Analysis of sea state radar scatterometer data from NASA/MSC missions 20 and 3

Newton, R. W.

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Technical Report RSC-9
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RADAR SCATTEROMETER DATA ANALYSIS: SEA STATE
NASA/MSC MISSION 20 and MISSION 34
by
Richard W. Newton
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May, 1970
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supported by
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NASA Grant 44662
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TEXAS ABLM UNIVERSITY
J REMOTE SENSING CENTER
COLLEGE STATION, TEXAS
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Technical Report RSC-09
RADAR SCATTEROMETER DATA ANALYSIS: SEA STATE
NASA/MSC Mission 20 and Mission 34
by
Richard W. Newton
I. INTRODUCTION
Mission 20 and Mission 34, which are the sub-
ject of this report, were flown as part of a National
Aeronautics and Space Administration program involving
the NASA 926 Convair 240A aircraft. Included among the
sensors aboard the aircraft was R;, an Redop radar scat-
terometer. Using the data recorded with this 2.25 cm
wavelength radar s cat terome ter , an attempt was made to
discover any characteristics which would distinguish
the two sets of data from one another. Previous work
with radar scatterometer data has supported the appli-
cation of the sensor to determining general sea surface
characteristics for low sea states. The missions were
flown over different areas of the Atlantic Ocean in-
volving two different types of sea; therefore, by ex-
tracting characteristic information from each set of
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data, the surface conditions could be inferred.
The analysis discussed in this report was ba-
sically approached from an empirical sense and was only
concerned with the information contained in the seat•-
terometer data.	 Only part of the data recorded during
Mission 20 and Mission 34 was available for analysis.
It was acknowledged that errors could be inherent in
these data; however, the analyses techniques did ex-
hibit the fact that information relating to sea state
was contained in the data.	 Unfortunately, due to the
lack of sufficient ground truth, further conclusions
could not be drawn.
II.	 THE `CATTEROMETER
The Ryan Redop radar scatterometer transmits
w' a vertically polarized continuous wave signal with a
2.25 cm wavelength.
	
The radar return is recorded from
an illuminated region 3° wide and +60 * along the flight
line.	 Fore data is that return collected within the
+60° and aft data that collected in the -60° part of the
beam (Figure 1) .	 In order to obtain a scattering coeffi-
cient at each of several angles within the beam, the
3return is processed through doppler filters. The re-
turn is then time shifted in such a way that regardless
of the angle at which the data are recorded, the return
is from a particular "cell" on the surface of the ocean.
In this manner a plot of scattering coefficient vs inci-
dence angle can be plotted for each cell, therefore con-
stituting a "signature" for each cell. At a 1000 feet
altitude each cell is approximately 30 meters on a side.
(Rouses 1969)
III. COMMENTS ON THE DATA
Mission 20, which was in support of the
NAVOCEANO and the NASA-OSSA Experiments Program, was
flown March 7, 1966 over the area of the ocean which
encompasses the Argus Island tower and Plantagenet and
Challenger Banks in the Bermuda Islands. Data available
from this mission were taken during:
Flight	 Line	 Run	 Direction of Data
2	 1	 3	 Aft
2	 2	 2	 Fore
2	 4	 1	 Fore
2	 4	 2	 Fore
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Mission 34, which was also conducted in support of the
NASA-OSSA Earth Resources Survey Program, was flown
December 10, 1966 over an area of the North Atlantic
which is directly off the coast of the United States
at the boundary of Virginia and North Carolina. This
area is between longitudes 73°30 1 W and 74°W and lati-
tudes 36°N and 36°30 1 N. Data available from this mis-
sion were taken during:
Flight	 Line	 Run	 Direction of Data
2	 1	 3	 Fore & Aft
2	 1	 4	 Fore & Aft
The only ground truth available to accompany
the data was a general description of the sea at the
time of the flights. The wind direction was unknown.
During Mission 20 there were 5-foot swells, and at the
time Mission 34 was flown the wind was #2 on the Beaufort
scale which indicates very low sea state.
