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MATHWORKS SOLUTIONS FOR

AERO DEFENSE INDUSTRY

MATHWORKS SOLUTIONS FOR

AERO DEFENSE INDUSTRY

MATLAB® and Simulink® products for Model-Based § Promote reuse by interfacing with existing tools,
Design and technical computing are the industry- simulations, and legacy software
standard tools for designing, implementing, and testing
air, space, naval, and land systems. Aerospace and § Leverage new technologies by moving directly from
defense companies worldwide rely on these products in IRAD to production
major programs, such as the F-35 Joint Strike Fighter and
Mars Exploration Rover, as well as for unmanned aerial § Research emerging technologies such as cyber-
vehicles and advanced wireless systems, such as physical systems
software defined radio (SDR).

Model-Based Design with MATLAB and Simulink is a
modular development approach that enables
engineering teams to move from internal research and
development (IRAD) to design and implementation in a
single environment. Companies are using this approach
to:

§Mitigate program risk by sharing system
specifications, analysis, and test data

§ Reduce costly rework through early simulation of
design

Data Analysis for Aerospace Defense Industry

Overview § All test data must be processed and analyzed before
the aircraft is cleared for the next flight
Aerospace defense systems are complex engineering
equipment developed using multimillion dollars of § Lack of single unified platform across teams for
investments. These systems have to be thoroughly tested performing data analysis
and analyzed before they are deemed airworthy. Some
common challenges faced during analysis of such data § Duplicated efforts, low levels of reuse, and slow project
are given below: ramp-up times makes it impossible to combine results
into a single, coherent evaluation
§ Before the system goes live it needs to undergo
extensive performance and flying qualities flight tests.

Our Solution MATLAB® helps you develop data-driven insights that
Using our solutions, what if you can? lead to better designs and decisions. You can use
§ Complete the data analysis 16 times faster MATLAB to address the major challenges of performing
§ Reduce program setup time from weeks to days data analytics:
§ Save millions of dollars in projected cost savings
§ Provide immediate, shared access to test results § Accessing and pre-processing data from a variety of
§ Use parallel computing tools to execute flight data sources

processing algorithms on a computer cluster § Exploring patterns in data to gain intuition
§ Conduct Intelligent Integrated Vehicle Health
§ Developing advanced analytics with machine learning
Monitoring with the aid of data analysis
§ Integrating analytics with enterprise systems

“MATLAB provides the Navy and Air Force with an
affordable, reliable, sustainable, and
technologically superior enterprise-wide approach
to test data analysis,” says Dave Kidman, technical
expert, Propulsion Integration Branch of the U.S. Air
Force.

Communication Systems

MATLAB® and Simulink® products provide a complete antennas. Perform simulation to optimize parameters,
environment for design, simulation, and verification of examine what-if scenarios, and iterate quickly on
satellite and terrestrial wireless systems. You can: designs. Test your designs and verify system-level
performance using a suite of visualization and
§ Simulate wireless communication systems from measurements tools, including configurable spectrum
antenna to bits. analyzers and scopes.

§ Design smart RF systems. With Communications System Toolbox™ and related
wireless design products, you can:
§ Test wireless designs with SDR hardware and RF
instruments. §Analyze signals and make performance
measurements such as EVM, ACLR, BLER.
§ Analyze, simulate, and test LTE/LTE-A standard-
compliant systems. § Incorporate algorithms such as MIMO, OFDM, and
beam-forming into your models.
Antenna-to-Bits Simulation
§ Generate waveforms and create verification reference
Model the physical layer of your wireless signals for downstream implementation
communications systems in MATLAB and Simulink before
building them. Compose test benches that provide
complete executable specifications of your designs,
extending from information bits to signals radiating on

“We needed to know if our communications system would
support a 50% increase in data rate. By modeling and
simulating the antenna, transmitter, and receiver designs in
Simulink, we got a direct answer: Yes. We had confidence in
this answer because the simulations showed us how the
system performed.” Skip Cubbedge, DigitalGlobe

Smart RF Design

With Simulink and SimRF™, you can model and simulate § Capabilities for LTE, WLAN, and 5G wireless
the RF transceiver together with baseband algorithms development include:
and analog/mixed-signal components.
§ LTE, LTE-Advanced, and 802.11 a/b/g/n/ac
§ Model smart RF architectures. simulation and waveform generation

§ Develop calibration and control algorithms such as § Carrier aggregation, CoMP, beamforming and
DPD or AGC to mitigate impairments and interferers. antenna array modeling for MIMO systems

§ Add measured RF component characteristics. § Signal and control parameter recovery

