term that

requires numerical integration in like polarized calculations. The format of presen-

tation is similar to Chapter 3, and it offers a comparison between the two models

by presenting comparisons with the same data set. Thus, for a given condition, the

reader can tell whether a more complex model is warranted. Generally, the more

complex model is not needed in backscattering but is needed in bistatic calcula-

tions.

In Chapter 5, we show backscattering from multiscale surfaces. The purpose

here is to provide a better understanding of the scattering properties in a natural

environment. By making comparisons with the moment method simulations in two

dimensions, both the IEM model and the simulation results indicate that there is a

strong frequency and view angle dependence in backscattering and that only certain

roughness scales are dominating scattering at a given observation angle and sens-

ing frequency. For this reason all model parameters derived from comparison with

experimental measurements are generally effective parameters indicating the

roughness scale or scales responsible for scattering. This effective scale size may

or may not agree with independent ground truth measurements, which must depend

on the method and system used to acquire them. Hence, a disagreement between

“ground truth” and the “model parameters” does not necessarily imply an error. It

only calls for a closer examination of the conditions under which the “ground

truth” was acquired and then decide whether the set is applicable at the sensing fre-

quency. Also discussed in this chapter are geometrically anisotropic surfaces which

possess different correlation lengths in orthogonal directions. Most wind-driven

surfaces and some cultivated fields are of this type.

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