Title: Effects of Environmental Variability on an XBand Phased Array Radar: AREPS Case Study
1Effects of Environmental Variability on an X-Band
Phased Array Radar AREPS Case Study
- LCDR Thomas Keefer
- OC3570
- 08SEP2006
2Motivation
- Steadily increasing focus on littoral
- MIW and NSW operations
- Range Prediction problematic
- environmental factors
- Confidence?
3Project Goals
- Track Pt Sur using X-Band Radar
- Gather data set
- Good simulation of a medium sized craft
- Run AREPS using 3 environmental profiles
- Standard, More Permissive, Less Permissive
- Compare and discuss observed and predicted
detection ranges - Gain insight into the confidence level of range
prediction in a littoral environment - Is the product high quality or dangerous??
4Procedure
- EXAMINE AREA OF OPERATIONS
- gather data from multiple sources
- Characterize the environment
- Profile the target and the sensor
- DEVELOP A PRODUCT
- Calculate Radar Horizon
- Run AREPS on 3 different cases
- Determine confidence in the product
- COMPARE PRODUCT TO OBSERVATIONS
- Discuss product limitation/inaccuracy
5Background/Literature Review
- The range of a radar system is limited by the
curvature of the earth (ignoring ducting),
antenna height, power and RCS of target - Ducting regularly occurs over the ocean
- In order to determine the presence of ducts, M
Profiles are particularly useful - Normally occur when Rh decreases rapidly with
height or Temp increases rapidly with height - Evaporation duct formation is favorable over the
ocean due to humidity change
6Data Set Description
- 12z and 24z Oakland, CA soundings
- Fort Ord Profiler for 12z and 24z
- Tair, RH, Wind Speed/Direction, SST and
Atmospheric Pressure measured onboard - Several SST measurements available
- Radar Output
7Characterizing the Environment
- Ideally, measured onboard
- Not available
- Composite of information a good substitute
- Bulk Parameters needed for evaporative duct
height prediction available from ship
8Gather Data
- Ideally, the profile used to predict radar ranges
would be available at multiple points between the
radar and target - Since this data was not available, a composite
profile was created - This profile was assumed to represent the entire
path from sensor to target
Z
Temp
Illustrative only NOT TO SCALE
9Gather Data
- This assumption, while not truly accurate, leads
to a good first guess. - Good starting point
- Allows sensitivity tests
- Sensitivity is a tool to evaluate product
confidence
Z
Temp
Illustrative only NOT TO SCALE
10Gather Data
- Using various sensors to put together a best
guess is always possible. - Composite could be an operational necessity.
Z
Temp
Illustrative only NOT TO SCALE
11Composite Profile
- Upper Air Profile Derived from Oakland Sounding
Z
- Inversion Bottom and Top parameters derived from
Ft Ord Profiler (Constant Lapse rate assumed
between) - Lower height is critical
- Lower Profile Input of ship bulk parameters and
match to bottom of inversion - Evap Duct done via param.
Temp
Illustrative only NOT TO SCALE
12- Does the data indicate a fairly homogenous
profile through the AOR? - How do the humidity, SST and Tair combine to give
an idea of duct presence - Modified Ref. Index
13(No Transcript)
14- Degrades confidence in model output and therefore
prediction - AREPS output can be discussed and adjusted to
suit risk tolerance of warfighter - SST and Tair Sensitivity tests are needed based
on data gathered in AOR
15- Examine Surface, elevated and evaporative ducting
- Best tool is the M Profile
- For this case, Sfc and elevated ducts are
unlikely Modified Refract. Index is always - Evap ducting possible
16Develop a Product
17Calculation of Radar Horizon
- R Radar Horizon
- Re Earths Radius
- H height of antenna
4/3 Earth Approximation is an empirical effort
to capture the refractive effects of a standard
atmosphere and neglects RCS and Power of Radar
18Calculation of Radar Horizon
Need to sum the radar horizon for the system
and the target
19Sensitivity Testing
- provide a prediction of radar ranges
- Assess accuracy and confidence
- Using 2 composite profiles with their lower
atmosphere derived from the upper and lower
bounds of the data recorded on the Pt Sur, AREPS
runs were conducted - A third AREPS run was done using standard
atmosphere for comparison
20Environment Comparisons
Env 1 evap ducting less likely Env 2 evap
ducting more likely
21AREPS is Sensitive to Radar/TGT
- Power output and Gain
- Target RCS critical
- Sea State/Intel
- Assumed good and held constant
22RV Pt Sur Radar Cross Sect.
- Power density return is a function of RCS
- No definitive value for Pt Sur
- Used 2000m2
- Varies greatly by beam vs bow vs stern aspect
- Sea State can silhouette or shade the target
23AREPS Environment 1
50 Probability of Detection likely to occur at
20.5km 100 Probability of Detection Likely to
occur at 15km
24AREPS Environment 2
50 Probability of Detection likely to occur at
24km 100 Probability of Detection Likely to
occur at 16km
25AREPS Std Atmosphere
50 Probability of Detection likely to occur at
20km 100 Probability of Detection Likely to
occur at 14km
26Results of Radar Tracking
- Acquired on an inbound run with coordination
- First run was outbound
- 100 Prob. Of Detection to 29.5km
- Second run was inbound
- 100 Prob of Detection at 27.5km
- Ducting has certainly occurred 100 POD range
doubled from predicted!!!
27Product Usefulness
- Given the extreme variability in the local
environment, confidence should have been
expressed as fairly low - Under prediction, even for the conservative case,
can be considered marginally successful provided
confidence is discussed - Model very sensitive to SST and RH
- RCS of target is highly variable and critical
- Sensors are rarely coincident with AOR
- Sensors may give erroneous readings
28Sensitivity Discussion Temp
- Evaporation duct height is highly sensitive to
SST - SST was measured 5 diff. ways onboard
- IR with the gun
- Bucket
- Sea chest injection
29Conclusions
- Radar range prediction a function of many input
variables - differing sensitivities
- Evaluating the confidence in the prediction is as
important, yet likely not as popular, as the
actual prediction itself - The confidence in your prediction should be based
on an assessment of the data quality and the
environmental variability over the AOR and should
include a discussion on the sensitivity of the
most influential variables
30Future Research
- Construct fall-off slide from existing data
- Not yet available
- Correlate Sea Swell to RCS
- Noticed cyclical fluctuation in power density
returned over short period
31Acknowledgments
- Peter Guest
- Ken Davidson
- Jeff Knorr
- Paul Buczynski
32Questions?