Tien Sze Lim

A new unmanned aerial vehicle synthetic aperture radar for environmental monitoring

A new Unmanned Aerial Vehicle (UAV) Synthetic Aperture Radar (SAR) has been developed at Multimedia University, in collaboration with Agency of Remote Sensing Malaysia. The SAR operates at C-band, single V V -polarization, with 5m £ 5m spatial resolution. Its unique features include compact in size, light weight, low power and capable of performing real-time imaging. A series of fleld measurements and ∞ight tests has been conducted and good quality SAR images have been obtained. The system will be used for monitoring and management of earth resources such as paddy flelds, oil palm plantation and soil surface. This paper reports the system design and development, as well as some preliminary results of the UAVSAR.

A SAR Autofocus Algorithm Based on Particle Swarm Optimization

In synthetic aperture radar (SAR) processing, autofocus techniques are commonly used to improve SAR image quality by removing its residual phase errors after conventional motion compensation. This paper highlights a SAR autofocus algorithm based on particle swarm optimization (PSO). PSO is a population-based stochastic optimization technique based on the movement of swarms and inspired by social behavior of bird flocking or fish schooling. PSO has been successfully applied in many different application areas due to its robustness and simplicity (1-3). This paper presents a novel approach to solve the low-frequency high-order polynomial and high- frequency sinusoidal phase errors. The power-to-spreading noise ratio (PSR) and image entropy (IE) are used as the focal quality indicator to search for optimum solution. The algorithm is tested on both simulated two-dimensional point target and real SAR raw data from RADARSAT-1. The results show significant improvement in SAR image focus quality after the distorted SAR signal was compensated by the proposed algorithm.

A Comparison of Autofocus Algorithms for SAR Imagery

A challenge in SAR system development involves compensation for nonlinear motion errors of the sensor platform. The uncompensated along-track motions can cause a severe loss of geometry accuracy and degrade SAR image quality. Autofocus techniques improve image focus by removing a large part of phase errors present after conventional motion compensation. It refers to the computer-automated error estimation and subsequent removal of the phase errors. Many autofocus algorithms have been proposed over the years, ranging from quantitative measurement of residual errors to qualitative visual comparison. However, due to the fact that different data sets and motion errors were employed, it is difficult to perform comparative studies on various algorithms. This paper compares and discusses some practical autofocus algorithms by using a common data set. Standard focal quality metrics are defined to measure how well an image is focused. Their implementation schemes and performance are evaluated in the presence of various phase errors, which include polynomial-like, high frequency sinusoidal, and random phase noise.

Investigation of Direct A-GPS Positioning for Hybrid E-OTD/GNSS

Assisted Global Positioning System (A-GPS) is intended to offer positioning capability with improved service availability and accuracy gain to areas such as street canyon in major cities, and even into indoor environment in some cases. This paper studies the positioning determination based on hybrid E-OTD/GNSS system developed in EMILY project. This study proposes another way of position calculation which is referred as direct method in this paper. This is an easier and simpler method as compared to conventional approach based on Taylor series expansion which is referred as approximate method in this paper. The proposed method requires additional ranging information which can be easily sought from surrounding base station (BTS). The obtained results show that the proposed direct method can achieve better accuracy as compared to approximate method.

Autofocus Algorithms Performance Evaluations Using an Integrated SAR Product Simulator and Processor

The design and development of synthetic aperture radar (SAR) system for a particular application often requires redesign of software and hardware to optimize the system performance. In addition, evaluations of the performance of existing autofocus and image formation algorithms are required for the SAR system designers to select a most suitable algorithm for a given image quality requirements. This is a time-consuming taskwithout a reconfigurable and comprehensive software package. Thus, a comprehensive SAR integrated simulator and processor software is needed to aid the system designers in optimizing all the system parameters and performance. This paper presents an integrated SAR simulator and processor (iSARSIMP) software package and the performance of three selected SAR autofocus algorithms has been evaluated as examples to demonstrate the usefulness of the iSARSIMP for SAR system designers. In the performance evaluation, simulated and actual SAR raw data were used for further analysis and comparison of the three selected autofocus algorithms.

