RADAR 2008

Tutorials

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Eight half day tutorials are confirmed. These will be held at the Conference venue on Tuesday 2 September.

Jump to:

morning

Tutorial 1 Prof. Fabrizio Berizzi - Basics of radar imaging and SAR

Tutorial 2 Dr Stuart J. Anderson - HF Sky wave radar

Tutorial 3 Dr Braham Himed - STAP techniques and applications

Tutorial 4 Dr Samuel Davey - Track-before-detect techniques

afternoon

Tutorial 5 Dr. Marco Martorella - Inverse Synthetic Aperture Radar: Concepts and Techniques

Tutorial 6 Dr Stuart J. Anderson - HF surface wave radar

Tutorial 7 Prof. Simon Watts, Dr Keith Ward - Sea Clutter: Scattering, the K Distribution and radar performance

Tutorial 8 John Laden - Maritime Surveillance Radar Systems Engineering

Morning session

Tutorial 1: Prof. Fabrizio Berizzi - Basics of radar imaging and SAR

Radar systems were born during the World War II to detect enemy targets. Nowadays radars are also used in civilian applications for surveillance purposes: in airports for Air Traffic Control (ATC), on ships for navigation, on car for driving aid, others.

Low resolution radars are typically used for surveillance. In these systems, spatial cells are usually much greater than the target size. Detection is generally presented as a single spot on the radar digital PPI and the target characteristics are those of a point scatterer.

When target details are needed, fine spatial resolution is required. In modern coherent radar, spatial resolution cells can be reduced by using wide bandwidth transmitted signals (finer range resolutions), and by coherently processing echoes coming from different target aspect angles (finer azimuth resolution). The results is an electromagnetic image of the target where fine details can be observed.

The goal of this tutorial is to provide basic concepts of radar imaging with specific focus on Synthetic Aperture Radar (SAR).

The tutorial is organized into three parts: High Range Resolution radars, basic concepts of radar imaging with examples of Real Aperture Radars (RAR) and finally SAR.

After a brief introduction on pulse radars, high range resolution radars are introduced and described. Techniques for range profile reconstruction are presented both for wide instantaneous bandwidth and wide synthetic bandwidth waveforms.

A definition of radar imaging is given and supported by examples of RAR and SAR systems. Coherent integration and Range-Doppler will be explained as the two most simple image formation techniques. A few aspects of SAR system design will be illustrated. Several operating modes, including stripmap, spotlight, multilook and scanSAR will be detailed. The tutorial ends with an overview on past and current SAR systems.

