Matching Items (3)
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- All Subjects: Systems science
- All Subjects: Target Tracking
- Creators: Bliss, Daniel
Description
In recent years, there has been an increased interest in sharing available bandwidth to avoid spectrum congestion. With an ever-increasing number wireless users, it is critical to develop signal processing based spectrum sharing algorithms to achieve cooperative use of the allocated spectrum among multiple systems in order to reduce interference between systems. This work studies the radar and communications systems coexistence problem using two main approaches. The first approach develops methodologies to increase radar target tracking performance under low signal-to-interference-plus-noise ratio (SINR) conditions due to the coexistence of strong communications interference. The second approach jointly optimizes the performance of both systems by co-designing a common transmit waveform.
When concentrating on improving radar tracking performance, a pulsed radar that is tracking a single target coexisting with high powered communications interference is considered. Although the Cramer-Rao lower bound (CRLB) on the covariance of an unbiased estimator of deterministic parameters provides a bound on the estimation mean squared error (MSE), there exists an SINR threshold at which estimator covariance rapidly deviates from the CRLB. After demonstrating that different radar waveforms experience different estimation SINR thresholds using the Barankin bound (BB), a new radar waveform design method is proposed based on predicting the waveform-dependent BB SINR threshold under low SINR operating conditions.
A novel method of predicting the SINR threshold value for maximum likelihood estimation (MLE) is proposed. A relationship is shown to exist between the formulation of the BB kernel and the probability of selecting sidelobes for the MLE. This relationship is demonstrated as an accurate means of threshold prediction for the radar target parameter estimation of frequency, time-delay and angle-of-arrival.
For the co-design radar and communications system problem, the use of a common transmit waveform for a pulse-Doppler radar and a multiuser communications system is proposed. The signaling scheme for each system is selected from a class of waveforms with nonlinear phase function by optimizing the waveform parameters to minimize interference between the two systems and interference among communications users. Using multi-objective optimization, a trade-off in system performance is demonstrated when selecting waveforms that minimize both system interference and tracking MSE.
When concentrating on improving radar tracking performance, a pulsed radar that is tracking a single target coexisting with high powered communications interference is considered. Although the Cramer-Rao lower bound (CRLB) on the covariance of an unbiased estimator of deterministic parameters provides a bound on the estimation mean squared error (MSE), there exists an SINR threshold at which estimator covariance rapidly deviates from the CRLB. After demonstrating that different radar waveforms experience different estimation SINR thresholds using the Barankin bound (BB), a new radar waveform design method is proposed based on predicting the waveform-dependent BB SINR threshold under low SINR operating conditions.
A novel method of predicting the SINR threshold value for maximum likelihood estimation (MLE) is proposed. A relationship is shown to exist between the formulation of the BB kernel and the probability of selecting sidelobes for the MLE. This relationship is demonstrated as an accurate means of threshold prediction for the radar target parameter estimation of frequency, time-delay and angle-of-arrival.
For the co-design radar and communications system problem, the use of a common transmit waveform for a pulse-Doppler radar and a multiuser communications system is proposed. The signaling scheme for each system is selected from a class of waveforms with nonlinear phase function by optimizing the waveform parameters to minimize interference between the two systems and interference among communications users. Using multi-objective optimization, a trade-off in system performance is demonstrated when selecting waveforms that minimize both system interference and tracking MSE.
ContributorsKota, John S (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Berisha, Visar (Committee member) / Bliss, Daniel (Committee member) / Kovvali, Narayan (Committee member) / Arizona State University (Publisher)
Created2016
Description
The radar performance of detecting a target and estimating its parameters can deteriorate rapidly in the presence of high clutter. This is because radar measurements due to clutter returns can be falsely detected as if originating from the actual target. Various data association methods and multiple hypothesis filtering approaches have been considered to solve this problem. Such methods, however, can be computationally intensive for real time radar processing. This work proposes a new approach that is based on the unsupervised clustering of target and clutter detections before target tracking using particle filtering. In particular, Gaussian mixture modeling is first used to separate detections into two Gaussian distinct mixtures. Using eigenvector analysis, the eccentricity of the covariance matrices of the Gaussian mixtures are computed and compared to threshold values that are obtained a priori. The thresholding allows only target detections to be used for target tracking. Simulations demonstrate the performance of the new algorithm and compare it with using k-means for clustering instead of Gaussian mixture modeling.
