Effective SAR image creation using low cost INS/GPS

Samczyński, Piotr; Malanowski, Mateusz; Gromek, Damian; Gromek, Artur; Kulpa, Krzysztof; Krzonkalla, Jarosław; Mordzonek, Maj; Nowakowski, M.

doi:10.1109/irs.2014.6869243

Cited by 9 publications

(7 citation statements)

References 4 publications

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“…This is not as critical for frequency modulated continuous wave (FMCW) radar architectures where the system is continuously transmitting and receiving. However, the use of FMCW radar architectures for SAR imaging have their own complications such as intrapulse range migration [18].…”

Section: Sar Motion Requirementsmentioning

confidence: 99%

An Up-Sampled Particle Filter Fusion Technique and Its Application in Synthetic Aperture Radar Imaging

et al. 2022

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Global positioning system (GPS) and inertial measurement units (IMUs) are often combined to produce navigation systems for airborne imaging platforms. The current state-of-the-art radar technology allows for radars to pulse at very high rates. GPS and IMU update rates are not fast enough to accurately report the platform position for each radar pulse. Independent GPS and IMUs cannot provide positional accuracy for long term stability. Traditional techniques, such as the Kalman and particle filter, are used to fuse GPS and IMU measurements. The Kalman filter excels for linear and Gaussian systems whereas the particle filter excels at non-linear and non-Gaussian systems. Sensor fusion techniques are used to help correct for IMU errors and provide the positional accuracy required for synthetic aperture radar (SAR) imaging applications. However, SAR requires the fusion algorithms to provide faster update rates. This paper explores the use of an up-sampled particle filter (UPF) for SAR to provide highly accurate position estimates at sampling frequencies comparable to radar pulse rates and overcome the limitations of standard interpolation techniques. This up-sampled particle filter is proven through simulations and instrumentation with a NovAtel GPS and IMU. The UPF technique allows for the GPS/IMU sampling rate to be different from the radar pulse repetition frequency (PRF) while providing accurate position solutions for each radar pulse capable of compensating for the phase history required for focusing a SAR image. The algorithms are instrumented in a SAR system and the position estimates are further validated and demonstrated through captured SAR images.

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Section: Sar Motion Requirementsmentioning

confidence: 99%

An Up-Sampled Particle Filter Fusion Technique and Its Application in Synthetic Aperture Radar Imaging

et al. 2022

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“…Uncorrected deviations from the assumed trajectory exceeding 0.1 λ introduce significant phase errors and deteriorate the quality of SAR images [2]. In some authors' opinion the fully focused SAR imaging requires the positioning accuracy better than 0.25 λ [3]. The carrier frequency of the radar sensor used in our experiments is equal to 2.91 GHz, therefore λ = 0.1034 m. The above mentioned requirement poses a great challenge for the navigation system.…”

Section: Introductionmentioning

confidence: 97%

Estimation of Flight Path Deviations for SAR Radar Installed on UAV

Labowski

Kaniewski

Konatowski

2016

Metrology and Measurement Systems

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The paper presents a method of calculation of position deviations from a theoretical, nominally rectilinear trajectory for a SAR imaging system installed on board of UAV. The UAV on-board system consists of a radar sensor, an antenna system, a SAR processor and a navigation system. The main task of the navigation part is to determine the vector of differences between the theoretical and the measured trajectories of UAV center of gravity. The paper includes chosen results of experiments obtained during ground and flight tests.

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“…SAR imagery, requirements with respect to the accuracy of positioning are very high [3,4,16,17]. On the other hand, short delays in image availability are often acceptable.…”

Section: Introductionmentioning

confidence: 99%

Estimation of UAV Position with Use of Smoothing Algorithms

Kaniewski

Gil

Konatowski

2017

Metrology and Measurement Systems

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The paper presents methods of on-line and off-line estimation of UAV position on the basis of measurements from its integrated navigation system. The navigation system installed on board UAV contains an INS and a GNSS receiver. The UAV position, as well as its velocity and orientation are estimated with the use of smoothing algorithms. For off-line estimation, a fixed-interval smoothing algorithm has been applied. On-line estimation has been accomplished with the use of a fixed-lag smoothing algorithm. The paper includes chosen results of simulations demonstrating improvements of accuracy of UAV position estimation with the use of smoothing algorithms in comparison with the use of a Kalman filter.

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Effective SAR image creation using low cost INS/GPS

Cited by 9 publications

References 4 publications

An Up-Sampled Particle Filter Fusion Technique and Its Application in Synthetic Aperture Radar Imaging

An Up-Sampled Particle Filter Fusion Technique and Its Application in Synthetic Aperture Radar Imaging

Estimation of Flight Path Deviations for SAR Radar Installed on UAV

Estimation of UAV Position with Use of Smoothing Algorithms

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