Файл: Ersoy O.K. Diffraction, Fourier optics, and imaging (Wiley, 2006)(ISBN 0471238163)(427s) PEo .pdf

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HIGHER ORDER IMPROVEMENTS AND ANALYSIS

95

With the new approximations, Eq. (7.2-11) is replaced by

 

Uðx0; y0; zÞ ¼ e jkr0

ðð u0ðx; yÞe j2pðfxxþfyyÞdxdy

ð7:3-11Þ

where the spatial frequencies are still given by Eqs. (7.2-12) and (7.2-13) due to Eqs. (7.3-6) and (7.3-7). With FFA, u0ðx; yÞ equals uðx; yÞ.

We note that Eq. (7.3-11) looks like Eq. (7.2-11) for the Fresnel approximation, but the phase factor outside the integral and the output sampling points are different. Equation (31) is straightforward to compute with the FFT, and the results are valid at the sampling points defined by Eqs. (7.3-8) and (7.3-9). The spatial frequencies can also be written as

fx ¼

x0

ð7:3-12Þ

lr0

fy ¼

y0

ð7:3-13Þ

lr0

It is observed that fx and fy are still given by Eqs. (7.2-12) and (7.2-13) with respect to the regular sampling points ðxs; ysÞ or by Eqs. (7.3-12) and (7.3-13) with respect to the actual sampling points ðx0; y0Þ.

7.4HIGHER ORDER IMPROVEMENTS AND ANALYSIS

We write r in Eq. (7.3-1) in a Taylor series as

 

 

 

r

¼

r

 

1

 

h

 

h2

 

h3

 

1

 

n 1

1

3 5

ð2n 1Þ

h2m 1

 

 

þ

2

8 þ

16 þð

Þ

 

 

 

 

 

 

0

 

 

 

 

2 4 6 2n

ð7:4-1Þ

where it is desirable to attain the terms shown in order to obtain high accuracy. In order to be able to use the Fourier transform, we only keep the terms in the Taylor series that do not have factors ðx0xÞn other than x0x.

We also define

a

n ¼ ð

1

Þ

n 1

1 3 5 ð2n 1Þ

 

1

 

 

 

 

2

 

4

 

6

 

2n z2n

 

 

 

 

 

 

 

 

 

 

 

Then, r is approximated by

r r0 xx0 þ yy0 þ pðwÞ r0

ð7:4-2Þ

ð7:4-3Þ


96 WIDE-ANGLE NEAR AND FAR FIELD APPROXIMATIONS

where

X

an

 

1

 

pðwÞ ¼ pðx; yÞ ¼

z2n 1

wn

ð7:4-4Þ

n¼1

 

 

 

Equations (7.3-8) and (7.3-9) remain the same because the term involving xx0 and yy0 is not modified. When z w as in the Fraunhofer approximation, the term pðwÞ in Eq. (7.4-3) is skipped. With the new approximations, Eq. (7.3-11) is replaced by

Uðx0; y0; zÞ ¼ e jkr0

ðð u00ðx; yÞe j2pðfxxþfyyÞdxdy

ð7:4-5Þ

where

 

 

u00ðx; yÞ ¼ uðx; yÞe jkpðwÞ

ð7:4-6Þ

For a given z, the maximum error in the Fresnel approximation is proportional to ðx20 þ y20Þ2 whereas, in the NFFA, it is approximately given by

E

¼

vðx2 þ y2Þ

 

ðx0x þ y0yÞ2

7:4-7

Þ

 

4z3

2z3

ð

This error corresponds to the neglected terms in the second component u22 of the Taylor series expansion.

We note that changes are made only in the object coordinates with Eqs. (7.3-8) and (7.3-9). Otherwise, the integral in Eq. (7.4-5) is the same as the integral in Eq. (7.2-9) or Eq. (7.2-14). The output points ðx0; y0Þ are determined by Eqs. (7.3-8) and (7.3-9) in terms of ðxs; ysÞ given by Eqs. (7.2-15) and (7.2-16).

An interesting observation is that the Fresnel approximation examples cited in the literature are approximately correct in the near field at the points ðx0; y0Þ given by Eqs. (7.3-8) and (7.3-9), and not at the points ðxs; ysÞ. As such, these results are really the NFFA results.

In order to use the FFT, it is necessary to satisfy Eqs. (7.2-19) and (7.2-20). mx 0x and my 0y are the output sampling positions that are modified to do so. It is possible to consider other sampling strategies in which mx 0x and my 0y are replaced by some other output sampling positions, say, xs and ys. The results obtained above are valid in all such cases.