Small errors were introduced into the data due
to the method by which it was necessary to put it into
workable form. The data were obtained in the form of
scattering coefficient versus incidence angle plots for
each cell of radar return. It was then necessary to
tabulate these data by manually measuring the scattering
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coefficient for each angle of incidence from these
graphs. The data were then placed on IBM cards so
that it could be used in conjunction with computer pro-
grams. However, the data reduction method introduced
a possible .25db error in each scattering coefficient
reading. It was assumed that for any particular angle
of interest the errors in all the scattering coeffi-
cients of a run were random as to which direction this
.25db error was introduced (i.e. + .25db or -.25db) ,
therefore the average scattering coefficient of each
angle was not altered.
IV. ANALYSIS TECHNIQUES
The basic objective of the analysis discussed
in this report was to determine if there is a difference
in the radar return over low sea state, as in Mission 34,
from that of Mission 20, which was assumed to be recorded
over higher sea state. Two techniques were used in order
to extract information from the data. One technique was
concerned with the average sigma (scattering coefficient)
versus theta (incidence angle) plots for each run of data.
These average plots were generated for each run of data
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using the average sigma at each particular angle. Data
were recorded at nine angles both fore and aft during
each mission, however, only the readings of the first six
angles from the nadir were used for analysis. During
Mission 20, data were recorded at 4.5 0 , 9 0 , 13.5 0 ,
23 0 , 32.5 0 , and 37 0 . The last three angles of the nine
were disregarded because the backscatter for angles
greater that 40' or 45° was very small, i.e. near the
noise level of the equipment used in taking the data.
For this reason no information could be obtained from
the data collected at these angles. After calculating
the average scattering coefficient for each angle of
each run, the equation
a o = -!slog(cos ``0 ± Qs in ? 0)
was fitted to these points by using a least squares
curve fitting routine (Epees 1969). This equation
comes from Kirchhoff' s method of predicting an average
far-zone backscatter power for a plane wave incident
upon a random surface with Gaussian height distribution
(Hagfors 1964) . From this relationship, a plot of the
scattering coefficient as a function of incidence angle
was generated with the "roughness factor", Q, as an
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independent parameter. As the slope of the curve changes,
Q changes, thereby indicating some type of information
about the data. Plots such as this were made for each
run of both missions (Figure 2 & 3) . However, since
the above equation forces any curve generated using
that equation to go through the origin, it was found
that the equation ac is could not be fitted to the ex-
perimental points. It was found, however, that shift-
ing the origin from zero the first incident angle while
fitting the curve to the experimental points, and • hen
plotting this curve with respect to the original origin
would result in a curve which fits the points reason-
ably well. The curve was generated assuming the origin
at 5° for the data from Mission 20 and at 2.5° for Mis-
sion 34. The curves were then plotted using the orig-
inal origin. Shifting the origin in this manner de-
stroys the theoretical aspects of the equation, but the
curves, and thus Q values, generated from the equation
are still of possible use in an empirical sense. It
is useful if the Q values generated from data taken over
different sea states vary with the sea state.
The Q values for different runs are tabulated
in Table I. From this table it is evident that the
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values of Q for Mission 20 are much higher than those
of Mission 34. The lowest Q of Mission 20 is 457.70
(Line 4 Run I Fore data) and the highest for Mission 34
is 237.94 (Line 1 Run 3 Aft data) . There is a definite
separation between missions, however, these results are
not in agreement with theoretical expectations.
It was reported that Mission 20 was flown
over 5-foot swells while Mission 34 was flown during
low winds, Beaufort #2, therefore very low sea state.
The sea state during Mission 34 was supposedly the lower
of the two, therefore, the scattering coefficient at
higher incidence angles should ,fall off rapidly while
for Mir--ion 20 it should not fall off so rapidly. Q is
an indication of the slope of the average sigma versus
theta curve, thus, Q should be higher for the runs of
Mission 34. This descrepancy could be due to the fact
that while Mission 20 had 5-foot swells it is possible
that the sea state on these swells were at a minimum,
less than the sea state encountered during Mission 34.
This is a possibility since swells are a result of past
and/or remote weather conditions while "sea" rides on
the swell and is a result of present wind fields in the
general area of interest. Assuming this possibility,
lio
9the values of Q could indicate that the major part of
the radar backsratter resulted from the smaller sea
state rather than the larger more uniform swells. How-
ever, due to the possibiltity of erroneous data or mis-
reported ground truth, no conclusions can be drawn.
After inspecting the various values of Q for
each mission CTable I) , it appears that they are depen-
dent upon the direction of the flight relative to the
wind direction. The direction of the wind is unknown,
therefore no statements can be made from the data in
this respect.
