A NEW CONICAL-TRAJECTORY POLAR FORMAT ALGORITHM FOR SPOTLIGHT BISTATIC SAR

Abstract-The Polar Format Algorithm (PFA) is suitable for spotlight synthetic aperture radar (SAR) image focusing either in monostatic or bistatic cases. The classic linear-trajectory PFA complete data correction in wavenumber domain, converting data from the polar format to the rectangular format. However, the twodimension processing (either using interpolation or chirp-z transform) introduces heavy computational load, which limits its real-time applications. This study presents a conical-trajectory PFA for bistatic SAR, in which the transmitter and receiver are designed to fly on conical surfaces, to simplify image formation procedures via eliminating the necessity of range processing. Moreover, the conicaltrajectory PFA provides a space-invariant range resolution to simplify the SAR image comprehension. A spotlight forward-looking bistatic missile guidance application was simulated for the algorithm validation and performance analysis

A Study in GPS-Denied Navigation Using Synthetic Aperture Radar

In modern navigation systems, GPS is vital to accurately piloting a vehicle. This is especially true in autonomous vehicles, such as UAVs, which have no pilot. Unfortunately, GPS signals can be easily jammed or spoofed. For example, canyons and urban cities create an environment where the sky is obstructed and make GPS signals unreliable. Additionally, hostile individuals can transmit personal signals intended to block or spoof GPS signals. In these situations, it is important to find a means of navigation that doesn’t rely on GPS. Navigating without GPS means that other types of sensors or instruments must be used to replace the information lost from GPS. Some examples of additional sensors include cameras, altimeters, magnetometers, and radar. The work presented in this thesis shows how radar can be used to navigate without GPS. Specifically, synthetic aperture radar (SAR) is used, which is a method of processing radar data to form images of a landscape similar to images captured using a camera. SAR presents its own unique set of benefits and challenges. One major benefit of SAR is that it can produce images of an area even at night or through cloud cover. Additionally, SAR can image a wide swath of land at an angle that would be difficult for a camera to achieve. However, SAR is more computationally complex than other imaging sensors. Image quality is also highly dependent on the quality of navigation information available. In general, SAR requires that good navigation data be had in order to form SAR images. The research here explores the reverse problem where SAR images are formed without good navigation data and then good navigation data is inferred from the images. This thesis performs feasibility studies and real data implementations that show how SAR can be used in navigation without the presence of GPS. Derivations and background materials are provided. Validation methods and additional discussions are provided on the results of each portion of research