21 research outputs found
The Bi-directional Spatial Spectrum for MIMO Radar and Its Applications
<p>Radar systems have long applied electronically-steered phased arrays to discriminate returns in azimuth angle and elevation angle. On receiver arrays, beamforming is performed after reception of the data, allowing for many adaptive array processing algorithms to be employed. However, on transmitter arrays, up until recently pre-determined phase shifts had to applied to each transmitter element before transmission, precluding adaptive transmit array processing schemes. Recent advances in multiple-input multiple-output radar techniques have allowed for transmitter channels to separated after data reception, allowing for virtual non-causal "after-the-fact" transmit beamforming. The ability to discriminate in both direction-of-arrival and direction-of-departure allows for the novel ability to discriminate line-of-sight returns from multipath returns. This works extends the concept of virtual non-causal transmit beamforming to the broader concept of a bi-directional spatial spectrum, and describes application of such a spectrum to applications such as spread-Doppler multipath clutter mitigation in ground-vehicle radar, and calibration of a receiver array of a MIMO system with ground clutter only. Additionally, for this work, a low-power MIMO radar testbed was developed for lab testing of MIMO radar concepts.</p>Dissertatio
Constant Modulus Waveform Estimation and Interference Suppression via Two-stage Fractional Program-based Beamforming
In radar and communication systems, there exist a large class of signals with constant modulus property, including BPSK, QPSK, LFM, and phase-coded signals. In this paper, we focus on the problem of joint constant modulus waveform estimation and interference suppression from signals received at an antenna array. Instead of seeking a compromise between interference suppression and output noise power reduction by the Capon method or utilizing the interference direction (ID) prior to place perfect nulls at the IDs and subsequently minimize output noise power by the linearly constrained minimum variance (LCMV) beamformer, we devise a novel power ratio criterion, namely, interference-plus-noise-to-noise ratio (INNR) in the beamformer output to attain perfect interference nulling and minimal output noise power as in LCMV yet under the unknown ID case. A two-stage fractional program-based method is developed to jointly suppress the interferences and estimate the constant modulus waveform. In the first stage, we formulate an optimization model with a fractional objective function to minimize the INNR. Then, in the second stage, another fraction-constrained optimization problem is established to refine the weight vector from the solution space constrained by the INNR bound, to achieve approximately perfect nulls and minimum output noise power. Moreover, the solution is further extended to tackle the case with steering vector errors. Numerical results demonstrate the excellent performance of our methods
Physically constrained maximum likelihood (PCML) mode filtering and its application as a pre-processing method for underwater acoustic communication
Submitted in partial fulfillment of the requirements for the degree of Master of Science at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2009Mode filtering is most commonly implemented using the sampled mode shape or
pseudoinverse algorithms. Buck et al placed these techniques in the context of
a broader maximum a posteriori (MAP) framework. However, the MAP algorithm
requires that the signal and noise statistics be known a priori. Adaptive array processing algorithms are candidates for improving performance without the need for a
priori signal and noise statistics. A variant of the physically constrained, maximum
likelihood (PCML) algorithm is developed for mode filtering that achieves the
same performance as the MAP mode filter yet does not need a priori knowledge of
the signal and noise statistics. The central innovation of this adaptive mode filter is
that the received signal's sample covariance matrix, as estimated by the algorithm,
is constrained to be that which can be physically realized given a modal propagation
model and an appropriate noise model.
