This paper presents a geometric extension to the well known Empirical Line Method (ELM) for atmospheric compensation, enabling improved results through the use of 3D scene geometry. Typically, this geometry is assumed to be known, either through direct measurement or analysis of other imagery such as lidar or photogrammetric products. However, when the scene geometry is unknown and only spectral information is available, in certain cases estimates of the surface orientation may be obtained directly from image brightness values. In this paper we derive a means to determine surface orientation estimates from a pair of brightness images, and then use this geometric information to improve the ELM solution.

Methods for generating accurate building models from lidar data have received considerable attention in the recent literature. Many of the proposed techniques examine the data to define dominant planes in the structure, then intersect these planes to determine the location of internal edges and vertices. However, since most airborne lidar datasets are collected from near-nadir orientations, there are usually very few data points that lie on vertical surfaces. As such, it is usually difficult to determine the planes corresponding to exterior walls using data points on these walls. However, if we assume that exterior walls are oriented directly under the outer boundary of the roof structure, we may identify the geometry of these walls by modeling the 2D shape of the building exterior. This paper presents a robust approach for extracting this exterior boundary directly from the lidar data.

The visually-realistic yet radiometrically-accurate simulation of long-wave infrared (LWIR) imagery is a problem that has plagued members of industry and academia alike. Simulating texture in LWIR imagery is a more complex task due to temperature variation which is a function of solar absorptivity, surface orientation, shadowing and bulk thermal properties. In order to deal with these additional sources of variability, we have improved the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model to allow the use of thermal property texture maps to control various thermal properties. This paper presents these methods and applies them in order to simulate LWIR imagery taken over natural desert scenes in Trona, CA. The resulting imagery demonstrates that these new methodologies for modeling thermodynamic phenomena and the utilization of an enhanced DIRSIG tool improve the average root mean-squared error (RMSE) of our synthetic LWIR imagery by up to 88%.

A new method is introduced for interference excision in spread-spectrum communications that is conducive to software-radio applications. Spare processing capacity in the receiver permits the use of time-frequency techniques to synthesize a nonstationary interference from the time-frequency domain using least squares methods. The synthesized signal is then subtracted from the incoming data in the time domain, leading to jammer removal and increased signal-to-interference-and-noise ratio at the input of the correlator. The paper focuses on jammers with constant modulus that are uniquely described by their instantaneous frequency characteristics. With this a priori knowledge, the jammer signal amplitude is restored by projecting each sample of the synthesized signal to a circle representing its constant modulus. With the phase matching provided by the least squares synthesis method and amplitude matching underlying the projection operation, a significant improvement in receiver performance/bit-error rates is achieved over the case where no projection is performed. Software-radio aspects including computational complexity and processing modes are also discussed.

A new method is introduced for interference excision in spread spectrum communications. Time-frequency synthesis techniques are used to synthesize the nonstationary jammer from the time-frequency domain using least-squares methods. The synthesized jammer is then subtracted from the incoming data in the time domain, leading to increased signal to interference ratio at the input of the correlator. The paper focuses on jammers with constant modulus where the jamming signal is a polynomial phase. With this a priori knowledge, the jammer signal amplitude is restored by projecting each sample of the synthesized signal to a circle representing its constant modulus. With the phase matching provided by the least-squares synthesis method and amplitude matching underlying the projection operation, the paper shows a significant improvement in receiver performance/bit error rates over the case where no projection is performed.