Another analysis technique, the slope-inter-
cept method (Lundien 1966) , was concerned with the sigma
versus theta plots for each cell of each run in order to
obtain a cluster plot which would hopefully define the
sea state. This technique involved fitting a straight
line to the first four points of the sigma versus theta
plots of each cell of radar return. In this manner two
types of information can be extracted from each sigma
plot and the information plotted against each other.
The information is the slope and 0° intercept of the
straight lines (Figure 4) (Eppes & McFarland 1969) .
With this data for each cell of a run, the slopes and
0 0 intercepts of the complete run can be plotted with
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the slope as the ordinate and Jw 0° intercept as the
abscissa, forming a cluster (Figures 5 & 6) . Due to
the large volume of data from Mission 20, only every
tenth cell was considered using this technique, thereby
giving a representative sample without an excess of com-
puter storage. An average slope and 0 0 intercept was
also calculated for each run of data. These averages
wex•e plotted to better indicate the separation between
the cluster plots of various runs (Figure 7) .
After examining the clusters from both missions
it is evident that there is a definite separation. The
clusters of Mission 34 are higher (smaller slope) than
Mission 20, however, they are generally vertically al-
ligned (0' intercepts are approximately the same) . This
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indicates that the 0° intercept contains little infor-
mation. about the sea state, since Mission 20 and Mission 34
were flown over different sea states. Clusters from both
missions indicate that the slope and 0° intercept have
a definite dependence upon each other due to the shape
of the clusters. This is obvious from the method by
which they are calculated. For this reason the slope
and 0 0 intercept are not independent enough to contain
two separate types of information.
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After, examining the cluster plots for each
run of both missions it becomes apparent than the plots
of Mission 20 are not as tightly grouped as those of
Mission 34. This seems to indicate that the data of
Mission 20 is possibly less consistant, and thus less
accurate for the purpose of this discussion, than that
of Mission 34. To better determine the accuracy of
the data the mean variance and mean deviation for each
angle of every run was calculated using
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DATAP
	
_ i	 (Diff (I) 2)Mean Variance -
DATAP
DATAP
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Mean Deviation = 1	 (IDiff (I) I)
DATAP
where: Diff (I) - difference of Sigma (I) from
the mean Sigma for a particular
angle
DATAP	 number of sigmas for the angle
under consideration
The results of these calculations are tabulated in Table I.
These results show that the most consistant data set should
be from Mission 34 Flight 2 Line 1 Run 3 Fore data, since
this run has the Lowest values of variance and deviation.
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This coincides with the cluster plot. This particular
run gave the most compact cluster. On the other hand,
Mission, 34 Flight 2 Line 1 Run 3 Aft data should be
the lest consistant set of data from Mission 34 because
it has the highest variance and deviation. The cluster
supports this, since it is the least compact of Mission
34. Overall it appears that Mission 34 contains the
most consistant data of the two missions, since all of
its clusters are more compact than those of Mission 20.
V. CONCLUSIONS
Due to the fact that very little ground truth
accompanied Mission 20 or Mission 34, the ability to
draw conclusions from the data is greatly stifled. It
would appear from the cluster plots that the higher the
cluster, and thus the smaller the slope, the lower the
sea state. However, for this to agree with expected
results the same assumption as in the discussion of sec-
tion IV, would h":ve to be made. From these analyses
it is evident that the data collected over different
sea states does have different characteristics and thus
the possibility of discriminating sea states.
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REFERENCES
Eppes , T. A., "Discussion of the Least Squares Technique
and the Developement of a. Curve Fitting Subroutine,"
Technical Report RSC-04, Remote Sensing Center, Texas
A & M University, September 1969.
Eppes, T. A. and McFarland, J. C. III, "Documentation of
Two Data Analysis Subroutines," Technical Memoran-
dum RSC-03, Remote Sensing Center, Texas A & M Uni-
versity, December 1969.
Hagfors , T., "Backscattering From An Undulating Surface
With Applications To Radar Return From the Moon,"
J. Geophysical Resoarch, vol 69, no 18, pp 3779-3784,1964.
Lundien, J. R., "Terrain Analysis by Electromagnetic
Means," United States Army Engineer Waterways Ex-
periment Station Technical Report No. 3-693, Sep-
tember 1966.
