Program Element: 0603217C Project Number: 1208

PE Title: Ballistic Missile Defense (U) Budget Activity: 03

Adv Technology Dev (U)

February 1994

A. (U) RESOURCES: ($ In Thousands)

Project Title: Discriminating Interceptor

FY1993 FY1994 FY1995 FY1996 FY1997 FY1998 FY1999 Total

Program Name: Actual Estimate Estimate Estimate Estimate Estimate Estimate Program

0603217C RDT&E 174 0 0 0 0 0 0 Completed

B. (U) BRIEF DESCRIPTION OF MISSION REQUIREMENT AND SYSTEM CAPABILITIES:

(U) To achieve a high probability of kill of midcourse targets, interceptors must be capable of discriminating between real targets, in the presence of decoys and debris during the exo-atmospheric portion of flight. The interceptor must be lightweight and must be able to kinematically engage a full range of threats. To perform discrimination at sufficient range to implement guidance commands requires fusion of multi-spectral passive and ladar data to capitalize on available discriminants. Processors able to support the large computational demand, and high thrust divert are needed while staying within cost and weight constraints.

(U) The objective of the ADI program is to develop and demonstrate interceptor components that, when integrated, will provide onboard discrimination capability. The original intent of this program was to design and demonstrate critical components for a discriminating interceptor including active/passive seekers (ladar/LWIR, rapid beam steerers, signal and data processors, discrimination algorithms, data fusion algorithms, and high acceleration divert propulsion. Additionally, an advanced vehicle concept (AVC) design, traceable to GBI requirements, was to be completed and maintained as the technology development progressed. Components were to be ground and flight tested as they became available. The program was planned to culminate with dedicated flight testing of a discriminating interceptor technology test vehicle (TTV). Due to severe budget cuts, the ADI program was tailored to focus on development and demonstration of the ladar only. The ADI funds were provided through PMA A2202. The PMA 1208 effort focused on development of discrimination algorithms and neural networks to support active/passive data fusion and target selection.

(U) This project is assigned to the Budget Activity and Program Element codes as identified in this descriptive summary in accordance with existing Department of Defense policy. Further justification of the Budget Activity code assigned to each Program Element is contained within the Brief Description of Element section of each Program Element Summary.

C. (U) PROGRAM ACCOMPLISHMENT AND PLANS:

(U) FY 1993 Accomplishments:

o ($24K) Identified discrimination algorithms required.

o ($75K) Began formulation of discrimination algorithms.

o ($75K) Began implementation of discrimination algorithms in nueral networks.

(U) FY 1994 Plans: None

(U) FY 1995 Plans: None

(U) Program Plan to Completion: This is a zero funded program.

D. (U) WORK PERFORMED BY:

o AEDAR - Rockville, MD

E. (U) COMPARISON WITH FY 1994 DESCRIPTION SUMMARY:

1. TECHNICAL CHANGES:

2. SCHEDULE CHANGES:

3. COST CHANGES: Program terminated due to zero budget.

F. (U) PROGRAM DOCUMENTATION:

o Program Management Agreement (PMA 1208), Jan 07, 1992; October 1993

G. (U) RELATED ACTIVITIES:

(U) The ADI effort PE No. 0603215C (Limited Defense System) Project 1208 will benefit from developments in Interceptor Component Technology (PE No. 0603217C, Project 1201). The discriminating interceptor will incorporate any of the following technologies that prove to be useful to an NMD Block Upgrade: focal plane array and readout electronics, ladars, beam steering, optics, signal processors, sensor/data fusion algorithms, discriminating algorithms, inertial measurement units, and propulsion.

H. (U) OTHER APPROPRIATION FUNDS: None

I. (U) INTERNATIONAL COOPERATIVE AGREEMENTS: None

J. (U) MILESTONE SCHEDULE:

o Identified discrimination algorithms required 2Q/FY93

o Began formulation of data fusion and discrimination algorithms 3Q/FY93

o Began implementation of algorithms in neural nets 3Q/FY93