§ Use circuit envelope techniques to simulate RF § Live waveform transmission and reception with SDR
transceivers an order of magnitude faster than circuit hardware and RF instruments.
simulations.
Prototyping and Implementation
Radio Connectivity to SDR and RF Instruments
Using MATLAB and Simulink for prototyping and
With Communications System Toolbox, along with implementation, you can:
software-defined radio hardware support packages or
Instrument Control Toolbox™, you can: § Convert floating point models to bit-true fixed-point
designs
§ Transmit and receive generated waveform over the air.
§ Automatically generate target-independent or target-
§ Configure hardware parameters and program the optimized HDL and C code
radio software.
§ Prototype algorithm designs on commercially
§ Model channels and RF impairments to build available or custom SDR, SoC, and FPGA
repeatable test scenarios and validate real-world development boards
operation.
§ Verify algorithm implementation using FPGA-in-the-
§ Analyze acquired I/Q baseband signal with loop verification or cosimulation with Cadence,
configurable measurement tools in MATLAB and Mentor and Synopsys HDL simulators
Simulink.
§ Automatically generate SystemVerilog models for
§ Verify and validate your designs based on live radio ASIC verification
signals.
“Completing this project on time without Model-
LTE, WLAN and 5G Based Design would have been very difficult. The
ability to generate code with HDL Coder and to
§ MATLAB provides a unified environment that enables separate signal processing algorithm design from
you to develop, test, and analyze LTE, WLAN, and 5G detailed hardware implementation helped us reduce
systems and develop next-generation algorithms. effort on the project by two engineer-years.” Kevin
Williams, Reutech Radar Systems
§ LTE System Toolbox™ and WLAN System Toolbox™
accelerate standard-compliant physical layer (PHY)
development, support golden reference verification
and conformance testing, and enable test waveform
generation. Because you're working in the MATLAB
environment, you can easily generate custom designs,
waveforms, and test benches.

Radar Systems

Radar system design, simulation, and analysis is § Accelerate development with libraries of algorithms
complex because the design space spans the digital, such as match filtering, adaptive beamforming, target
analog, and RF domains. These domains extend across detection, space-time adaptive processing,
the complete signal chain, from the antenna array, to environmental and clutter modeling, and direction of
radar signal processing algorithms, to data processing arrival estimation.
and control. The resulting system level complexity drives
the need for modeling and simulation at all stages of the § Model the dynamics of ground-based, airborne, ship-
development cycle. borne or automotive radar systems with moving
targets and radar platforms.
Modeling and simulation tools can improve all aspects of
the radar system design workflow. Using these tools for § Design end-to-end phased array systems and analyze
radar design, you can: their performance under different scenarios using
realistic data.
§ Design waveforms and sensor arrays interactively,
and explore trade-offs with the radar range equation § Integrate models for RF components and complex
and link budget. antenna designs to increase level of radar system
design fidelity.

ISR Sensing Systems

Intelligence, Surveillance, and Reconnaissance (ISR) analysis, RADAR, FLIR, Mapping, Image/Video
systems are multi-domain smart systems and the typical Processing, Communications and machine learning
workflow to model such complex systems requires a techniques. MathWorks tools essentially provides a
single environment for simulation, modelling, system single unified framework/environment to accelerate the
integration, test & verification. Typically the process design and development of such complex smart systems.
involves Sensor Modelling, Big Data & Analytics

Robotics

Design and simulate a robot.
Prototype and test algorithms.
Connect to robot platforms or
peripherals.

Three of the most critical questions that robotics Connecting to Robot Platforms and Peripherals
engineers and scientists need to answer are:
With MathWorks tools you can directly communicate
§ How do I design and simulate a robot? from MATLAB with robots running ROS, robots
equipped with low-cost hardware such as Raspberry
§ How do I prototype and test algorithms for my Pi and Arduino, or other popular research robot
robot? platforms.

§ How do I connect to my robot platforms and “Model-Based Design and automatic code
peripherals? generation enable us to cope with the complexity of
Agile Justin's 53 degrees of freedom. Without
MATLAB® and Simulink® can help answer these Model-Based Design it would have been impossible
questions, and accelerate and streamline the design, to build the controllers for such a complex robotic
prototyping, and verification of robotics applications. system with hard real-time performance.” Berthold
Bäuml, DLR
Designing and Simulating Robotics Systems

Your current robotics design project may require you
to prototype a robot that has wheels, arms, and
sensors. You may know the basics of kinematics,
dynamics, servo, stepper motors, or CAD tools.
Simulink can help convert your ideas and concepts
into a functional robot design.

