Exosemiotics: an inter-disciplinary approach

Over the past several hundred years, many ideas have been expressed as to how human beings might communicate with extraterrestrials. These ideas have been put forth by experts from a diverse range of fields including physical scientists, mathematicians, behavioral scientists, philosophers and creative writers who have widely differing views on how to express ourselves coherently with civilizations from other worlds.This paper will look at some of these differing viewpoints and stress the need for an inter-disciplinary approach to the challenges of sending and, perhaps most important, receiving messages. Could we decipher a message if we got one? Who is doing the listening and what advantages could an inter-disciplinary approach bring to these efforts? What are some inter-disciplinary approaches to sending messages to extraterrestrials?     

A Detection Algorithm for Optical Targets in Clutter

There is active interest in the development of algorithms for detecting weak stationary optical and IR targets in a heavy opticalclutter background. Often only poor detectability of low signal-to-noise ratio (SNR) targets is achieved when the direct correlation method is used. In many cases, this is partly obviated by using detection with correlated reference scenes [1, 2].This paper uses the experimentally justified assumption that most optical clutter can be modeled as a whitened Gaussian randomprocess with a rapidly space-varying mean and a more slowlyvarying covariance [2]. With this assumption, a new constant falsealarm rate (CFAR) detector is developed as an application of the classical generalized maximum likelihood ratio test of Neyman and Pearson. The final CFAR test is a dimensionless ratio. This test exhibits the desirable property that its probability of a false alarm(PFA) is independent of the covariance matrix of the actual noiseencountered. When the underlying noise processes are complex intime, similar considerations can yield a sidelobe canceler CFARdetection criterion for radar and communications. Performance analyses based on the probability of detection (PD)versus signal-to-noise ratio for several given fixed false alarm probabilities are presented. Finally these performance curves are validated by computer simulations of the detection process which use real image data with artificially implanted signals.     

An Adaptive Array Signal Processing Algorithm for Communications

An algorithm is described for initial synchronization in a communication system with a digital adaptive array. This algorithm can also be used for message extraction. A set of consecutive complex video samples of the array output is processed to obtain optimum adaptive array weights, based on a least mean square (LMS) error criterion. This computation is performed for each of the possible alternative signals which may be present during an observation interval. The correct synchronization time or message symbol is selected as the one which yields the minimum LMS error. Assuming orthogonality of the alternative codes, a probability distribution for the output of this processor has been derived.     

Modeling visuospatial reasoning

I apply my proposed modification of Soar/Spatial/Visual System and Kosslyn’s (1983) computational operations on images to problems within a 2 × 2 taxonomy that classifies research according to whether the coding involves static or dynamic relations within an object or between objects (Newcombe & Shipley, 2015). I then repeat this analysis for problems that are included in mathematics and science curricula. Because many of these problems involve reasoning from diagrams Hegarty’s (2011) framework for reasoning from visual-spatial displays provides additional support for organizing this topic. Two more relevant frameworks specify reasoning at different levels of abstraction (Reed, 2016) and with different combinations of actions and objects (Reed, 2018). The article concludes with suggestions for future directions.     

A recursive moving-target-indication algorithm for optical imagesequences

A recursive track-before-detect algorithm, producing potentially large signal-to-noise ratio (SNR) gains under realizable conditions, is described. The basic relation has the form of a linear, constant-coefficient difference equation with a unity magnitude damping factor. Known as recursive moving-target-indication (RMTI), this procedure adapts easily to digital processing and achieves SNR gains comparable to those from other robust track-before-detect algorithms. Examples are given to demonstrate the performance of the moving target indicator (MTI) procedure     

The performance of KSC Fixation Tubes with RNALater for orbital experiments: A case study in ISS operations for molecular biology

Molecular biology experiments on the International Space Station (ISS) continue to face challenges of sample harvesting and sample return to earth for post flight analysis; however, the use of Kennedy Space Center Fixation Tubes filled with RNALater has proven to be a robust solution to many of these challenges. While it is clear that one direction of future spaceflight experimentation may be towards enhanced on-orbit analytical capabilities, the rapid progress of earth-bound analytical capacity dictates that facile return of molecular biology samples from the ISS will continue to be a mainstay of space life sciences research and flight operations. In this paper we present a case study of the successful performance of KFTs and RNALater over a broad set of operational conditions of ascent configuration, on-orbit experiment use, on-orbit storage and sample return configurations that are unique to ISS current operations and constraints. We also provide observations on performance limits and discuss deployment opportunities and scenarios that are consistent with continued successful ISS molecular biology experimentation.     

Optimum Processing of Unequally Spaced Radar Pulse Trains for Clutter Rejection

A train of radar pulses from one resolution cell can be processed coherently to reject echoes from external clutter and detect targets moving radially with respect to the clutter. Optimum methods of signal processing are defined for systems in which the interpulse spacings are multiply staggered to avoid target blind speeds. Likelihood ratio tests are developed for systems in which the target Doppler frequency is known a priori and for systems employing a bank of filters to cover the target Doppler band. To implement such tests, the N pulses in the train are added with complex weights and the amplitude of the sum compared with a detection threshold. The set of weights which maximizes the average signal-to-clutter ratio is also computed for a single-filter system with unknown target Doppler frequency. When the clutter autocorrelation function is exponential, the clutter covariance matrix can be inverted analytically. This latter result is useful for comparing different interpulse-spacing codes for a particular system application.     

Optical moving target detection with 3-D matched filtering

Three-dimensional (3-D) matched filtering has been suggested as a powerful processing technique for detecting weak, moving optical targets immersed in a background noise field. The procedure requires the processing of entire sequences of frames of optical scenes containing the moving targets. The 3-D processor must be properly matched to the target signature and its velocity vector, but will simultaneously detect all targets to which it is matched. The results of a study to evaluate the 3-D processor are presented. Simulation results are reported which show the ability of the processor to detect targets well below the background level. These results demonstrate the capability and robustness of the processor, and show that the algorithms, although somewhat complicated, can be implemented readily. Some effects on the number of frames processed, target flight scenarios, and velocity and signature mismatch are also presented. The ability to detect multiple targets is demonstrated     

Multistage partially adaptive STAP CFAR detection algorithm

A new method of partially adaptive constant false-alarm rate (CFAR) detection is introduced. The processor implements a novel sequence of orthogonal subspace projections to decompose the Wiener solution in terms of the cross-correlation observed at each stage. The performance is evaluated using the general framework of space-time adaptive processing (STAP) for the cases of both known and unknown covariance. It is demonstrated that this new approach to partially adaptive STAP outperforms the more complex eigen-analysis approaches using both simulated DARPA Mountain Top data and true pulse-Doppler radar data collected by the MCARM radar     

Effect of Envelope Limiting in Adaptive Array Control Loops

The properties of an adaptive array antenna, including transient response rate and control loop noise, depend on the intensity of the external noise field. This dependence can be reduced by envelope hard limiting in the control loops, without degrading the performance of the adaptive array.