Contents

1. Introduction to pulse radar systems (definition and nomenclature)

2. High Range Resolution (HRR) radar

2.1. Pulse compression principles

2.2 Transmitted waveforms

2.2.1 Wide Instantaneous bandwidth signals - Chirp pulses - Phase coded signals

2.2.2 Wide synthetic bandwidth signals - Stepped frequency waveforms - Range profiling - Waveform parameter design

3. Fundamentals of radar imaging

3.1. Introduction

3.2. Circular scan Real Aperture Radar (CS-RAR)

3.3. Side looking Real Aperture Radar (SL-RAR) - System geometry - Spatial resolution - Image formation

4. Synthetic Aperture Radar (SAR)

4.1. Fundamentals

4.2. Coherent integration technique

4.3. Stripmap SAR image formation

4.4. Range Doppler Technique

4.5. System design

4.5.1. Depth of focus

4.5.2. PRF constraints

4.5.3. Range Migration

4.5.4. Examples

4.6. Multilook mode

4.7. ScanSAR mode

4.8. Spotlight mode

5. Overview of current and past SAR systems

Presenter : Prof. Fabrizio BERIZZI Prof. Fabrizio Berizzi received the Electronic Engineering Laurea and PhD degrees from the University of Pisa (Italy) in 1990 and 1994 respectively. He has been an Associate Professor of the Univ. of Pisa since Oct. 2000. He is a lecturer of "Remote sensing systems" at the Univ. of Pisa and "Radar Techniques" at the Univ. of Siena. He is a IEEE Senior member since 2006. He has been working on Synthetic Aperture Radar (SAR) and Inverse Synthetic Aperture Radar (ISAR) since 1990. He is co-author of more than 80 papers and the book "Radar remote sensing systems" (in Italian), Apogeo, Milano. He has been guest editor of the "Special Issue on ISAR" on JASP (Eurasip) on June 2006 and co-chairman of the special session "Radar target imaging" at the "2003 IEEE Int. Radar Conf." Adelaide, (AUS) Sept. 2003. Since 1992 Prof. Berizzi has been involved in several scientific projects as a Principal Investigator funded by the Univ. Ministry, Defence Ministry, Italian and European Space Agencies, several industries, Tuscany Region.

Tutorial 2: Dr Stuart J. Anderson - HF Sky wave radar

HF skywave radars exploit reflection from the earth's ionosphere at heights of 100 - 350 kilometres to achieve 'over-the-horizon' illumination of the distant earth's surface. The general pattern of this illumination is governed not only by the radar antenna design but also by the electron density distribution within the ionosphere, which varies over a wide range of spatial and temporal scales in response to solar radiation, dynamical processes in the enveloping magnetosphere, planetary tides, internal waves and plasma instabilities, forcing from the underlying atmosphere and anthropogenic sources. One of the distinguishing features of HF skywave radars is that they must adapt to the ever-changing environmental conditions in order to achieve the desired illumination of the target and reception of the scattered field. This adaptation may span octaves in frequency, bandwidth, radiated power and other radar parameters, whilst dealing with several orders of magnitude variation in target RCS, external noise levels and environmental clutter. As a consequence, the design and effective operation of a skywave radar constitutes a complex optimization problem in which the key to success is the ability to exploit detailed knowledge of the prevailing environment and the associated physics.

This tutorial surveys the principles of operation of HF skywave radar, illustrating the logic behind the designs which have evolved over the past half century. A fairly detailed account of the structure and dynamics of the ionosphere and of a variety of related geophysical phenomena provides an essential basis for understanding the limitations, as well as the capabilities, of skywave radars addressing a variety of tactical and strategic missions. The electromagnetics of skywave propagation and scattering at HF is treated in some detail, emphasizing the differences between the HF and the microwave domains. Whilst not venturing into the detailed engineering, the main subsystems of skywave radars are described, emphasising the factors which impact on radar performance, and these are linked to consideration of systems-level issues. Finally, the function and implementation of signal processing techniques is treated and illustrated with examples from several HF radars.