High-frequency Phase Error Reduction in Sar Using Particle Swarm of Optimization Algorithm

Since 1970, various autofocus algorithms have been developed to improve synthetic aperture radar (SAR) image quantity by removing its residual phase errors after conventional motion compensation. In particular, the high-frequency SAR phase error is formulated as a nonlinear constrained optimization problem in and a genetic algorithm based autofocus technique is used to minimize the phase noise at the expense of high computational cost. This paper presents a relatively simple and computational efficient approach to solve the high-frequency SAR phase noise. The proposed algorithm utilizes a particle swarm optimization (PSO) technique, which has been successfully applied in many applications due to its robustness and simplicity. The power-to-spreading noise ratio (PSR) is used as the focal quality indicator to search for optimum solution. The algorithm is tested on simulated targets and the results show significant improvement in the phase measurements of SAR signals. Furthermore, the proposed approach outperforms the former genetic algorithm based technique in terms of the computational time and solution errors — which clearly demonstrates the potential of this approach in SAR autofocusing.

THE MASAR PROJECT: DESIGN AND DEVELOPMENT

In 2002, the MASAR (Malaysian Airborne Synthetic Aperture Radar) project was initiated at Multimedia University (MMU), in collaboration with the Malaysian Centre for Remote Sensing (MACRES). The main objective of this project is to construct an instrument for earth resource monitoring in Malaysia. The proposed SAR system is a C-band, single polarization, linear FM radar. This paper outlines the major design issues and considerations for MASAR. In particular, the design and construction of the microwave system, microstrip antenna, and a high-speed data recording system are described. The SAR processing algorithm which incorporates motion compensation capability for high resolution image generation is also outlined.

Practical approach in estimating inertial navigation unit's errors

Inertial navigation unit (INU), which is commonly composed of three orthogonally aligned accelerometers and gyros, is well known for its short term measurement accuracy in position, velocity and attitude. However, such measurement accuracy degrades with time due to various types of errors. In this paper, a practical approach is proposed to estimate both the deterministic and random errors of an INU. The deterministic errors, which include bias and scaling errors, can be estimated through a simple experimental setup; while the random noise is modeled using Allan Variance (AV) analysis method. The empirical values of the errors are then fed into the INUs system model for error correction using Kalman filtering. Finally, the calibrated INU shows promising results in preserving long term accuracy of the motion sensor.

Conceptual Design of A High Resolution, Low Cost X-Band Airborne Synthetic Aperture Radar System

This paper describes the conceptual design of a low cost airborne Synthetic Aper- ture Radar (SAR) capable to obtain high-resolution image. The proposed system is an X-band, single polarization, high bandwidth linear FM radar and high resolution airborne SAR system. The system can be used as monitoring and management of earth resources such as paddy fleld, oil palm plantation and soil surface. First of all, the high level design will be discussed and detail design parameters are presented. It followed by radar electronics design, which outlined the detail in radar transmitter and receiver.

A GA-based autofocus technique for correcting high-frequency SAR phase error

The presence of a space-invariant sinusoidal phase error in the azimuth SAR (synthetic aperture radar) signal history causes paired echoes to appear in the system impulse response [1]. These high peaksidelobes may be interpreted erroneously as separate targets by conventional autofocus algorithms. In this paper, a new approach to solve the high-frequency phase noise problems in SAR imaging is presented. The phase error is formulated as a nonlinear optimization problem for continuous variables. The optimum solution is obtained by minimizing the entropy of the signal. The proposed algorithm utilizes a real-coded genetic algorithm (GA) in the first stage to direct the search towards the global optimum region and a local search method in the second stage to do fine tuning. The algorithm is tested on simulated point targets and the results show significant improvement in the target response, as compared to the conventional autofocus and optimization algorithms. Thus the efficiency and the success rate of the algorithm are placed in sharper focus to minimize high frequency phase noise. Furthermore, the complexity of the problems solved clearly demonstrates the usefulness of this novel approach in solving such nonlinear systems.