Directed Infrared Countermeasures (DIRCM) Principles Training
Directed Infrared Countermeasures (DIRCM) Principles Training Course Description
In this 2-day Directed Infrared Countermeasures (DIRCM) Principles Training, the design of phase- and amplitude-sampling DRFM architectures are presented along with their problems and solutions. Narrowband and wideband designs are compared. Calculation of the spurious signals is presented and design strategies for advanced DRFM decoys for counter-targeting, counter-terminal applications are emphasized. Methods to synthesize multiple, structured false-targets against high range resolution profiling radars (ISAR, SAR) are presented. Derivation of false-target phase and gain coefficients are discussed including those for the required clutter models. Digital circuit design issues e.g., quantization errors, overflow, dynamic range are addressed. Methods used by adversaries to discriminate the DRFM false-targets from actual targets are offered leading to further DRFM design considerations. Lessons learned from recent EW flight tests are emphasized.
This course is intended primarily for radar, EW engineers and scientists interested in the design of digital RF memories and signal processing algorithms for electronic attack. Attendees should have a good knowledge of radar systems and signal processing. Many example problems are worked out to demonstrate the concepts and further the understanding of the material being presented.
Design of DRFM amplitude and phase sampling architectures for electronic warfare applications. Trade-offs and the significance of noise components is calculated. Operational considerations for narrowband and wideband DRFMs are discussed. Identification and prediction of spurious signals is presented and methods to reduce their effect is quantified. Algorithms for time and frequency modulation are presented. Use of DRFMs in a hard-kill situation is also presented. Design of structured false-target processors is emphasized. Lessons learned from recent EW flight tests are presented and counter-DRFM techniques are also discussed.
With onsite Training, courses can be scheduled on a date that is convenient for you, and because they can be scheduled at your location, you don’t incur travel costs and students won’t be away from home. Onsite classes can also be tailored to meet your needs. You might shorten a 5-day class into a 3-day class, or combine portions of several related courses into a single course, or have the instructor vary the emphasis of topics depending on your staff’s and site’s requirements.
Architectures, Design Trade-offs Phase- and amplitude sampling architectures; Single and double sideband systems; Mathematical models for both digital and analog components; Limitations including noise components; Prediction of dynamic performance and derivation of DRFM transfer functions;
Technical Considerations Instantaneous, operating bandwidth requirements; Significant problems in DRFM design and their solutions; Calculation of spurious signals; Efficiency comparison between phase and amplitude designs;
Algorithms for Electronic Attack Overall performance prediction of electronic attack; Algorithms for time-delay, advance modulation; for electronic attack; Algorithms for frequency modulation; Effects of coordinated time-frequency modulation;
Advanced Decoy Processor Designs DRFM role in hard-kill chain; Counter-surveillance, counter-targeting and counter-terminal applications; Effects on coherent range-Doppler processors; Digital image synthesizer design; False target and sea-clutter coefficients; Bit-level models and pipelined architectures;
Lessons from UAS EW Flight Tests Electromagnetic maneuver warfare (EMW) and counter-SAM suppression configurations; Eliminating geometrical EA limitations; Measures of effectiveness; Fielded DRFM configurations; DRFM swarm concepts and preliminary flight test results;
Differentiating DRFM false targets Statistical signal processing; Principal component analysis and the Fisher ratio; Polarization modulation algorithms; Multivariate analysis of variance; Multi-layer perceptrons.
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