Radar surveillance systems, in both airspace and maritime domains, are facing increasing challenges in dealing with objects that cannot be detected by traditional transponder-based radar surveillance technologies. These objects, including birds, weather, Unmanned Aircraft Systems (UAS), hot balloons, are labeled as non-cooperative objects. In order to prevent ambiguity and confusion for human operators using the surveillance data non-cooperative objects are commonly treated as unwanted clutter and removed from the displayed data. However, the omitted information of non-cooperative object can be critical to aircraft safety. With new developments in technology and radar capabilities, it is possible to detect these non-cooperative objects and consider how to distribute relevant information about them to human operators throughout a system. The research goal of this thesis is to identify the human factors challenges in future radar surveillance systems where non-cooperative object information is distributed to both air traffic controllers and pilots. In order to achieve the goal, the thesis first constructed a model of surveillance information distribution in current ATC operations and a model of surveillance information distribution in the expected future operational environment. The expected future surveillance information distribution model was then carefully examined to identify potential human factors challenges in the non-cooperative object information distribution process. Two of the identified challenges (non-equal time delay and information level of details) were studied in depth through conducting human-in-the-loop experiments and online surveys. The results of an asynchronous information (non-equal time delay) static simulation environment experiment showed that while a delay in the non-cooperative object information would lead to observable but not statistically significant longer communication time, it does have a significant effect on number of clarification statements ??? with an increase of time delay, more clarifications were made. A survey of controller and pilot perceptions of maximum acceptable delay showed no significant differences in the average maximum acceptable delay reported by controller (20.5 seconds) and pilot (13.64 seconds) participants. Future research should consider adopting dynamic simulation environment, subject matter experts and shorter delay intervals to identify an acceptable delay threshold. The survey results also demonstrated that there are more controllers and pilots who have had encounters with UAS in their daily tasks than what was originally expected. The survey also helped identify operational information requirements and availabilities for individual UAS and challenges in sharing non-cooperative object information between controllers and pilots. These findings are quite valuable as they provide guidance on future radar surveillance systems design in supporting the effective distribution of non-cooperative object information. Future work should complete the analysis of the survey and create more dynamic environment for studying information asynchrony.

Color vision deficiency (CVD) is the inability or limited ability to recognize colors and discriminate between them. A person with this condition perceives a narrower range of colors compared to a person with a normal color vision. A growing number of researchers are striving to improve the quality of life for CVD patients. Finding cure, making rectification equipment, providing simulation tools and applying color transformation methods are among the efforts being made by researchers in this field. In this study we concentrate on recoloring digital images in such a way that users with CVD, especially dichromats, perceive more details from the recolored images compared to the original image. The main focus is to give the CVD user a chance to find information within the picture which they could not perceive before. However, this transformed image might look strange or unnatural to users with normal color vision. During this color transformation process, the goal is to keep the overall contrast of the image constant while adjusting the colors that might cause confusion for the CVD user. First, each pixel in the RGB-image is converted to HSV color space in order to be able to control hue, saturation and intensity for each pixel and then safe and problematic hue ranges need to be found. The method for recognizing these ranges was inspired by a condition called “unilateral dichromacy” in which the patient has normal color vision in one eye and dichromacy in another. A special grid-like color card is designed, having constant saturation and intensity over the entire image, while the hue smoothly changes from one block to another to cover the entire hue range. The next step is to simulate the way this color card is perceived by a dichromatic user and finally to find the colors that are perceived identically from two images and the ones that differ too much. This part makes our method highly customizable and we can apply it to other types of CVD, even personalize it for the color vision of a specific observer. The resulting problematic colors need to be dealt with by shifting the hue or saturation based on some pre-defined rules. The results for the method have been evaluated both objectively and subjectively. First, we simulated a set of images as they would be perceived by a dichromat and compared them with simulated view of our transformed images. The results clearly show that our recolored images can eliminate a lot of confusion from user and convey more details. Moreover, an online questionnaire was created and 39 users with CVD confirmed that the transformed images allow them to perceive more information compared to the original images.