LCDR Thomas Keefer OC SEP2006

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Presentation transcript:

LCDR Thomas Keefer OC3570 08SEP2006 Effects of Environmental Variability on an X-Band Phased Array Radar: AREPS Case Study LCDR Thomas Keefer OC3570 08SEP2006

Steadily increasing focus on littoral MIW and NSW operations Motivation Steadily increasing focus on littoral MIW and NSW operations Range Prediction problematic environmental factors Confidence?

Project 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??

Procedure EXAMINE AREA OF OPERATIONS DEVELOP A PRODUCT 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

Background/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

Data 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

Gather 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

Gather 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

Gather 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

Composite 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

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

Not Homogenous!!

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

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

Develop a Product

Calculation 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

Calculation of Radar Horizon * Need to sum the radar horizon for the system and the target

Environment Comparisons RH% 97 95 SST (C) 16.0 16.5 Tair 14 13.5 Wind spd 4 Env 1 = evap ducting less likely; Env 2 = evap ducting more likely

AREPS is Sensitive to Radar/TGT Power output and Gain Target RCS critical Sea State/Intel Assumed good and held constant

RV Pt Sur: Radar Cross Sect. Power density return is a function of RCS No definitive value for Pt Sur Used 2000m^2 Varies greatly by beam vs bow vs stern aspect Sea State can ‘silhouette or ‘shade’ the target

AREPS: Environment 1 50% Probability of Detection likely to occur at 20.5km 100% Probability of Detection Likely to occur at 15km

AREPS: Environment 2 50% Probability of Detection likely to occur at 24km 100% Probability of Detection Likely to occur at 16km

AREPS: Std Atmosphere 50% Probability of Detection likely to occur at 20km 100% Probability of Detection Likely to occur at 14km

Results 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!!!

Product 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…

Sensitivity 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

Conclusions 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

Future 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

Peter Guest Ken Davidson Jeff Knorr Paul Buczynski Acknowledgments Peter Guest Ken Davidson Jeff Knorr Paul Buczynski

Questions?