Contents

1. Introduction

1.1 Propagation mechanisms at HF

1.2 Radar configurations

2. Historical perspective

3. Radar process models

3.1 Dimensionality of the radar process

3.2 Reduction to the standard radar equation

3.3 Formulation of the major inverse problems

4. The ionosphere

4.1 Structure

4.2 Dynamics

4.3 Models and their uses

5. Radiowave propagation : skywave

5.1 Magnetoionic theory

5.2 Simplified models

5.3 Some important complications

6. Waveforms

6.1 Basics of pulse, phase-coded and frequency-modulated CW waveforms

6.2 Factors influencing the choice of waveforms for skywave radar

6.3 Special waveforms designed for skywave radar applications

7. Transmitting system

7.1 Transmitters

7.2 Transmit antennas

7.3 Transmit arrays

8. Radar cross section and scattering

8.1 Scattering from discrete obstacles

8.2 Computational electromagnetics

8.3 Examples of RCS properties of representative targets

9. Clutter : Echoes from the environment

9.1 Land clutter

9.2 Sea clutter

9.3 Ionospheric clutter

10. Noise, interference and the HF spectrum

10.1 Sources of additive noise in the HF band

10.2 Spectrum occupancy and allocation

10.3 Spatial and temporal properties of HF noise

11. Receiving system

11.1 Receiving antennas

11.2 Receiving arrays

11.3 Receivers

12. Signal processing

12.1 Basics of signal decomposition

12.2 Functionality and physics-based processing techniques

12.3 Adaptive processing

13. Tracking and displays

13.1 Factors influencing choice of tracking algorithm

13.2 Metrics for tracker performance

13.3 Radar displays and operator responsibilities

Presenter : Dr Stuart J. ANDERSON Dr Stuart Anderson holds BSc (Hons) and PhD degrees from the University of Western Australia. Since 1972, Dr Anderson has worked in the Australian Defence Science and Technology Organisation, where he was responsible for developing the ocean surveillance and remote sensing capabilities of the Jindalee over-the-horizon skywave radar system and the Iluka HF surface wave radar system. He has worked as a visiting scientist in several countries, contributing to various national and international HF radar programs, as well as holding adjunct appointments at Curtin University of Technology (Professor of Applied Physics), the University of New South Wales (Professor of Mathematics), and the University of Rennes I, France, (Professor and Docteur honoris causa). His active research interests include electromagnetic scattering, ionospheric physics, radio oceanography, physics-based signal processing, microwave radar polarimetry, passive coherent location, and the exploitation of HF radar systems for a wide variety of missions. This work has been reported in over 250 journal papers, book chapters, conference papers and DSTO publications.

Tutorial 3: Dr Braham Himed - STAP techniques and applications

Space-Time-Adaptive Processing (STAP) is becoming an integral part of modern airborne and space-based radar (SBR) systems for Air/Ground/Surface Moving Target Indication (A/G/S MTI). STAP techniques combine spatial and temporal degrees of freedom to detect moving targets in strong background disturbance consisting of clutter and jamming. STAP uses the multiple spatial channels in a phased-array antenna and the multiple coherent pulses transmitted and received by the radar to form an adaptive weight vector that is applied to the received radar data. In order to calculate the adaptive STAP weight vector, the statistics of the interference environment are determined from the training or secondary data. The interference covariance matrix is not known a priori and must be estimated from independent and identically distributed (iid) data. However, experimental data obtained from several experiments have shown that this data is non-homogeneous, and hence violates the iid assumption. These facts are exacerbated when a bistatic, spaceborne, or a conformal radar configuration is employed. These issues and challenges will be identified and adequate solutions will be provided in this course.

The tutorial begins with the monostatic airborne radar system. The principles of STAP will then be extended to a bistatic configuration, where the transmitter and receiver are not collocated and move independently of each other. Moving the platform to space raises other issues which make the application of STAP techniques very difficult, and will be discussed next. Recently, there has been a strong interest in deploying smaller platforms, where three-dimensional (3D) conformal arrays are used. We will extend the STAP concept to these antenna array systems. We will then introduce the concept of simultaneously performing Synthetic Aperture Radar (SAR) imaging and MTI, using multichannel systems. We will conclude the tutorial with the application of advanced STAP techniques to Hyperspectral Imaging (HSI).

1. Overview

Introduction and notation
Basic detection theory
Estimation considerations
CFAR issues
Sample matrix-based approaches
Multi-channel parametric-based techniques

2. STAP for Monostatic Air borne Radar Systems

Practical implementation and performance
Multi-channel airborne radar measurements (MCARM) data analysis
Real-Time MCARM (RTMCARM) system
Knowledge aided STAP

3. Extensions to Bistatic Airborne Radar Systems

Bistatic geometry
Bistatic isorange / isoDoppler / isocone contours
Bistatic angle-Doppler traces and spectra
Bistatic STAP techniques

4. Space-Based Radar (SBR) STAP Systems

Radar - Earth geometry
Effect of Earth's rotation
Effect of range ambiguities
Performance of SBR-STAP
Waveform diversity techniques for SBR

5. Conformal Array STAP

Issues and challenges with conformal arrays
Antenna modeling
Conformal array STAP techniques