The first simulation presented in this thesis models the acoustic pressure field as a
complex Gaussian random vector and compares the performance of the pseudoinverse,
reduced rank pseudoinverse, sampled mode shape, PCML minimum power distortionless response (MPDR), PCML-MAP, and MAP mode filters. The PCML-MAP filter
performs as well as the MAP filter without the need for a priori data statistics. The
PCML-MPDR filter performs nearly as well as the MAP filter as well, and avoids a
sawtooth pattern that occurs with the reduced rank pseudoinverse filter. The second
simulation presented models the underwater environment and broadband communication setup of the Shallow Water 2006 (SW06) experiment. Data processing results
are presented from the Shallow Water 2006 experiment, showing the reduced sensitivity of the PCML-MPDR filter to white noise compared with the reduced rank
pseudoinverse filter. Lastly, a linear, decision-directed, RLS equalizer is used to combine the response of several modes and its performance is compared with an equalizer
applied directly to the data received on each hydrophone
Polynomial eigenvalue decomposition for multichannel broadband signal processing
This article is devoted to the polynomial eigenvalue decomposition (PEVD) and its applications in broadband multichannel signal processing, motivated by the optimum solutions provided by the eigenvalue decomposition (EVD) for the narrow-band case [1], [2]. In general, the successful techniques from narrowband problems can also be applied to broadband ones, leading to improved solutions. Multichannel broadband signals arise at the core of many essential commercial applications such as telecommunications, speech processing, healthcare monitoring, astronomy and seismic surveillance, and military technologies like radar, sonar and communications [3]. The success of these applications often depends on the performance of signal processing tasks, including data compression [4], source localization [5], channel coding [6], signal enhancement [7], beamforming [8], and source separation [9]. In most cases and for narrowband signals, performing an EVD is the key to the signal processing algorithm. Therefore, this paper aims to introduce PEVD as a novel mathematical technique suitable for many broadband signal processing applications
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Design and Implementation of System Components for Radio Frequency Based Asset Tracking Devices to Enhance Location Based Services. Study of angle of arrival techniques, effects of mutual coupling, design of an angle of arrival algorithm, design of a novel miniature reconfigurable antenna optimised for wireless communication systems
The angle of arrival estimation of multiple sources plays a vital role in the field of array signal
processing as MIMO systems can be employed at both the transmitter and the receiver end
and the system capacity, reliability and throughput can be significantly increased by using array
signal processing. Almost all applications require accurate direction of arrival (DOA) estimation
to localize the sources of the signals. Another important parameter of localization systems is
the array geometry and sensor design which can be application specific and is used to
estimate the DOA.
In this work, various array geometries and arrival estimation algorithms are studied and then a
new scheme for multiple source estimation is proposed and evaluated based on the
performance of subspace and non-subspace decomposition methods. The proposed scheme
has shown to outperform the conventional Multiple Signal Classification (MUSIC) estimation
and Bartlett estimation techniques. The new scheme has a better performance advantage at
low and high signal to noise ratio values (SNRs).
The research work also studies different array geometries for both single and multiple incident
sources and proposes a geometry which is cost effective and efficient for 3, 4, and 5 antenna
array elements. This research also considers the shape of the ground plane and its effects on
the angle of arrival estimation and in addition it shows how the mutual couplings between the
elements effect the overall estimation and how this error can be minimised by using a decoupling
matrix.
At the end, a novel miniaturised multi element reconfigurable antenna to represent the receiver
base station is designed and tested. The antenna radiation patterns in the azimuth angle are
almost omni-directional with linear polarisation. The antenna geometry is uniplanar printed logspiral
with striplines feeding network and biased components to improve the impedance
bandwidth. The antenna provides the benefit of small size, and re-configurability and is very
well suited for the asset tracking applications
Ultra-Wideband Secure Communications and Direct RF Sampling Transceivers
Larger wireless device bandwidth results in new capabilities in terms of higher data rates and security. The 5G evolution is focus on exploiting larger bandwidths for higher though-puts. Interference and co-existence issues can also be addressed by the larger bandwidth in the 5G and 6G evolution. This dissertation introduces of a novel Ultra-wideband (UWB) Code Division Multiple Access (CDMA) technique to exploit the largest bandwidth available in the upcoming wireless connectivity scenarios. The dissertation addresses interference immunity, secure communication at the physical layer and longer distance communication due to increased receiver sensitivity. The dissertation presents the design, workflow, simulations, hardware prototypes and experimental measurements to demonstrate the benefits of wideband Code-Division-Multiple-Access. Specifically, a description of each of the hardware and software stages is presented along with simulations of different scenarios using a test-bench and open-field measurements. The measurements provided experimental validation carried out to demonstrate the interference mitigation capabilities. In addition, Direct RF sampling techniques are employed to handle the larger bandwidth and avoid analog components. Additionally, a transmit and receive chain is designed and implemented at 28 GHz to provide a proof-of-concept for future 5G applications. The proposed wideband transceiver is also used to demonstrate higher accuracy direction finding, as much as 10 times improvement