Geometric aspects of long-term noncoherent integration

Long-term integration is defined as integration, perhaps interrupted, over time periods long enough for targets to move through volumes in space resolvable by the radar. Because the motion of the target is unknown prior to detection, long-term integration must be performed along multiple paths representing plausible target paths. The geometry of such a set of integration paths affects detection performance in several ways. The simplest implementation of long-term integration, using constant radial velocity paths, is investigated. The effects of path geometry on detection is quantified and optimized for a target whose motion is nearly radial but otherwise unknown     

Closed-Form Expressions for Noncoherent Radar Integration Gain and Collapsing Loss

Closed-form formulas allow rapid determination of noncoherent integration gain and integration loss when the single-sample IF signal-to-noise ratio (SNR) is known. In addition, if the required SNR is known for any number of integrated pulses, the required SNR for any other number is easily determined. A closed-form expression is given for radar collapsing loss, expressed in terms of the equivalent integrated signal-to-noise ratio required to produce a given combination of false-alarm and detection probabilities. Alternatively, the single-sample signal-to-noise ratio of a set of samples may be used together with the closed-form expression for integration gain to get the equivalent integrated signal-to-noise ratio.     

Stochastic Dynamic System Suboptimal Control with Uncertain Parameters

The control of a linear system with random coefficients is studied here. The cost function is of a quadratic form and the random coefficients are assumed to be partially observable by the controller. By means of the stochastic Bellman equation, the optimal control of stochastic dynamic models with partially observable coefficients is derived. The optimal control is shown to be a linear function of the observable states and a nonlinear function of random parameters. The theory is applied to an optimal control design of an aircraft landing in wind gust.     

Sequences and arrays with perfect periodic correlation

Properties and methods for synthesizing sequences with perfect periodic autocorrelation functions and good energy efficiency are discussed. The construction is extended to two-dimensional perfect arrays. The construction methods used are based mainly on a search in the frequency domain and on a multiplication theorem for periodic sequences and arrays     

Medium PRF radar PRF selection using evolutionary algorithms

Evolutionary algorithms are applied to the optimization of pulse repetition frequency (PRF), for both eight-and nine PRFs, in medium PRF radar while considering the detailed effects of sidelobe clutter and many other technical factors. The algorithm presented also ensures that all the solutions produced are fully decodable and have no blind velocities. The evolutionary algorithm was able to identify near-optimum PRF sets for a realistic radar system with only a modest computational effort.     

Coarse attitude determination from Earth albedo measurements

Attitude estimation algorithms for the Thrusted Vector Mission which determine attitude based on Sun sensor and very coarse albedo sensor measurements are presented. On the basis of these measurements, it has been demonstrated by comparison with more accurate gyro-based attitude that it is possible to estimate three-axis attitude with an average error per axis of 11 deg. Most of this error is about the Sun direction. Both deterministic quick-look and optimal estimates are examined