Prototyping Robotics Algorithms

MATLAB and Simulink enable you to quickly
prototype robotics algorithms using behavioral
simulations .For example, you can design collision
avoidance algorithms with supervisory control in a
3D environment, test vision-based object detection
and tracking algorithms with USB cameras, or
prototype motor control algorithms with
Microprocessors.

UAV

Engineers and Scientists developing high-integrity flight With a single environment, MathWorks tools enable the
management and control software for unmanned aerial engineers to
vehicles (UAVs) verify the software throughout
development using a variety of techniques, including § Simulate the UAV, visualize the simulation data
simulation, unit tests, formal tests, and hardware-in-the-
loop (HIL) simulations. Engineering teams can accelerate § Design, model, and analyze the control system
these verification steps, as well as the overall
development of UAV flight control software, with Model- § Design the Radar, Image and Video processing
Based Design.
§ Verify the simulation model based on the requirements

§ Perform testing, and automatically generate the
autopilot code

MATLAB and Simulink greatly reduced development
cycle time and cut system and software design and
testing costs by 50%.” —Feng Liang, BAE Systems
Controls

GNC Systems and Avionics

Using MATLAB and Simulink, control engineers are Propulsion Systems
achieving complex designs without expensive prototypes
by simulating the control algorithm with the plant model Engineers rely on MathWorks products to design fuel
before implementation. These products help them design controls for launch vehicles, jet engines, and other
for multiple physical configurations, such as the common propulsion systems that meet rigorous fuel-efficiency and
bus architecture of a satellite design and the three aircraft performance requirements. With MATLAB, Simulink,
and Stateflow® they can work in one environment to
variations─ conventional landing, short landing, and simulate the effect of design changes on the entire
system, and quickly visualize and analyze engine-test
carrier landing—of the Joint Strike Fighter (JSF). In a results.
single environment, engineers work on:
“MathWorks tools are our long-term testing solution
§ Building and sharing GNC models for the facility. We are in the process of converting
our Fortran-based systems to Simulink for hardware-
§ Integrating and simulating system-level effects of in-the-loop testing using Simulink Real-Time.”
controls and mechanical design changes —Kenneth Anthony, Guided Weapons Evaluation
Facility, U.S Air Force
§ Reusing automatically generated flight code and test
cases

§ Integrating new designs with legacy designs and tools

Certification

Aerospace engineers who work on high-integrity § Traceability to requirements
systems are under constant pressure to not just meet the
stringent requirements of the systems they design, but § Compliance with requirements
also keep pace with industry demands for increased
development speed and quality. With Model-Based § Robustness of requirements
Design already established as a design workflow, these
engineers have been extending their use of MathWorks § Conformance to standards
tools for projects and large programs requiring
certification. Software systems deployed in safety-critical § Verification and validation
applications in aerospace and other industries must
satisfy rigorous development and verification standards. Using Model-Based Design, engineers can satisfy DO-
Most widely used of these standards are DO-178BC and 178C and DO-254 objectives while realizing cost and
DO-254 time-to-market benefits associated with early verification
of requirements, automated linking to requirements,
The DO-178C standard specifies objectives across the model and code standards checking, code generation,
development cycle to achieve flight software report artifact generation, and test case reuse.
certification. The DO-254 standard defines a set of
objectives for hardware to be certified for use in airborne “Simulink and Model-Based Design reduced the
systems. It is modelled after DO-178, the equivalent effort needed to upgrade functionality, code analysis
standard for flight software certification. Activities to time, and design time for the safety-critical
satisfy DO-178C and DO-254 objectives can be time- embedded system. The compatibility of Simulink with
consuming and expensive, including several associated the DO-178 process gave us confidence to use
with design, coding, and integration processes: Model-Based Design for our upcoming DO-178
projects.” —Manju Nanda, CSIR-National
Aerospace Laboratories

Simulink as a Platform for Model-Based Design

Simulink® is a block diagram environment for ODE solvers
multidomain simulation and Model-Based Design. It
supports system-level design, simulation, automatic code § Scopes and data displays for viewing simulation
generation, and continuous test and verification of results
embedded systems. Simulink provides a graphical
editor, customizable block libraries, and solvers for § Project and data management tools for managing
modeling and simulating dynamic systems. It is model files and data
integrated with MATLAB®, enabling you to incorporate
MATLAB algorithms into models and export simulation § Model analysis tools for refining model architecture
results to MATLAB for further analysis. and increasing simulation speed

Key Features § MATLAB Function block for importing MATLAB
algorithms into models
§ Graphical editor for building and managing
hierarchical block diagrams § Legacy Code Tool for importing C and C++ code into
models
§ Libraries of predefined blocks for modeling
continuous-time and discrete-time systems

§ Simulation engine with fixed-step and variable-step

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