Segregated FLS Processing Cores for V/STOL Autonomous Landing Guidance Assistant System Using FPGA

Abstract

To keep up with today's dense metropolitan areas and their accompanying traffic problems, a growing number of towns are looking for more advanced and swift urban taxi drones. The safety parameters that must be taken into consideration may be the most important element in the widespread use of such technology. Most recent aviation mishaps have happened during the landing phase, making this a particularly important safety consideration for Vertical and/or Short Take-Off and Landing (V/STOL) drones. In this study, we focused on improving the fault tolerance of the processor architectures used by the predecessors of Autonomous Landing Guidance Assistance Systems (ALGAS), which in turn improves their decision-making capabilities. Furthermore, this is achieved by proposing a fault-tolerant processing architecture that depends on the Gamma Distribution Sliding Window Unit (GDSWU). This proposed GDSWU has been designed completely using VHDL, and the targeted FPFA was the Intel Cyclone V 5CGXFC9D6F27C7 chip. The GDSWU could operate at a maximum frequency of 369.96 MHz, as calculated by the synthesis results of the INTEL Quartus Prime program. The suggested GDSWU core only requires 20.36 mW for dynamic core and I/O power consumption.

Adaptive Prognostic Malfunction Based Processor for Autonomous Landing Guidance Assistance System Using FPGA

“…To maximize the computing performance of the proposed ALGAS4 processing core, the entire design was built from the ground up at the gate level and RTL using VHDL, with no IPs used. The results have also been verified by comparing the achieved results from the Questa Simulation tool and MATLAB, as has been explicitly discussed in previous contributions [4,5,11]. In this paper, we mainly focused on the performance of the proposed APMU and its comparison with the PMU from [5], as depicted in Table I.…”

“…Within a single ALGAS4 processing core, we have two 15-TAPS FIR filters, one systolic FLS unit, and the APMU. Most of these building blocks have been explained in previous contributions except the HSDCI, SIU, and DIC [4,5,11]. Each Mamdani-based model of the proposed FLS processing core depends on eleven fuzzy rules.…”

“…The Proposed ALGAS3 System in [5] The Proposed ALGAS2 System in [4] The Proposed ALGAS1 System in [11] FPGA…”

“…It should also be taken into consideration that the new generation of UAM drones will depend mainly on their vertical takeoff and landing (V/STOL) capability. The embedded V/STOL mechanisms must be highly effective against unexpected and likely challenges, such as inept pilots and limited and/or unexpected landing sites during emergencies due to the enormous UAM taxi drones that are expected to cover each city in the near future [4][5]. Improving the efficiency of autonomous V/STOL mechanisms will also benefit related space and military applications [6].…”

“…Thus, it will be almost impossible to afford the predicted demands for such a large number of skilled pilots to cover a certain small geographical area. Third, the intended UAM technology must account for the fact that the routing of these route(s) per trip will be dynamically allocated and adaptable depending on a range of elements and situations that may spontaneously arise [4,9,10]. These circumstances could be natural or manmade and might trigger the activation of emergency and precautionary control measures.…”