Weak Signal Detection in Non-Gaussian Noise of Unknown Level

An adaptive threshold detector to test for the presence of a weak signal in additive non-Gaussian noise of unknown level is discussed. The detector consists of a locally optimum detector, a noise level estimator, and a decision device. The detection threshold is made adaptive according to the information provided by the noise level estimator in order to keep a fixed false-alarm probability. Asymptotic performance characteristics are obtained indicating relationships among the basic system parameters such as the reference noise sample size and the underlying noise statistics. It is shown that, as the reference noise sample size is made sufficiently large, the adaptive threshold detector attains the performance of a corresponding locally optimum detector for detecting the weak signal were the noise level known.     

The Measurement of Echo Direction in a Phased-Array Radar

For a planar-array antenna with a monopulse feed horn, this study describes a simple algorithm for the determination of the direction of target echoes. Antenna pattern measurements of the array indicate that the direction sines of a received wavefront can be independently obtained with one simple relation between a normalized difference channel output and a direction sine. This paper determines the accuracy of the algorithm.     

Nitrogen Isotopes on the Moon: Archives of the Solar and Planetary Contributions to the Inner Solar System

Space Science Reviews - The two isotopes of nitrogen, 14N and 15N, have relative abundances extremely variable among solar system reservoirs such as planets and their atmospheres, primitive and...     

Genesis on-board determination of the solar wind flow regime

Some of the objectives of the Genesis mission require the separate collection of solar wind originating in different types of solar sources. Measurements of the solar wind protons, alpha particles, and electrons are used on-board the spacecraft to determine whether the solar-wind source is most likely a coronal hole, interstream flow, or a coronal mass ejection. A simple fuzzy logic scheme operating on measurements of the proton temperature, the alpha-particle abundance, and the presence of bidirectional streaming of suprathermal electrons was developed for this purpose. Additional requirements on the algorithm include the ability to identify the passage of forward shocks, reasonable levels of hysteresis and persistence, and the ability to modify the algorithm by changes in stored constants rather than changes in the software. After a few minor adjustments, the algorithm performed well during the initial portion of the mission. This revised version was published online in August 2006 with corrections to the Cover Date.     

SWE,a comprehensive plasma instrument for the WIND spacecraft

The Solar Wind Experiment (SWE) on the WIND spacecraft is a comprehensive, integrated set of sensors which is designed to investigate outstanding problems in solar wind physics. It consists of two Faraday cup (FC) sensors; a vector electron and ion spectrometer (VEIS); a strahl sensor, which is especially configured to study the electron strahl close to the magnetic field direction; and an on-board calibration system. The energy/charge range of the Faraday cups is 150 V to 8 kV, and that of the VEIS is 7 V to 24.8 kV. The time resolution depends on the operational mode used, but can be of the order of a few seconds for 3-D measurements. Key parameters which broadly characterize the solar wind positive ion velocity distribution function will be made available rapidly from the GGS Central Data Handling Facility.     

Measurement of Distributed Targets with the Random Signal Radar

A model of a distributed target as a collection of independent, Poisson distributed point scatterers or scattering centers in a range-velocity target space is introduced and is characterized by a deterministic function called the ?scatterer density function.? This function is the density of the point scatterers in the range-velocity space and can be estimated in a relatively straightforward manner by any radar having adequate resolution in both range and velocity and no ambiguities in the region occupied by the distributed target. The use of the random signal radar with a correlator receiver is considered here and the statistical properties of the correlator output, when the return signal is from a distributed target, are derived. It is shown that the spectral density is simply related to the scatterer density function. The technique is illustrated by an example in which the target is a tornado modeled as a cylinder with constant angular velocity. The example suggests that is a possible to remotely estimate the radar cross section per unit volume as a function of distance from the center of the tornado.     

Angular Accuracy of a Scanning Radar Employing a Two-Pole Filter

A two-pole filter is proposed as a detector for a scanning radar. The optimum values of the filter coefficients are found and are approximated by a simple expression. The optimum two-pole filter requires a 0.15-dB increase in signal-to-noise ratio in order to provide the same detection capability as the optimum detector, and yields azimuth estimates whose standard deviation are within 15 percent of the Cramér-Rao lower bound. The estimator is simple to implement, avoiding the storage requirements of the moving window detector and the bias complications of the feedback integrator.     

Synergism of binocular and motion stereo for passive ranging

Range measurements to objects in the world relative to mobile platforms such as ground or air vehicles are critical for visually aided navigation and obstacle detection/avoidance. An approach is presented that consists of a synergistic combination of two types of passive ranging method: binocular stereo and motion stereo. We show a new way to model the errors in binocular and motion stereo in conjunction with an inertial navigation system (INS) and derive the appropriate Kalman filter to refine the estimates from these two stereo ranging techniques. We present results using laboratory images that show that refined estimates can be optimally combined to give range values which are more accurate than any one of the individual estimates from binocular and motion stereo. By incorporating a blending filter, the approach has the potential of providing accurate, dense range measurements for all the pixels in the field of view (FOV)