7.5INVERSE DIFFRACTION AND ITERATIVE OPTIMIZATION

Inverse diffraction involves recovery of uðx; yÞ from Uðx0; y0; zÞ as discussed in Chapter 6. In the case of the Fresnel approximation, Eq. (7.2-9) is a Fourier transform, and its inversion yields

ðð

u0ðx; yÞ ¼ U^ðx0; y0; zÞe j2pðfxxþfyyÞdfxdfy

ð7:5-1Þ


NUMERICAL EXAMPLES

97

where u0ðx; yÞ is given by Eq. (7.2-10), the spatial frequencies fx, fy Eqs. (7.2-12), (7.2-13), and

^ð y zÞ ¼ Uðx y zÞe jk2vz

U x0; 0; 0; 0;

are given by

ð7:5-2Þ

Similarly, the integrals in Eqs. (7.3-11) and (7.4-5) are Fourier transforms. Inverse Fourier transformation of Eq. (7.3-11) yields

ðð

 

u0ðx; yÞ ¼ U0ðx0; y0; zÞe j2pðfxxþfyyÞdxdy

ð7:5-3Þ

where

 

U0ðx0; y0; zÞ ¼ Uðx0; y0; zÞe jkr0

ð7:5-4Þ

The inverse Fourier transformation of Eq. (7.4-5) similarly yields

 

ðð

 

u00ðx; yÞ ¼ U0ðx0; y0; zÞe j2pðfxxþfyyÞdxdy

ð7:5-5Þ

Iterative optimization techniques are often used to design optical devices such as DOE’s [Lee, 1970, 1975, 1979; Zhuang and Ersoy, 1995]. These techniques are discussed in Chapters 15 and 16. For this purpose, many iterations are carried out between the input and output planes. Equations (7.3-11) and (7.5-3) as well as Eqs. (7.4-5) and (7.5-5) are Fourier transform pairs. Hence, iterative optimization can be carried out exactly as before with these equations.

7.6NUMERICAL EXAMPLES

Below the 2-D case is considered first with y variable neglected without loss of generality. In the initial computer simulations, the relevant parameters are chosen as follows:

l ¼ 0:6328 m; x ¼ 1 mm; N ¼ 256; x=l ¼ 7

The minimum z distance for the approximations to be valid as a function of offset x0 at the output plane can be computed by specifying kðr rðapproximateÞÞ to be less than 1 radian. The result with input offset x equal to 1 mm is shown in Figure 7.1. It is observed that for very small ðx0 xÞ, the two approximations behave almost the same, but this quickly changes as ðx0 xÞ increases.

Figure 7.2 shows the ratio z=x0 as a function of the output plane offset x0. This ratio approaches 2 with the new approximation whereas it approaches 36 with the Fresnel approximation as the offset x0 increases. We note that with the FFT, the maximum output offset equals zx=lÞ, x being the input plane sampling



98

WIDE-ANGLE NEAR AND FAR FIELD APPROXIMATIONS

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Figure 7.1. Minimum z distance for the approximations to be valid as a function of x0 at the output plane with x equal to 1 mm.

interval. Hence, the new approximation is sufficiently accurate at all the output sampling points for x=l greater than 2. Figure 7.3 shows the growth of the difference between x0 and xs calculated with Eq. (28) as x0 increases when z ¼ 10 cm.

Figure 7.2.

The ratio z=x0

as a function of x0.

NUMERICAL EXAMPLES

99

 

 

 

 

 

 

Figure 7.3. Change of x0 in mm as a function of x0 at the output plane when z ¼ 20 cm and x ¼ 1 mm.

Equations (7.3-8) and (7.3-9) show the relationship with the regularly sampled output points as in the Fresnel or Fraunhofer approximations, and the semiirregularly sampled output points as in the NFFA. Examples of these relationships are given in Tables 7.1 thru 7.3. The (x,y) sampling coordinate values in these tables are shown as complex numbers x þ iy. Table 7.1 shows the example of regularly sampled values. Table 7.2 shows the corresponding example of semi-irregularly sampled values. Table 7.3 is the difference between Tables 7.1 and 7.2.

In the next set of experiments in 2-D, a comparison of the exact, Fresnel and NFFA approximation integrals was carried out for diffraction of a converging spherical wave from a diffracting aperture. The parameters of the experiments are as follows:

Diffracting aperture size ðDI Þ ¼ 30 m; z ðfocusing distanceÞ ¼ 5 mm;

N ¼ 512; l ¼ 0:6328 m

The numerical integration was carried out with the adaptive Simpson quadrature algorithm [Garner]. The output aperture sampling was chosen according to the FFT conditions. Then, the full output aperture size is given by

DO ¼

Nlz

ð7:6-1Þ

DI

However, only the central portion of the output aperture corresponding to 64 sampling points and an extent of 6.7 mm was actually computed. As z ¼ 5 mm, this represents a very wide-angle output field.