This paper describes methods for broadening the beam of a phased array antenna using phase-only element weights. This type of broadening can be valuable for improving the search occupancy and/or reducing the search fr...
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ISBN:
(纸本)1424403081
This paper describes methods for broadening the beam of a phased array antenna using phase-only element weights. This type of broadening can be valuable for improving the search occupancy and/or reducing the search frame time for large phased arrays, when transmit beam broadening is combined with multiple simultaneous receive beams. Phase-only broadening is required for typical solid-state (active phased) arrays because control of the transmit amplitude at each element is not practical. A notable result is that there is a relationship between the amount of beam broadening and the efficiency (directivity) of the resulting beam. In particular it is shown that broadening less than similar to 2.5:1 results in reduced beam efficiency for both linear and circular arrays, while a broadening of greater than similar to 2.5:1 results in improved beam efficiency, and that, therefore, certain broadening configurations will be preferable to the radar designer (e.g. 4:1 in one plane rather than 2:1 in two planes, due to a large difference in efficiency). The algorithms used to achieve the broadening patterns presented here are based on a combination of homotopy from known optimality with a stochastic gradient descent approach using a carefully constructed one parameter family of penalty functions.
Monitoring harsh environments such as underwater scenarios or aircraft external surfaces pertains to important applications like assisted navigation and tactical surveillance;nevertheless, it poses additional challeng...
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ISBN:
(纸本)1424403081
Monitoring harsh environments such as underwater scenarios or aircraft external surfaces pertains to important applications like assisted navigation and tactical surveillance;nevertheless, it poses additional challenges compared with standard applications. At Transducers2005 we presented a wired addressing architecture of distributed sensors for monitoring real-time in-situ pressure variations in underwater environment that faces the above-mentioned issues. This architecture consists in a double array of identical and interconnected smart nodes monitoring a matrix of passive sensors. I n this paper, we present an analysis of the delay model related to the presented architecture and a calculation of the overall frame-rate of the system as a function of the geometrical topology of the arrays. The topology of the network, i.e. the length of each bus and the number of nodes, can be chosen according to the application, and directly affects the global capacitive load on the serial lines. Each serial line can be schematized with a distributed RC model for the flat cable plus a lumped capacitance for each smart node. Then, a 3(rd)-order pi-segmented model of O'Brien-Savarino [4] is calculated for a 16-block fine with block length equal to 0.3m. Thanks to that, the global time per iteration is calculated on each bus as well as the scanning time of the whole matrix and the frame rate for the system as a function of sensor distribution and of the aspect ratio of the matrix. This model can be employed to identify the optimal arrangement for the sensor matrix and smart node arrays.
Close-in sensing is needed for urban warfare operations, where Ground Moving Target Indication (GMTI) could be provided via forward or rear-facing multi-function array radars mounted on small highly-maneuverable airbo...
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ISBN:
(纸本)1424403081
Close-in sensing is needed for urban warfare operations, where Ground Moving Target Indication (GMTI) could be provided via forward or rear-facing multi-function array radars mounted on small highly-maneuverable airborne platforms. However, airborne radar arrays oriented any direction other than side-looking cause an elevation dependent angle-Doppler relationship in the clutter returns. This non-stationarity is acute in close-in sensing geometries where elevation diversity exists over the scene of interest. However, planar arrays have an inherent advantage over linear arrays due to their ability to observe clutter statistics as a function of elevation. This paper demonstrates the utility of elevation diversity by synthesizing a single 3D-STAP filter that exhibits an elevation dependent azimuth-Doppler response which is tailored to null the clutter "bowl" which characterizes the forward-looking clutter spectrum. Such a capability is particularly exploitable on transmit, where all elevation angles are simultaneously illuminated. To demonstrate potential benefits, this paper proposes the use of recently developed Space Time Illumination Patterns (STIP) from a planar AESA to invoke elevation diverse space-time illumination in a forward-looking clutter scenario. It is shown that 3D-STIP (azimuth-elevation-Doppler) facilitates elevation specific space-time beamforming which removes the clutter energy from a given Doppler frequency across all ranges, potentially simplifying processing on receive. Simulations using synthesized training data and clairvoyant covariance knowledge are conducted to demonstrate proof-of-concept.
sensor localization bounds have been derived assuming that received signal strength (RSS) measurements are performed with perfectly known sensor transmit powers. In this paper the Bayesian Cramér-Rao bound is der...
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An asynchronous unicast ad hoc network is considered, where each node i is equipped with a receive/transmit beamformer pair (w(i), g(i)) designed under a quality-of-service (QoS) SNR constraint. It is first shown that...
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An asynchronous unicast ad hoc network is considered, where each node i is equipped with a receive/transmit beamformer pair (w(i), g(i)) designed under a quality-of-service (QoS) SNR constraint. It is first shown that the minimum sum-power beamformers for the network satisfy a weak duality condition, in which the pairs ((g(i)(opt))*, (w(i)(opt))*) achieve the same sum power as the primal network. However, the optimum receive beamformer w(i)(opt) is not in general equal to (g(i)(opt))*, in contrast to the case of cellular and time-division duplexing networks. Iterative minimum mean-square error (IMMSE) beamforming algorithms are then proposed in which w(i) = g(i)* is enforced. These algorithms are shown to be instances of the Power Algorithm in which gi is the maximizing eigenvector of an SNR-related objective matrix. The IMMSE algorithm can also be viewed as a noncooperative beamforming game, in which the payoff includes normalized SNR, and the tax is related to interference caused at other nodes. The existence of fixed points (Nash equilibria) is proved for IMMSE. Furthermore, fixed points of IMMSE are shown to satisfy the first-order necessary conditions for optimization using a network Lagrangian. The IMMSE game is modified to yield a sequential distortionless-response beamforming algorithm, which is shown to be convergent using a Total Interference Function. Extensive simulation results illustrate that IMMSE yields better power efficiency than a greedy noncooperative SNR-maximizing game.
This paper focuses on the various arraysignalprocessing methods that have been inspired by biological models. It discusses the long-standing algorithmic challenges and combinatorial complexity as well as the knowled...
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This paper focuses on the various arraysignalprocessing methods that have been inspired by biological models. It discusses the long-standing algorithmic challenges and combinatorial complexity as well as the knowledge instinct and dynamic logic of these biologically-inspired methods. It also provides examples of these methods used in GMTI tracking, slow-moving targets in SAR and UAV swarm navigation and fusion
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