Robert J. Bonneau

Bistatic radar denial/embedded communications via waveform diversity

Use of an interferometer along with a host radar is proposed for simultaneously achieving coherent reference denial and embedded communications. To prevent self-jamming, spatial orthogonality is achieved between the interferometer antenna pattern and main beam of the host radar. Costas and orthogonal frequency division multiplexing (OFDM) signals are suggested for the host radar and interferometer, respectively. The effectiveness of the interferometer masking signal on a non-cooperative bistatic radar is discussed.

A rate distortion method for waveform design in RF target detection

Conventional RF image formation relies on a fixed waveform set that is based largely on obtaining maximum resolution for a given amount of bandwidth present in a waveform. However, the correlation process for a given waveform set varies widely depending on the cross correlation properties of the waveform and the geometry of the aperture interrogating the object to be detected. We propose a method that maximizes quality of the object being detected by first using an orthogonal basis to minimize the unwanted correlation response for the waveform. We then shape the frequency and temporal correlation response of the waveform for a given target using a rate distortion criteria and demonstrate the imaging and detection performance of the method

A rate distortion method for waveform design in RF image formation

Conventional RF image formation relies on a fixed waveform set that is based largely on obtaining maximum resolution for a given amount of bandwidth present in a waveform. However, the correlation process for a given waveform set varies widely depending on the cross correlation properties of the waveform and the geometry of the aperture interrogating the object to be imaged. We propose a method that maximizes quality of the imagery being reconstructed based by first using an orthogonal basis to minimize the unwanted correlation response for the waveform. We then shape the frequency and temporal correlation response of the waveform for a given target using a rate distortion criterion and demonstrate the performance of the method

3-dimensional object reconstruction from frequency diverse RF systems

Conventional phased arrays operate on narrow bandwidth principles to achieve resolution in imaging of buildings and other objects of interest. Unfortunately, such narrow bandwidth methods to not allow sufficient resolution to reconstruct objects of interest in 3 dimensions at low frequencies and with small apertures. We propose a method that is computationally efficient and allows dynamic use of spectrum to achieve high resolution 3 dimensional reconstruction of objects from small or distributed apertures. This method also allows available spectrum bands to be used on a non-interference basis.

Imaging of moving targets using a Doppler compensated multiresolution method

Traditional radar imaging has difficulties in imaging moving targets due to Doppler shifts induced in the imagery and limited spatial resolution of the target. We propose a method that uses a multiresolution processing technique that sharpens the ambiguity function of moving objects to remove Doppler induced imaging errors and improves instantaneous resolution. This method allows for instantaneous imaging of both static an moving objects in a computationally efficient manner thereby allowing more real time radar imagery generation.

A waveform strategy for detection of targets in multiplicative clutter

Conventional radar signal processing techniques approximate multipath as a linear process. Unfortunately, such an approach results in poor detection performance and because the model for the interference does not accurately represent the physical scattering process. We instead propose a method that uses the flexibility of waveform design for a given aperture to linearize the physical scattering phenomenon. This allows us to successfully detect targets using a Wiener matched filter approach in high multipath conditions.

Sensor fusion for target detection and tracking

Multipath can be a significant contributor to poor detection performance in radar ground moving target tracking systems. Recently, ground multisensor networks have been used to detect and track targets. Unfortunately, such networks can only be deployed in a limited area compared with the coverage possible using a radar. We show how, in those areas where multipath contributes to detection errors, the ground sensor network performance can be improved. Using integrated radar and ground sensor networks significantly improves the performance of radar target detection in a multipath environment. Such improvement in performance has implications for using more varied type of sensors to support the radar with statistics that complement the radars receiver operating characteristic.

A constant probability of detection model for image quantization

A large number of remote sensing applications require that images be transmitted across a low bandwidth communication link for human analysis and automatic evaluation. To accommodate the low bandwidth link, compression is often used to reduce the amount of data transmitted. A central part of this compression process is quantization which decreases the entropy in the compressed imagery. While quantization decreases the amount of data it adds nonlinear distortion to the image. This nonlinear quantization noise can severely impair the ability of the analyst and automatic algorithm to identify features of interest in the decompressed data. We develop a wavelet Markov model based approach to detection before quantization to preserve features of interest to the analyst or automatic algorithm.

A multiresolution time domain approach to RF image formation

Conventional image formation approaches rely on frequency domain Fourier methods to create images of objects. Most rely on integrating spatial resolution in the Fourier domain and do not accurately factor in the spatial aperture function to create an image because of the uniform spatial sampling necessary for the Fourier transform. We propose a multiresolution approach based on a Greens function inverse scattering method that allows us to solve for the object function directly in the time domain thereby allowing a more accurate rendering of the object in question.

A spectral approach to image-enhanced moving target radar detection

A difficult problem with ground moving target radar (GMTI) detection is how to consistently track targets moving through non-homogeneous regions of clutter such as forest and urban boundaries. Although attempts have been made to mitigate this detection problem using terrain mapping data, such data does not give current clutter information due to change in vegetation, roads, buildings, and seasonal variation. We propose to use synthetic aperture radar (SAR) imagery to enhance the detection performance of GMTI radar. We use a multiresolution Markov model to represent both target and background clutter. This multiresolution structure allows us to accurately match GMTI clutter with the geographically registered SAR imagery for consistent moving target detection through clutter boundary areas.