Engineering topics
Towfic, Zaid J.
Publications and source records attributed to Towfic, Zaid J..
Flood Mapping Using UAVSAR and Convolutional Neural Networks
We have mapped flooded areas in data collected by the NASA/JPL Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) using two convolutional neural network (CNN) image classifier architectures: U-Net and SegNet. Our study area was a region around Houston, TX, USA affected by widespread flooding in 2017 due to Hurricane Harvey. To train and test the classifiers, we manually labelled over 10000 image segments in two flight lines. Both U-Net and SegNet yielded higher accuracy than a previous non-machine learning classifier we used as a baseline. U-Net had slightly higher accuracy than SegNet. The classifiers performed better in areas with more homogeneous land cover. To independently validate the classifier accuracy we used NOAA aerial imagery, with overall accuracy around 80%. Future work includes assessing the classifier robustness in other study areas, assessing the classifier dependence on UAVSAR incidence angle, particularly for open water and bare ground, and collecting more training data, particularly in urban areas. This study demonstrates the potential of CNN image classifiers for mapping flooded areas in airborne polarimetric SAR imagery, and for land cover classification of polarimetric SAR imagery more generally.
X-band PN Delta DOR Signal Design and Implementation on the JPL Iris Transponder
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Simulation and analysis of opportunistic MSPA for multiple Cubesat deployments
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Simulation and Analysis of Opportunistic MSPA for Multiple Cubesat Deployments
We describe a software approach for simultaneous demodulation and decoding of multiple frequency- multiplexed spacecraft across multiple ground stations. The approach involves the use of a single ground antenna with wide enough aperture to receive multiple angularly adjacent spacecraft simultaneously. This technique uses a wide-band RF signal digitizer coupled with easily and cheaply duplicated software-receiver modules to independently process the frequency-channelized downlink signals from the spacecraft. This approach relaxes the need for realizable modems at each antenna, for example in the Deep-SpaceNetwork (DSN), and can also function as a delayed data retrieval method for cubesat missions with routine science data return. Thus, we hope that this solution can enable more efficient utilization of DSN assets. We concentrate on a simulation similar to the proposed Exploration Mission 1 (EM-1) mission from a geometric perspective. To that end, the simulated scenario involves ten secondary cubesats deployed and tracked for a span of four days (the modeled motion over the first four days of the mission does not include any Trajectory Correction Maneuvers (TCMs) that may be necessary as the cubesats approach the moon). Transmissions from the cubesats may be received through a combination of DSN ground sites based on visibility. The cubesats are assumed to utilize typical cubesat transmit powers and a waveform similar to that of the Iris radio. One cubesat is chosen as the “target” and is considered tracked by all ground-stations throughout the simulation (i.e., it is consistently at the center of the main lobe of each ground station antenna when the ground station is in view of the cubesat in terms of elevation angle). The simulation effort involves synthesizing a wideband signal that includes the ten cubesats across a large bandwidth due to each cubesat having its own center-frequency in X-band, near 8.4 GHz. Each signal is characterized by its own Doppler-frequency shift and free-space path-loss computed through the underlying geometry of the simulation as well as the cubesat transmit power. Finally, each cubesat signal experiences a unique antenna gain at each ground station due to the underlying antenna pattern and spacecraft-ground station geometry. We establish two interesting findings: First, the link-budget for the EM-1-like scenario is almost completely limited by the angle between the center of the antenna main beam and the cubesat, which means that the signal-to-noise ratio is wholly adequate for demodulation and decoding at the simulated bitrates unless the cubesat exits the main beam. Secondly, and fortunately due to the use of a software radio architecture, we show that it is possible to successfully receive signals from most cubesats for the entire 4-day simulation. Due to the signal-to-noise ratio being sufficient for demodulation even after the side-lobe’s 17dB reduction in SNR, the software radio can still demodulate such cubesats as long as the radio is capable of re-establishing carrier lock as the cubesats leave the main beam and enter the side-lobe. Considering that the target application utilizes offline processing, a loss of lock can be detected and lock can be re-established by iterating over the data. Extensive simulations demonstrate these results.