ContributorsFreeman, Matthew Gregory (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Bliss, Daniel (Thesis advisor) / Chakrabarti, Chaitali (Committee member) / Arizona State University (Publisher)
Created2016
Description
The power of science lies in its ability to infer and predict the
existence of objects from which no direct information can be obtained
experimentally or observationally. A well known example is to
ascertain the existence of black holes of various masses in different
parts of the universe from indirect evidence, such as X-ray emissions.
In the field of complex networks, the problem of detecting
hidden nodes can be stated, as follows. Consider a network whose
topology is completely unknown but whose nodes consist of two types:
one accessible and another inaccessible from the outside world. The
accessible nodes can be observed or monitored, and it is assumed that time
series are available from each node in this group. The inaccessible
nodes are shielded from the outside and they are essentially
``hidden.'' The question is, based solely on the
available time series from the accessible nodes, can the existence and
locations of the hidden nodes be inferred? A completely data-driven,
compressive-sensing based method is developed to address this issue by utilizing
complex weighted networks of nonlinear oscillators, evolutionary game
and geospatial networks.
Both microbes and multicellular organisms actively regulate their cell
fate determination to cope with changing environments or to ensure
proper development. Here, the synthetic biology approaches are used to
engineer bistable gene networks to demonstrate that stochastic and
permanent cell fate determination can be achieved through initializing
gene regulatory networks (GRNs) at the boundary between dynamic
attractors. This is experimentally realized by linking a synthetic GRN
to a natural output of galactose metabolism regulation in yeast.
Combining mathematical modeling and flow cytometry, the
engineered systems are shown to be bistable and that inherent gene expression
stochasticity does not induce spontaneous state transitioning at
steady state. By interfacing rationally designed synthetic
GRNs with background gene regulation mechanisms, this work
investigates intricate properties of networks that illuminate possible
regulatory mechanisms for cell differentiation and development that
can be initiated from points of instability.
existence of objects from which no direct information can be obtained
experimentally or observationally. A well known example is to
ascertain the existence of black holes of various masses in different
parts of the universe from indirect evidence, such as X-ray emissions.
In the field of complex networks, the problem of detecting
hidden nodes can be stated, as follows. Consider a network whose
topology is completely unknown but whose nodes consist of two types:
one accessible and another inaccessible from the outside world. The
accessible nodes can be observed or monitored, and it is assumed that time
series are available from each node in this group. The inaccessible
nodes are shielded from the outside and they are essentially
``hidden.'' The question is, based solely on the
available time series from the accessible nodes, can the existence and
locations of the hidden nodes be inferred? A completely data-driven,
compressive-sensing based method is developed to address this issue by utilizing
complex weighted networks of nonlinear oscillators, evolutionary game
and geospatial networks.
Both microbes and multicellular organisms actively regulate their cell
fate determination to cope with changing environments or to ensure
proper development. Here, the synthetic biology approaches are used to
engineer bistable gene networks to demonstrate that stochastic and
permanent cell fate determination can be achieved through initializing
gene regulatory networks (GRNs) at the boundary between dynamic
attractors. This is experimentally realized by linking a synthetic GRN
to a natural output of galactose metabolism regulation in yeast.
Combining mathematical modeling and flow cytometry, the
engineered systems are shown to be bistable and that inherent gene expression
stochasticity does not induce spontaneous state transitioning at
steady state. By interfacing rationally designed synthetic
GRNs with background gene regulation mechanisms, this work
investigates intricate properties of networks that illuminate possible
regulatory mechanisms for cell differentiation and development that
can be initiated from points of instability.
ContributorsSu, Ri-Qi (Author) / Lai, Ying-Cheng (Thesis advisor) / Wang, Xiao (Thesis advisor) / Bliss, Daniel (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Arizona State University (Publisher)
Created2015