PDSP16510

17

trated in Table 7. The results are obtained from the reference

quoted, which should be consulted for a full mathematical

treatment. The significance of each parameter is outlined

below :

Highest Side Lobe Level

The inherent rectangular window has sidelobes which

are only 13dB down from the mainlobe. These severely limit

the dynamic range. The object of the window is to improve this

situation with better side load attenuation.

Mid-Point Loss

In line with the filter concept it is possible to conceive of

an additional processing loss for a tone of frequency mid-way

between two bins. This is defined as the ratio of the coherent

gains of two tones, one at the mid-point and one at the sample

point. It is expressed in dB in Table 8.

Overall loss

An overall figure for the reduction in signal to noise ratio

can be obtained by adding the mid-point loss to the reciprocal

of the equivalent noise power bandwidth in dB. It is a measure

of the ability of the window to detect single tones in broadband

noise. The variance between windows is less than 1dB.

6.0dB Bandwidth

This figure, expressed in bin widths, represents the ability

of the window to resolve two tones and should be as close to

unity as possible. As the highest sidelobe level is reduced, this

parameter tends to get worse, and a compromise must be

used when choosing a window.

Overlap Correlation

In many practical systems the squared magnitudes of

successive transforms are averaged to reduce the variance of

the measurements. If, however, a windowed FFT is applied to

non overlapping partitions of the sequence, data near the

boundaries will be ignored since the window exhibits small

values at those points. To avoid this loss partitions are usually

overlapped by 50% or 75%, which might, at first sight, remove

the need to average successive transforms. If non-windowed

Window

Highest

Mid-Point

Overall

6dB

Overlap Correlation

Operator

Side Lobe

Loss dB

Loss dB

Bandwidth

75%

50%

Rectangular

-13

3.92

3.92

1.21

75

50

Hamming

-43

1.78

3.1

1.81

70.7

23.5

Dolph-Chebyshev

-70

1.25

3.35

2.17

60.2

11.9

[C = 3.5]

Kaiser-Bessel

-69

1.02

3.55

2.39

53.9

7.4

[C = 3]

Blackman

-58

1.1

3.47

2.35

56.7

9

Blackman-Harris

-67

1.13

3.45

1.81

57.2

9.6

[3 term]

Table 7. Window Performance ( from The use of Windows for Harmonic Analysis. F J Harris. Proc IEEE Vol 66. Jan 1978 )

D

R

PDSP16510

AUX

POWER

ON RESET

PARAMETERS

PDSP16116

COMPLEX

MULTIPLIER

SYSTEM

CLOCK

REAL

DATA

IMAG'

DATA

WINDOW

PROM

XR

XI

YI

YR

ZERO

COUNTER

CLK

FIRST

SAMPLE

SAMPLE

CLOCK

CLR

Fig. 11. External Window Generator

window it is six bins.

The latter two windows are actually supported by the

PDSP16510. These are constructed on the fly as needed, and

take the general form:

A - Bcosx + Ccos2x where x = (2

πn)/N, n = 0 to N-1

For Hamming, A = 0.54, B = 0.46, C = 0

For Blackman-Harris, A = 0.42323, B = 0.49755,C=0.07922

These windows can be applied to any of the transform

size options, except the 16 x 16 complex variant. When the

latter is specified the rectangular window option MUST be

selected, or the device will be configured in an internal test

mode.

If other operators are required these must be applied

externally. This can be conveniently achieved with either a

PDSP16112 or a PDSP16116, both of which are complex

multipliers but with different accuracies. Fig. 11 shows how

either one can be configured to perform two separate multipli-

cations with one input common to both. This arrangement is

necessary to perform the window function on complex inputs.

Important features of the windows generated by

PDSP16510, and other commonly used windows, are illus-