We develop and evaluate receiver signal processing algorithms for the detection of signals transmitted via the forward link of a cell in a cellular system modeled after the IS-95 standard for direct-sequence spread-spectrum code-division multiple-access (CDMA) communications. Multiuser detectors on board airborne and terrestrial mobile interceptors or monitors attempt the simultaneous detection, in a single receiver, of all communication signals transmitted by the base station of interest. Due to the detrimental effects of transmitter, reciever and channel nonlinearities, very fast multipath fading, shadowing, path loss, Doppler spread, additive white Gaussian noise, and intracell and intercell multiple-access interference, the user signals are de-orthogonalized. This leads to performance degradation in conventional receivers that is too severe, especially when the powers of some of the interfering users are dominant. In order to improve upon the performance of conventional matched filter receivers, this article focuses on the development and evaluation of fast reliable successive interference canceling (SIC) algorithms. The technique we have developed can be used to relax the strict requirements on power control and to improve the capacity of CDMA systems.

In this paper, we develop optimum and suboptimum receivers for jointly detecting two cochannel continuous phase modulated (CPM) signals. These receivers are based upon Laurent's representation of binary CPM as a sum of a finite number of pulse amplitude modulated signals. We also provide a review of the Laurent representation and its application to the design of suboptimum single-channel receivers.

Most of the recent work on inhomogeneous diffusion in image filtering focuses on diffusing the isotope curve. We present a less familiar approach to the development of inhomogeneous diffusion algorithms in which the image is regarded as a surface in three-space. The magnitude of the surface normal controls a diffusion that evolves the image surface at the speed proportional to its mean curvature. A discrete algorithm to implement this proposed diffusion is introduced and we show experimentally that the algorithm develops singularities that reveal, preserve, and enhance the underlying signal. If the imput signal is an isolated noisy edge, this leads to complete noise removal and enhancement without affecting the edge locality.

Mean curvature diffusion is shown to be a position vector diffusion, tending to scalar diffusion as a flat image region is approached, and providing noise removal by steepest decent surface minimization. At edges, it swithches to a nondiffusion state due to two factors: the Laplacian of position vanishes and the magnitude of the surface normal attains a local maximum.

Representing the image as a surface, an inhomogeneous diffusion algorithm is developed, evolving the surface at a speed proportional to its mean curvature, reducing noise while preserving image structure. An adaptive scaling parameter increases the speed of the diffusion. The properties of a discrete algorithm are demonstrated experimentally

The design of linear image filters based on properties of human visual perception has been shown to require the minimization of criterion functions in both the spatial and frequency domains. In this correspondence, we extend this approach to continuous filters of infinite support. For low pass filters, this leads to the concept of an ideal low pass image filter which provides a response that is superior perceptually to that of the classical ideal low pass filter.

A receiver is developed for MAP symbol detection of a burst (i.e., finite-length)CPM signal received in additve white Gaussian noise. This minimum probability of symbol error receiver requires the entire burst of data and involves the use of both forward and backward recursions. Performance results are provided comparing the MAP symbol detector to the more commonly used ML sequence detector (i.e., the Viterbi detector) applied to GMSK signals with the smae burst structure as those employed in the GSM system. It is also shown that using only the forward recursions, the transmitted symbols can be detected in real-time (i.e., without the delay required by the ML sequence detector or the MAP symbol detector) with only slight degradation in performance.

In image processing operations involving changes in the sampling grid, preserve image structure. Structure includes regions of high contrast, such as edges, streaks, or corners, all indicated by large gradients. In this paper, we consider the use of local spatial analysis for both sampling and interpolation. Anisotropic diffusion is considered as a directional smoothing technique that preserves structure. This is used in conjunction with a method of directional interpolation, which is also based on structure analysis