6. Synthetic Aperture Radar (SAR) - MTI Imaging Techniques

Along Track Interferometry (ATI)
Processing of NASA's AirSAR data
Processing of MCARM data

7. Hyperspectral Imaging (HSI)

Overview of HSI
HSI subpixel target detection
Advanced STAP techniques for HSI
Experimental results

8. Concluding remarks

9. Bibliography

Braham Himed received the Ph.D degree in electrical engineering from Syracuse University in 1990. Currently, he serves as the chief research officer at Signal Labs Inc. in Reston, Virginia. Prior to that, he was with the United States Air Force Research Laboratory, Rome, New York, where he was involved in airborne and spaceborne phased array radar systems, waveform diversity, and tomography. His research interests include detection, estimation, multichannel adaptive signal processing, space-time adaptive processing, and ground penetrating radar technology. Braham is a Fellow of the IEEE and a member of the AES Radar Systems Panel.

Tutorial 4 Samuel Davey, IRSD DSTO Track-before-detect techniques

The conventional method to process sensor data is to compartmentalise the required signal processing into a sequence of independent algorithms. Typical stages include range and doppler processing, beam forming, interference mitigation, detection and tracking. Conventional tracking algorithms are designed assuming this processing model, and assume a set of point observations as an input. However, the detection algorithm is a hard decision process, and for low SNR targets must be tuned to a high probability of false alarm to ensure sufficient target detections. In this case, the conventional tracking approaches become swamped by the false detections and produce too many false tracks.

Track Before Detect (TkBD) is the name given to the problem of joint target detection and estimation. Essentially, the detector is removed from the sequence and the tracker operates directly over the sensor data, which is typically an image. TkBD algorithms are typically able to detect and track targets at significantly lower SNR than conventional methods.

1. Introduction

1.1 Conventional detection and tracking

1.1.1 Detectors

1.1.2 Probabilistic Data Association
1.2 TkBD paradigm

1.3 Historical development of TkBD approaches

2. Analytic Approximations to TkBD

2.1 Review of the Extended Kalman Filter

2.2 Extended Kalman Filter for TkBD

3. Grid based TkBD

3.1 3D matched filter (velocity filter)

3.2 Hough Transform

3.3 Dynamic Programming (Viterbi Algorithm)

3.4 Bayesian Filter

4. Particle Filtering for TkBD

4.1 Review of Particle Filtering

4.2 TkBD state estimation with particle filters

4.3 TkBD detection with particle filters

4.4 Multi-target extensions

5. Maximum Likelihood Probabilistic Data Association

5.1 ML-PDA algorithm

5.2 ML-PDA search techniques

6. Histogram Probabilistic Multi-Hypothesis Tracker

6.1 Review of PMHT

6.2 H-PMHT

6.3 Amplitude Estimates

6.4 Track Management

7. Comparison of Several TkBD approaches

8. Conclusion

Samuel Davey received the Bachelor of Engineering, Master of Mathematical Science, and PhD degrees from the University of Adelaide in 1995, 1998, and 2003 respectively. In 1995 he joined the Defence Science and Technology Organisation, where he has worked on tracking system performance assessment, design of real-time multi-target tracking algorithms, automatic track initiation, and multi-sensor fusion. His current research interests include decentralised data fusion, multi-sensor fusion performance analysis, track before detect and probabilistic multi-hypothesis tracking.

Afternoon session

Tutorial 5: Dr. Marco Martorella - Inverse Synthetic Aperture Radar: Concepts and Techniques

Inverse Synthetic Aperture Radar (ISAR) is a technique used for reconstructing radar images. Modern tracking radar implicitly offer the system requirements needed for implementing ISAR imaging. ISAR images are obtained by means of a signal processing that can be enabled both on and off-line. Automatic Target Recognition (ATR) systems are often based on the use of radar images because they provide a 2D e.m. map of the target reflectivity. Therefore, classification features that contain spatial information can be extracted and used to increase the performance of classifiers.