Rouse, J. W... "Artic Ice Type Identification by Radar,"
Proceedings of IEEE, vol 57, pp 605-611, April 1969.
4
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TABLE 1
MIS. FLT. LINE RUN SITE DIREC
MEAN
VAR.
MEAN
DEV. Q
AVG.
SLOPE
AVG.	 0 0
INTERCEPT
MAG.
HEADING
20 2 4 1 86 Fore 2.27 1.15 457.7 -1.46 13.99 3300
3.21 1.41.
5.21 1.77
3.74 1.48
1.08 0.81
1.64 1.01
20 2 2 2 86 Fore 2.78 1.34 733.9 -1.64 13.99 0550
4.01 1.57
5.10 1.78
3.71 1.43
1.73 0.96
2.97 1.29
20 2 1 3 86 Aft 2. 29 1.23 607.1 -1.58 14.12 1940
4.26 1.64
7.40 2.17
4.91 1.76
3.30 1.45
3.56 1.15
20 2 4 2 86 Fore 3.23 1.42 916.3 -1.65 13.41 1520
5.65 1.88
13.0 2.82
18.2 2.77
12.7 2. 82
10.4 2.59
34 2 1 3 138 Fore 0.82 0.73 144.4 -0.88 10.73 0650
0.45 0.48
0. 87 0.55
0.39 :0.51
0.58 0.62
0.40 0.51
34 2 1 3 138 Aft 20.3 3.72 237.9 -1.OR 14.16 060
23.0 3.51
3.53 1.39
2. 27 1.36
1.57 1.07
0.55 0.53
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MIS. FLT. LINE RUN SITE DIREC
MEAN
VAR.
MEAN
DEV. Q
AVG.
SLOPE
AVG.	 0 0
INTERCEPT
MAG.
HEADING
34 2 1 4 138 Fore 0.33 0.45 174.8 -1.03 10.62 0700
0.43 0.52
0.43 0.48
1.40 0.81
0.38 0.51
1.3.5 1.69
34 2 1 4 138 Aft 8.23 1.62 168.8 -.1.02 12.67 0700
3.25 0.72
1.24 0.76
0.73 0.69
2. 73 1.06
0.22 0.34
.
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F-
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LLJ
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r.	 NORMALIZED SCATTERING COEFFICIENT VERSUS INCIDENCE ANGLE
THETA (DEGREES)
A	 1 5.0 0	 2 0.00 	 2 5.0 0	 3 0.0 0
CD
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MISSION 34 FLIGHT 2 LINE 1 RUN 4 AFT DATA
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NORMALIZED SCATTERING COEFFICIENT VERSUS INCIDENCE ANGLE
THETA (DEGREES)
MISSION 20 FLIGHT 2 LINE 2 RUN 2 FORE DATA
FIGURE 3
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Q	 I
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FIGURE 4 METHOD OF OBTAINING POINTS FOR CLUSTER PLOTS
f
SLOPE INTERCEPT CATEGORIZATION
- 1 0.0 0
	
: 540 0	 0.0 0
	 5.0 0	 1 0 1 0 0	 1 5.0 0	 2 0.0 0
0 DEGREE INTERCEPT (DB)
MISSION 20 FLIGHT 2 LINE 2 RUN 2 FORE DATA
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r
SLOPE INTERCEPT CATEGORIZATION
- 1 0.0 0	 - 5.0 0	 0.0 0	 510 0	 1 0.0 0	 1 5.0 0	 2 0.0 0
0 DEGREE INTERCEPT (DB)
MISSION 34 FLIGHT 2 LINE 1 RUN 3 FORE DATA
AVERAGE SLOPE INTERCEPT POINTS FOR EACH RUN
0.0 0	 5.0 0 010 0 5.0 0 1 0.0 0 1 5.0 0	 2 0.0 0
0 DEGREE INTERCEPT (DB)
SYMBOL MISSION FLIGHT LINE RUN	 DATA DIRECTION
0 34 2 1 3 Fore
34 2 1 3 Aft
34 2 1 4 Fore
34 2 1 4 Aft
0 20 2 1 3 Aft
x 20 2 4 2 Fore
+ 20 2 4 1 Fore
20 2 2 2 Fore
FIGURE 7
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Radar scatterometer data analysis - Sea state. NASA/MSC Mission 20 and Mission 34

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