Nonlinear Suppression of Range Ambiguity in Pulse Doppler Radar

Coherent pulse train processing is most commonly used in airborne pulse Doppler radar, achieving adequate transmitter/receiver isolation and excellent resolution properties while inherently inducing ambiguities in Doppler and range. First introduced by Palermo in 1962 using two conjugate LFM pulses, the primary nonlinear suppression objective involves reducing range ambiguity, given the waveform is nominally unambiguous in Doppler, by using interpulse and intrapulse coding (pulse compression) to discriminate received ambiguous pulse responses. By introducing a nonlinear operation on compressed (undesired) pulse responses within individual channels, ambiguous energy levels are reduced in channel outputs. This research expands the NLS concept using discrete coding and processing. A general theory is developed showing how NLS accomplishes ambiguity surface volume removal without requiring orthogonal coding. Useful NLS code sets are generated using combinatorial, simulated annealing optimization techniques - a general algorithm is developed to extended family size, code length, and number of phases (polyphase coding). An adaptive reserved code thresholding scheme is introduced to efficiently and effectively track the matched filter response of a target field over a wide dynamic range, such as normally experienced in airborne radar systems. An evaluation model for characterizing NLS clutter suppression performance is developed - NLS performance is characterized using measured clutter data with analysis indicating the proposed technique performs relatively well even when large clutter cells exist

Extended depth-of-field imaging and ranging in a snapshot

Traditional approaches to imaging require that an increase in depth of field is associated with a reduction in numerical aperture, and hence with a reduction in resolution and optical throughput. In their seminal work, Dowski and Cathey reported how the asymmetric point-spread function generated by a cubic-phase aberration encodes the detected image such that digital recovery can yield images with an extended depth of field without sacrificing resolution [Appl. Opt. 34, 1859 (1995)]. Unfortunately recovered images are generally visibly degraded by artifacts arising from subtle variations in point-spread functions with defocus. We report a technique that involves determination of the spatially variant translation of image components that accompanies defocus to enable determination of spatially variant defocus. This in turn enables recovery of artifact-free, extended depth-of-field images together with a two-dimensional defocus and range map of the imaged scene. We demonstrate the technique for high-quality macroscopic and microscopic imaging of scenes presenting an extended defocus of up to two waves, and for generation of defocus maps with an uncertainty of 0.036 waves

An Analysis of Mutually Dispersive Brown Symbols for Non-Linear Ambiguity Suppression

This thesis significantly advances research towards the implementation of optimal Non-linear Ambiguity Suppression (NLS) waveforms by analyzing the Brown theorem. The Brown theorem is reintroduced with the use of simplified linear algebraic notation. A methodology for Brown symbol design and digitization is provided, and the concept of dispersive gain is introduced. Numerical methods are utilized to design, synthesize, and analyze Brown symbol performance. The theoretical performance in compression and dispersion of Brown symbols is demonstrated and is shown to exhibit significant improvement compared to discrete codes. As a result of this research a process is derived for the design of optimal mutually dispersive symbols for any sized family. In other words, the limitations imposed by conjugate LFM are overcome using NLS waveforms that provide an effective-fold increase in radar unambiguous range. This research effort has taken a theorem from its infancy, validated it analytically, simplified it algebraically, tested it for realizability, and now provides a means for the synthesis and digitization of pulse coded waveforms that generate an N-fold increase in radar effective unambiguous range. Peripherally, this effort has motivated many avenues of future research

Evaluation of coding scheme for MIMO radar

Multiple Input Multiple Output (MIMO) antenna systems have shown a great potential for wireless communication. These systems support high capacity, increased diversity and interference suppression. Recently it has been proposed MIMO constellations for Radar. MIMO Radar is not only a new research field, but also a very promising approach in terms of overcoming Radar Cross Section (RCS) fluctuations with diversity. This thesis explores the potential of coding schemes for MIMO Radar. The ambiguity functions measures related to MIMO Radar are used to evaluate how much diversity gain can be coherently achieved with certain coding schemes. The results of this analysis show that the cross correlation between the signals from different transmitters hinders achieving the full diversity gain. The code length of the used Gold codes is an important factor for this effect. However, in this thesis a coding scheme related to the Alamouti scheme in Communication is presented, this scheme under some constraints is capable of maintaining orthogonality between the signals from different transmitters and therefore cancels the mutual interference among those signals. In general, MIMO radar is a novel and ingenious approach to improve radar performance which needs to be analyzed and developed. This thesis is the first work exploring the coding schemes and the related aspects for MIMO Radar

Neural Models of Motion Integration, Segmentation, and Probablistic Decision-Making

When brain mechanism carry out motion integration and segmentation processes that compute unambiguous global motion percepts from ambiguous local motion signals? Consider, for example, a deer running at variable speeds behind forest cover. The forest cover is an occluder that creates apertures through which fragments of the deer's motion signals are intermittently experienced. The brain coherently groups these fragments into a trackable percept of the deer in its trajectory. Form and motion processes are needed to accomplish this using feedforward and feedback interactions both within and across cortical processing streams. All the cortical areas V1, V2, MT, and MST are involved in these interactions. Figure-ground processes in the form stream through V2, such as the seperation of occluding boundaries of the forest cover from the boundaries of the deer, select the motion signals which determine global object motion percepts in the motion stream through MT. Sparse, but unambiguous, feauture tracking signals are amplified before they propogate across position and are intergrated with far more numerous ambiguous motion signals. Figure-ground and integration processes together determine the global percept. A neural model predicts the processing stages that embody these form and motion interactions. Model concepts and data are summarized about motion grouping across apertures in response to a wide variety of displays, and probabilistic decision making in parietal cortex in response to random dot displays.National Science Foundation (SBE-0354378); Office of Naval Research (N00014-01-1-0624

Principles and applications of wavefront coding

Abstract unavailable please refer to PD

Development of Variable Slope Piecewise-Based Brown Symbols for Application to Nonlinear Ambiguity Suppression

In 1962, Palermo used two conjugate Linear Frequency Modulated (LFM) pulses to demonstrate a Non-linear Ambiguity Suppression (NLAS) technique to reduce ambiguous energy in radar returns. Using conjugate LFM pulse coding does not readily extend to larger symbol families and thus is severely limited for M-channel (M\u3e 2) NLAS applications. Larger families of optimal mutually dispersible codes with bigger time bandwidth products are needed to achieve the desired M-fold range ambiguity reduction. Using correlation function the time duration as an optimization metric, the recently proposed Brown\u27s theorem formulates a deterministic process for designing optimal mutually dispersible symbol sets of arbitrary size. The rms time duration performance of digitized Brown symbols is invariant to choice of basis (phase-rate) functions used in the design process, yet improvement in cross-correlation side lobe performance is directly linked to basis function design. This insight provided the impetus for designing and synthesizing a new set of mutually dispersible symbols based on Variable Slope (VS) piecewise basis functions. The resultant VS piecewise-based Brown symbols are used with NLAS processing to demonstrate M-fold ambiguity suppression capability. Despite the presence of two undesired ambiguous signal responses having +24.0 dB more signal power relative to the weaker desired unambiguous signal, the NLAS processor effectively suppressed the ambiguous responses. The desired signal peak NLAS output response was approximately 11.0 dB above the noise floor and undesired ambiguous responses were suppressed an average of 10.0 to 12.0 dB - a net improvement of approximately 21.01 to 22.0 dB