The first part of this tutorial deals with the basic principles of ISAR whereas the second part concerns basic and advanced ISAR techniques. The ISAR system is introduced by defining the radar-target geometry and by considering simple radar concepts. The derivation of the ISAR processor is obtained by defining the signal model and by interpreting it in the Fourier domain.

Basic and advanced techniques are presented in order to provide an overview of the current methods used for implementing ISAR and improving its performance. In particular, the problem of ISAR image autofocus is analysed in details and several solutions are presented. The time window selection and cross-range scaling problems are also addressed. The last two topics of the tutorial deal with polarimetric and bistatic ISAR, which represent two new frontiers in ISAR imaging. ISAR processors for such systems are defined and their performance are analysed and compared to monostatic and single polarisation ISAR systems. Several examples with simulations and real data are provided throughout the tutorial in order to demonstrate the effectiveness and potentiality of ISAR imaging.

Contents

1. Introduction

1.1. Synthetic Aperture Radar (SAR)

1.2. Inverse Synthetic Aperture Radar (ISAR)

1.3. ISAR system

1.4. Examples of applications

2. Signal modelling

2.1. Radar-target geometry

2.2. Transmitted signal

2.3. Received signal (Time-Frequency representation)

2.4. Radial motion compensation

2.5. Interpretation of the received signal in the Fourier Domain

3. ISAR image reconstruction

3.1. Image formation

3.1.1. Range-Doppler

3.1.2. Polar Reformatting

3.1.3. Back-projection

3.2. Point Spread Function (PSF)

3.3. Image Resolution

3.4. Analogies and differences with SAR

4. ISAR image Autofocus

4.1. Hot Spot (HS) or Prominent Point Processing (PPP)

4.2. Phase Gradient Autofocus (PGA)

4.3. Image Contrast Based Autofocus (ICBA)

4.4. Image Entropy Based Autofocus (IEBA)

5. Cross-range scaling

5.1. Back-projection method

5.2. Chirp estimation method

6. Time window selection

6.1. Max Image Contrast (IC) method

6.2. Ad-hoc techniques for ISAR imaging of ships

7. Polarimetric ISAR

7.1. Concept of multi-polarisation image processing

7.2. Polarimetric ISAR Autofocus

7.2.1. Pol-PGA 7.2.2. Pol-PPP

7.2.3. Pol-ICBA

7.2.4. Pol-IEBA

7.3. Polarimetric decomposition and image interpretation

8. Bistatic ISAR

8.1. Geometry

8.2. Signal modelling

8.3. Image reconstruction

8.4. Analysis of the distortions introduced by time-varying bistatic angles and synchronisation errors

Presenter Marco Martorella received the Telecommunication Engineering Laurea (cum laude) and Ph.D. degrees from the University of Pisa (Italy) in 1999 and 2003 respectively. His research interests are in the field of Synthetic Aperture Radar (SAR) and Inverse Synthetic Aperture Radar (ISAR). He has organized journal special issues and conference special sessions on ISAR and he is co-author of more than 40 papers on SAR/ISAR imaging.

Tutorial 6: Dr Stuart J. Anderson - HF surface wave radar

HF surface wave radars exploit the electromagnetic ground wave mode of propagation to illuminate targets near the earth's surface at 'over-the-horizon' ranges with sufficient energy density to achieve detection via two-way propagation. The propagation loss is strongly influenced by the permittivity and electrical conductivity of the underlying terrestrial surface; significant ranges can be attained only when almost all the propagation path lies over the ocean. Sea surface conditions have a significant impact on the spatial and temporal properties of the ground wave signal.

Existing HFSWR systems are clustered into two main categories : (i) low power, reasonably compact remote sensing systems designed to monitor ocean currents and measure wave spectra, and (ii) high power military systems with greater sensitivity and extended range coverage, employed for detection and tracking of ships, smaller ocean-going vessels and low-flying aircraft which fall below the horizon of microwave 'line-of-sight' radar systems. In addition, mention should be made of ship-borne HFSWR systems, though these remain the subject of research and development rather than being fitted to operational platforms.

