Kalman Filtering and Its Real‐Time Applications

Kalman filter was pioneered by Rudolf Emil Kalman in 1960, originally designed and developed to solve the navigation problem in Apollo Project. Since then, numerous applications were developed with the implementation of Kalman filter, such as applications in the fields of navigation and computer vision\u27s object tracking. Kalman filter consists of two separate processes, namely the prediction process and the measurement process, which work in a recursive manner. Both processes are modeled by groups of equations in the state space model to achieve optimal estimation outputs. Prior knowledge on the state space model is needed, and it differs between different systems. In this chapter, the authors outlined and explained the fundamental Kalman filtering model in real‐time discrete form and devised two real‐time applications that implemented Kalman filter. The first application involved using vision camera to perform real‐time image processing for vehicle tracking, whereas the second application discussed the real‐time Global Positioning System (GPS)‐aided Strapdown Inertial Navigation Unit (SINU) system implementation using Kalman filter. Detail descriptions, model derivations, and results are outlined in both applications

Real-Time SAR Auto-Focus: System Modelling, Simulation, And Implementation Scheme

This study deals with the SAR autofocus problem, with the aim to implement the proposed autofocus algorithm in real-time

Design And Construction Of A C-Band Polarimetric Scatterometer

A ground-based C-band scatterometer system has been constructed at the Faculty of Engineering, Multimedia University, Malaysia. This is a full polarimetric radar operating at 6Ghz frequency (5cm wavelength). The scatterometer is targeted for short range operation from 20 to 100 meter. It has the capability to determine complete backscattering matrix of various natural targets over a wide dynamic range (+20dB to -40dB). The system operates using frequency-modulated continuous-wave (FM-CW) technique. For short range radar, this is a simpler and more economical hardware design. In general, the system hardware consists of four major sections: an antenna, a radio frequency (RF) subsystem, and intermediate frequency ( IF) electronic, and a data acquisition unit (DAU). The antenna is a parabolic reflector with dual-polarised corrugated horn feed. The RF section is constructed in housefrom several RF components, which include a C-band voltage-controlled oscillator, directional coupler, circulator, RF switches, band-pass filter, isolators, and quadrature mixer. In RF section, the received signal is mixed with a portion of the transmitted signal to produce low frequency IF signals. The IF signals are pre-processed in IF section, before they are digitised in DAU. A microcomputer is used to store the measurement data. In addition, a dedicated computer program has been written to automate the measurement system and to analyse the collected data. Both internal and external calibrations are employed to eliminate short-term and long-term variations in the measurements, respectively. A 100ns delay line is incorporated in the hardware system for internal calibration. External calibration is accomplished by using the single-target calibration technique (STCT) proposed by Sarabandi and Ulaby (1990). With this technique, only a conducting sphere is needed to fully calibrate the radar for all polarisation combinations. The internal calibration is carried out for every measurement, while the external calibration is conducted only once in a controlled environment before conducting the actual field measurement. In May 1999, a series of controlled experiments has been conducted to evaluate the system performance. The test site is a typical football field. A styrofoam column, which has a dielectric constant close to that of the air, is used to support the test targets. The test targets include a non-depolarised 8" trihedral corner reflector, and a rotatable 4" X 8" dihedral corner reflector. The dihedral is rotated in different angles to provide different sets of polarimetric data. The measurement results show good agreement with the theory. This system will be used to conduct in situ backscatter measurement on earth terrain such as vegetation fields, forest and soil surfaces in the near future

Compact L-& C-Band SAR Antenna

A compact three-layer shared-aperture dual-band dual-polarised sub-array operating in L/C-band is designed for application in synthetic aperture radar (SAR). Square, aperture-coupled patches in the C-band and a square, perforated L-band patch are combined on the top layer. They are fed from behind the ground plane by a combined feed system. Combined layers of patches and feed layers results in a highly compact antenna suitable for low weight applications such as space borne synthetic aperture radars (SAR)

Design and construction of a near real-time advanced automated C-band scatterometer system

