Firooz A. Sadjadi

Hypotheses Testing in a Distributed Environment

The problem of optimum detection with n decentralized sensors selecting among m possible signals is considered from the decision theory point of view. The loss function is defined in terms of the decisions made by each observer and the transmitted signal. Then the average of this loss function is minimized. This leads to sets of coupled inequalities in terms of the likelihood ratio of each observer and the decisions made at the other sensors. This determines the structure of the optimum decentralized detection for an arbitrary number of sensors and an arbitrary number of possible signals. These results are valuable in numerous situations that may arise in large-scale and distributed systems.

Radar synthetic vision system for adverse weather aircraft landing

A synthetic vision system (SVS) is described for aid in landing aircraft in poor weather conditions. The system consists of a scanning millimeter wave radar, heads-up display and real-time signal processing hardware. A suite of fast image processing algorithms are used for enhancing and displaying of the imagery. The system has been tested in number of tower and flight demonstration during actual adverse weather conditions. The significance of the work is in both system demonstration of the overall concept and the novelty of its signal processing algorithms.

Automatic object recognition: critical issues and current approaches

Automatic object recognition, with its diverse applications in numerous fields of science and technology, is permeating many aspects of military and civilian industries. This paper gives an overview of the issues confronting the automatic object recognition field and the approaches being used to address these issues.

Experimental design methodology: the scientific tool for performance evaluation

With the rapid growth of the signal and image processing technology in the last several decades has arisen the need for means of evaluating and comparing the numerous algorithms and systems that are created or are being developed. Performance evaluation, in the past, has been mostly ad hoc and incohesive. In this paper we present a systematic step by step approach for the scientific evaluation of signal and image processing algorithms and systems. This approach is based on the methodology of Experimental Design. We illustrate this method by means of an example from the field of automatic object recognition.

Automatic Target Recognition Algorithm Performance Evaluation: The Bottleneck In The Development Life Cycle

A current critical problem in Automatic Target Recognition (ATR) technology is the inability to effectively evaluate ATR systems performance and component algorithms. Beyond the problem of evaluating system performance, it is often impossible to determine why a system is performing poorly under certain circumstances. This is largely due to the relatively unsophisticated tools and methods currently employed to extract and analyze the vast quantities of data processed by such systems. The amount of time and effort dedicated to testing, evaluation, and refinement of complex ATR systems and their component algorithm is by far the longest stage in the life cycle of the development process. Adequate tools, techniques, standards, and groundtruthing are critically needed for effective diagnostics and evaluation of next generation ATR systems. In this paper, we present a thesis on the critical issues of ATR evaluation and potential solutions.

Enhanced vision for adverse weather aircraft landing

Landing in poor weather is a crucial problem for the air transportation system of the future. To aid the pilots for these conditions several solutions have been suggested and/or implemented including instrument landing system(ILS) and microwave landing system(MLS) that put the responsibility of the landing to a large extent in the hands of the airport facilities. These systems even though useful are not available due to their high costs except in few major metropolitan airports. This shortcoming has generated interest in providing all weather capabilities not on the landing facility but on the vehicle itself. The Synthetic Vision System Technology Demonstration sponsored by the United States Federal Aviation Administration(FAA) and the US Air Force represents an effort to respond to the above needs[1,2]. In this paper we present a summary of a typical synthetic vision system. This system consists of a scanning 35GHz radar a scanning antenna, a signal/image processor and a head up display(HUD). The pilot is presented a final perspective image of the scene sensed by the radar with associated flight guidance symbology. This systems is implemented in real time hardware and has been under going tower and flight testing under a variety of weather conditions since early 1992.

Automatic recognition of partially occluded objects

Machine recognition of partially occluded objects is essential for any realistic automatic object recognition (AOR) system. This important problem however, has been mostly ignored by the researchers and developers of AOR systems. Due to this lack of attention very little work is done even in the formulation of the problem and much less for its solution. In this paper I attempt to analyze the occlusion problem, define its various categories, and to present an approach for its solution in some of these categories. I also present some of the empirical results of the implementation of the approach on real imagery. These results have been very encouraging so far. However, more work is definitely needed to be done for the resolution of this problem.

Performance evaluation of a texture-based segmentation algorithm

Texture segmentations are crucial components of many remote sensing, scene analysis, and object recognition systems. However, very little attention has been paid to the problem of performance evaluation in the numerous algorithms that have been proposed by the image understanding community. In this paper, a particular algorithm is introduced and its performance is evaluated in a systematic manner on a wide range of scene and scenarios. Both the algorithm and the methodology used in its evaluation have significance in numerous applications in the computer-based image understanding field.

A model based technique for recognizing targets by using millimeter wave radar signatures

A technique for recognizing real targets by millimeter wave (MMW) radar at 35 GHz and 94 GHz is presented. The recognition is performed by a model based technique in which real targets are represented by their high range resolution (HRR) profiles in hierarchical fashion.The unknown signal is classified by a model matching method and a coarse-fine searching technique. The advantages of this model based method are in low storage capacity, fast processing time and high recognition performance. Moreover this technique is very easily modifiable to incorporate multi sensor processing.We will present the results of the several experiments that we have conducted.

Guest Editorial: Automatic Target Recognition

This PDF file contains the editorial “Guest Editorial: Automatic Target Recognition” for OE Vol. 31 Issue 12