Many of the engineering and the physics associated with HFSWR systems is closely related to that of HF skywave radars, including the transmitters, receivers, scattering phenomenology, noise environment and clutter properties. On the other hand, waveforms, antenna design, propagation mechanisms and signal processing have rather less in common.

This tutorial sets out to describe the principle characteristics of HFSWR systems, both the low power remote sensing systems and the military surveillance radars. The main subsystems of such radars are described, emphasising the factors which impact on HFSWR design. The electromagnetics of ground wave propagation and scattering is treated in some depth. A fairly detailed account of the geometry and dynamics of the ocean surface is provided, since it is effectively this surface that constitutes the 'channel' connecting radar to target, as well as serving as the target of interest in the case of remote sensing. The issue of radar siting is treated in detail, as in practice this often entails important compromises in radar design and capability. Advanced signal processing techniques are discussed and their efficacy demonstrated. Remote sensing capabilities are reviewed and illustrated with products from a number of existing HFSWR systems.

This tutorial has a small amount of overlap with the tutorial on HF skywave radar.

Contents

1. Introduction Propagation mechanisms at HF Radar configurations

2. Historical perspective - HFSWR

3. Radar process models for HFSWR

3.1 Dimensionality of the radar process

3.2 Reduction to the standard radar equation

3.3 Formulation of the major inverse problems

4. The ocean surface

4.1 Geometry

4.2 Dynamics

4.3 Spectral representations

5. Ground wave propagation

5.1 Formal theory

5.2 Simplified models and key parameters

5.3 Some important complications

6. Waveforms

6.1 Factors influencing the choice of waveforms for HFSWR

6.2 Special waveforms designed for HFSWR applications

7. Transmitting system

7.1 Transmit antennas for HFSWR

7.2 Transmit arrays for HFSWR

8. Radar cross section and scattering

8.1 Scattering from rough surfaces

8.2 Scattering from discrete obstacles on or above an interface

8.3 Examples of RCS properties of representative HFSWR targets

9. Clutter : Echoes from the environment as observed with HFSWR

9.1 Land clutter

9.2 Sea clutter

9.3 Ionospheric clutter

10. Noise, interference and the HF spectrum : HFSWR aspects

10.1 Sources of additive noise in the HF band

10.2 Spectrum occupancy and allocation

10.3 Spatial and temporal properties of HF noise

11. Receiving system

11.1 Receiving antennas for HFSWR

11.2 Receiving arrays for HFSWR

11.3 Receivers

12. Signal processing

12.1 Basics of signal decomposition

12.2 Functionality and physics-based processing techniques

12.3 Adaptive processing for HFSWR

Tutorial 7: Prof. Simon Watts, Dr Keith Ward - Sea Clutter: Scattering, the K Distribution and radar performance

The understanding and modelling of radar sea clutter is central to the design and performance evaluation of radars in a maritime environment. The first part of the tutorial will introduce the methods used to describe radar sea clutter and show how physical and empirical models are developed. The second part of the tutorial will show how clutter models are used to predict performance and analyse the performance of CFAR detection systems. This will concentrate on the application of the compound K distribution sea clutter model. Tutorial text: K.D.Ward, R.J.A.Tough and S.Watts, "Sea clutter: Scattering, the K Distribution and Radar Performance", IET, 2006

Course outline:

Radar clutter modelling

The characteristics of sea clutter

Reflectivity

Polarisation characteristics

Amplitude statistics

Spectrum

Spatial correlation

Modelling of radar scattering by the ocean surface

Statistical models of sea clutter

The Compound K distribution

Data analysis and simulation

Performance prediction

Radar detection performance calculations

Clutter reflectivity models

Detection calculations with the compound K-distribution model

CFAR detection

Cell-averaging CFAR analysis CA-CFAR, GO-CFAR, OS-CFAR etc.