This paper presents the design and construction of a complete near real-time scatterometer system for in-situ measurement. The full polarimetric system is comprised of inexpensive Frequency Modulated Continuous Wave (FMCW) radar that is efficiently constructed from a combination of commercially available components and in-house fabricated circuitry. An automated advanced antenna positioning system (AAPS) is included in the development of the system, giving rise for a more practical measurement. The backscattering matrices of a 4 '' x 8 '' dihedral corner reflector are rotated and measured at different angles to provide different sets of polarimetric data. The backscattering matrices of 8 '' sphere, 12 '' sphere and 16.5 '' trihedral are also measured and the results are presented in this paper. In order to verify the effectiveness of the calibration technique, the results are compared with the theoretical values. Consideration on the challenges of measurement in outdoor environment is countered with external and internal calibration. As a result, the proposed scatterometer system has shown good correlation between measurement and theoretical results

An introduction to synthetic aperture radar (SAR)

This paper outlines basic principle of Synthetic Aperture Radar (SAR). Matched filter approaches for processing the received data and pulse compression technique are presented. Besides the SAR radar equation, the linear frequency modulation (LFM) waveform and matched filter response are also discussed. Finally the system design consideration of various parameters and aspects are also highlighted

Development of a compact S-band SAR for earth resource monitoring

The design and development of Synthetic Aperture Radar (SAR) is one of the focused research areas in Malaysia since early 2000s. The main objective of this research is to develop an all-weather instrument for earth resource monitoring in Malaysia. The first SAR sensor developed was a C-band (5.3 GHz) SAR mounted on a small unmanned aerial vehicle (UAV) [1]. In 2013, a new SAR sensor operating at S-band (3.125 GHz) frequency has been developed for earth resource monitoring. It is an enhanced version of the former C-band SAR sensor, with 1.5 m spatial resolution and onboard SAR processing capabilities. This paper presents the design and development of the new S-band SAR system and its preliminary test results for remote sensing applications

FPGA-Based Chirp Generator for High Resolution UAV SAR

This paper discusses the design and development of a FPGA-based chirp generator for high resolution Unmanned Aerial Vehicle (UAV) Synthetic Aperture Radar. The desired bandwidth of the chirp signal is 100 MHz (combination of I and Q channels) with a chirp rate of 5 MHz/μs. Two algorithms based on the Memory-based architecture and the Direct Digital Synthesizer (DDS) architecture are presented. The measurement results indicate that the DDS chirp generator is a preferred choice for high-resolution SAR application

Smart Sensing for Earth Resource Monitoring

Smart sensing is the process of monitoring the properties of a particular object or phenomenon and performing some predefined actions upon detection of specific characteristics. In the context of earth resource monitoring, a smart sensing system allows automated collection of environmental data, extraction of critical information, and sending timely notifications to users for further actions. A typical smart sensing system setup involves a front-end sensor, an embedded controller or processor, a communication link, and a cloud-based platform. This paper presents the framework of a smart sensing system with example use cases in air quality monitoring, landslide monitoring and precision agriculture

PatchMatch Filter-Census: A slanted-plane stereo matching method for slope modelling application

Image matching is a well-studied problem in computer vision. Conventional image matching is solved using image feature matching algorithms, and later deep learning techniques are also applied to tackle the problem. Here, a slope-modelling framework is proposed by adopting the image matching techniques. First, image pairs of a slope scene are captured and camera calibration as well as image rectification are performed. Then, PatchMatch Filter (PMF-S) and PWC-Net techniques are adapted to solve the matching of image pairs. In the proposed PatchMatch Filter-Census (PMF-Census), slanted-plane modelling, image census transform and gradient difference are employed in matching cost formulation. Later, nine matching points are manually selected from an image pair. Matching point pairs are further used in fitting a transformation matrix to relate the matching between the image pair. Then, the transformation matrix is applied to obtain a ground truth matching image for algorithm evaluation. The challenges in this matching problem are that the slope is of a homogenous region and it has a slanted-surface geometric structure. In this work, it is found out that the error rate of the proposed PMF-Census is significantly lower as compared with the PWC-Net method and is more suitable in this slope-modelling task. In addition, to show the robustness of the proposed PMF-Census against the original PMF-S, further experiments on some image pairs from Middlebury Stereo 2006 dataset are conducted. It is demonstrated that the error percentage by the proposed PMF-Census is reduced significantly especially in the low-texture and photometric distorted region, in comparison to the original PMF-S algorithm. This further verifies the suitability of the PMF-Census in modelling the outdoor low-texture slope scene