Hundreds of simple target-detection algorithms were tested on mid- and long-wave forward-looking infrared images. Each algorithm is briefly described. Indications are given as to which performed well. Most of these simple algorithms are loosely derived from standard tests of the difference of two populations. For target detection, these are populations of pixel grayscale values or features derived from them. The statistical tests are implemented in the form of sliding triple window filters. Several more elaborate algorithms are also described with their relative performances noted. They utilize neural networks, deformable templates, and adaptive filtering. Algorithm design issues are broadened to cover system design issues and concepts of operation. Since target detection is such a fundamental problem, it is often used as a test case for developing technology. New technology leads to innovative approaches for attacking the problem. Eight inventive paradigms, each with deep philosophical underpinnings, are described in relation to their effect on target detector design.