A new data acquisition and processing system for UAVSAR

Lim

et al. 2020

JETAP

This paper proposes a technique for synthesizing multiple point target scatterer Synthetic Aperture Radar (SAR) echoesin real-time. Traditional approaches require high computation resources to calculate the complex SAR echoes due to its complex mathematical model. The proposed technique employs the low computation Direct Digital Synthesis (DDS) approach to generate these complex sinusoid echoes. The proposed Synthetic Aperture Radar Echoes Synthesizer(SAR-ES)is capable of synthesizing SAR echoes accurately in real-time and was built in a Field Programmable Gate Array (FPGA) platform. The system can be used as a testbed to validate and evaluate the performance of a real-time SAR processing algorithms/system prior to the actual flight mission. This could help in reducing the frequency of flight trials and to reduce the SAR system development risk especially for satellite-borne SAR system.

Section: Hardware Implementation On Fpga Platformmentioning

confidence: 99%

“…Conventional radar systems digitize the echoes, record and store them in a digital storage media [4]. The data is then retrieved and processed "off-line" for SAR image formation using dedicated signal processing algorithms such as Range Doppler algorithm, Omega-K algorithm, and Chirp Scaling algorithm [5].…”

Section: Introductionmentioning

confidence: 99%

An FPGA based Real-Time Multi-Target Synthetic Aperture Radar Echoes Synthesizer

Yam

Lim

et al. 2020

JETAP

“…Navigation experiments were conducted to compare and analyse the performance of both systems offline. The developed navigation system will eventually be incorporated into an Unmanned Aerial Vehicle Synthetic Aperture Radar (UAVSAR) [12] system to measure the UAVʹs motion in order to achieve motion compensation in SAR signal processing [13].…”

Section: Introductionmentioning

confidence: 99%

Design and Development of a Real-Time GPS-Aided SINU System

Lim

International Journal of Advanced Robotic Systems

2012

Self Cite

A Strapdown Inertial Navigation Unit (SINU) is a low cost motion measurement device commonly used for navigation solutions. Global Positioning System (GPS) is usually adopted as an external reference source to minimize the SINUʹs accumulation errors by applying a Kalman filter to obtain best estimations in positions, velocities and orientations. However, due to the low sampling rate of GPS, such a configuration does not provide intensive orientation estimation. In this paper, a new and efficient real-time GPSaided SINU system with incorporated magnetometers is developed to enhance the orientation estimation. An intensive orientation estimation algorithm is developed by combining the extra sensory inputs from magnetometers with the inputs from accelerometers. The estimated orientation was applied in the Kalman filtering, replacing the GPS-aided orientation estimation. The offline implementation shows promising results in reducing both the accelerometersʹ and gyroscopesʹ errors. Finally, the design is successfully implemented in real-time.

A PC-based orientation sensing using 9-DOF strapdown inertial measurement unit

Hun

Sze

2012 12th International Conference on Control Automation Robotics &Amp; Vision (ICARCV)

2012

This paper presents the design and development of a PC-based orientation sensing system using strapdown inertial measurement unit (SIMU). A 9-DOF (degree of freedom) SIMU, which consists of 3-DOF gyroscopes, 3-DOF accelerometers, and 3-DOF magnetometers, are used to estimate the orientation. Data fusion is performed to improve measurement accuracy. In this paper, the orientation measurements are compared and discussed using three different approaches, known as the conventional accelerometer/gyroscope approach, the Kalman filter based 9-DOF SIMU approach, and the gradient decent algorithm based 9-DOF SIMU approach. The derivation of each approach together with the design of the PC-based orientation sensing system is outlined in this paper.