Cell-averaging CFAR detection in spatially-correlated sea clutter Ideal CFAR

Presenters. Simon Watts graduated from the University of Oxford in 1971 and obtained an MSc from the University of Birmingham in 1972. He is currently deputy Scientific Director of Thales UK, Aerospace Division and is also a Visiting Professor in the department of Electronic and Electrical Engineering at University College London. He joined Thales (then EMI Electronics) in 1967 and since then has worked on a wide range of radar and EW projects. His research interests include the modelling of radar sea clutter and the development of signal processing techniques for radar target detection, and he obtained a PhD for work in these areas from the CNAA in 1987. He is author and co-author of over 35 journal and conference papers, and several patents. He was chairman of the international radar conference RADAR-97. He was appointed MBE in 1996 for services to the UK defence industry and is a Fellow of the Royal Academy of Engineering, Fellow of the IEE and Fellow of the IEEE.

Keith Ward graduated from the University of Cambridge in 1977 and obtained a PhD from the University of Birmingham. Throughout his career he has worked on radar and military systems. His areas of research have covered: radar sea scattering, target detection, ocean imaging, ship classification, radar imaging theory, low probability of intercept (LPI) techniques, and radar seekers. In addition he has had responsibility for managing radar experiments and providing technical support to UK MOD procurements. His work on sea scattering has received wide recognition (IEE Electronics Letters Premium 1980, Mountbatten Prize 1990) and is being applied throughout the world. He has served as Honorary Editor of IEE Proceedings Part F, as a member of IEE professional group E15, on conference organising committees, and as chairman of TTCP KTP3 (an international panel of experts on radar signal processing). He has published over 100 papers and reports. At MoD/DRA he achieved an Individual Merit promotion. He left MoD/DRA to set up TW Research with Dr. R.J.A. Tough in September 1995. Since then he has carried out consultancy and contract research on ocean imaging, small target detection, rough surface scattering, detection theory, range profile classification, radar system analysis and performance analysis for clients in the UK, USA and Australia. He is a Fellow of the Royal Academy of Engineering and a Fellow of the IET.

Tutorial 8 John Laden Maritime Surveillance Radar Systems Engineering

This tutorial provides a systems engineering approach to the design of a radar system that provides an interdisciplinary approach and means to enable the realization of a successful radar system. It focuses on defining customer needs and required functionality early in the development cycle, documenting requirements, then proceeding with design synthesis and system validation while considering the complete problem:

Operations
Performance
Test
Manufacturing
Cost & Schedule
Training & Support
Disposal

Systems Engineering integrates all the disciplines and specialty groups into a team effort forming a structured development process that proceeds from concept to production and to operation. It considers both the business and the technical needs of all customers with the goal of providing a quality product that meets the user needs. This tutorial will provide a top level introduction to Systems Engineering focused on radar systems.

Tutorial Overview

a. Defining Customer Needs

i. Planning

ii. Requirements

iii. Schedule

iv. Cost

v. Risk Management

vi. Security

b. Design definition

i. Evaluation of Alternatives

ii. Simulation

c. Defining System Interfaces

d. Preparing Specifications

e. Manufacturing

f. Testing

g. Integration

h. Training

i. Operational Support

j. Disposal

Presenter: John Laden received his Bachelor Degree in Electrical Engineering from the University of Santa Clara and is a registered Electrical Engineer in California, USA. He has worked at Boeing, Lockheed and most recently at Raytheon on Ground, Sea, Airborne and Satellite based Radar systems. This included a Security Radar system for the minuteman missile Silo, SAR radars for large and small surveillance aircraft both manned and unmanned. He worked on radar designs for satellites and ships. He was the System engineer on JORN for several years and recently was the Chief Engineer for the SBX system which is a large radar that is mounted on a Semi-submersible Platform and is currently operational in the Pacific. He has been a member of IEEE for 23 years and is now a Private Consultant working with Associated Electronic Services in Australia.