STAP has been widely studied for airborne radar as an approach to adaptively detect small target competing with ground clutter. Non-homogeneous interference is currently an important aspect of STAP. The discrete non-h...
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(纸本)0780370007
STAP has been widely studied for airborne radar as an approach to adaptively detect small target competing with ground clutter. Non-homogeneous interference is currently an important aspect of STAP. The discrete non-homogenates due to strong interference or target separating from the clutter ridge accounts for much of the degradation in urban and spiky clutter scenarios. The use of adaptive weights with the hybrid algorithm is widely applicable to discrete non-homogeneity problems, which is a hybridization of a two-dimensional non-statistical method with statistically based methods. This paper presents a new direct data domain processor with a prefilter attenuating clutter to strengthen suppression for discrete non-homogeneous interference. The desirable performance of STAP to discrete non-homogeneous interference is observed.
The convergence analysis of a maximally decimated (MD) adaptive filtering structure (AFS) employing a new adaptation scheme is presented. The structure was based on uniform perfect reconstruction (PR) filter banks (FB...
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The convergence analysis of a maximally decimated (MD) adaptive filtering structure (AFS) employing a new adaptation scheme is presented. The structure was based on uniform perfect reconstruction (PR) filter banks (FB), their dual transmultiplexers (TMUX) and a model for the system under identification of interpolated FIR (IFIR) filters connected in parallel. A new algorithm was used for the adaptation of the subband filter coefficients employing a new power normalisation (PN) scheme introduced in Papoulis et al. (2002). This structure is briefly described here, the adaptive algorithm is presented and an extensive convergence analysis is then given. Reference then is made to the relevant work reported in Petraglia et al. (2000), namely to a structure that can be considered as the dual of the one presented here and employed an adaptive algorithm that is a simplified version of the one we proposed. The convergence analysis is then specialised for the adaptive scheme used in Petraglia. The rest of the paper is an extensive performance comparison of both structures and of the two adaptation schemes, through both theoretical and experimental results. These demonstrate the improvement in the performance our approach offers; highlight aspects of the theoretical analysis and further enlighten on the similarities and differences of the two approaches. A performance comparison with the full-band NLMS algorithm is given.
This paper presents a new scheme to estimate the user mobility by incorporating the aggregate history of mobile users and system parameters. With this approach, each user's position within the location area is dif...
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This paper presents a new scheme to estimate the user mobility by incorporating the aggregate history of mobile users and system parameters. With this approach, each user's position within the location area is differentiated by zone partition for more accurate prediction. In order to provide the flexibility of tradeoff between quality demand and computation complexity, the estimation is adjusted dynamically according to the constraint of prediction order. Then an adaptive algorithm is developed to predict the future position of mobile terminals in terms of location probabilities, while considering each terminal's movement direction, residence time, and path information. Simulation results demonstrate that the signaling cost for location tracking under delay bound is greatly reduced based on the estimated user mobility pattern.
This paper investigates an adaptive robust regulation problem when a discrete-time plant is subjected to both coprime factor perturbation and unknown external disturbances. Firstly, we present a design method of optim...
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This paper investigates an adaptive robust regulation problem when a discrete-time plant is subjected to both coprime factor perturbation and unknown external disturbances. Firstly, we present a design method of optimal robust regulation controller for plant with coprime factor perturbation and unknown external disturbances. Then, based on the idea of set-membership identification, we propose a recursive estimation for extended parameters in which includes the parameters of nominal model and the bound of unmodelled dynamics and disturbances. Finally, we propose a novel adaptive robust tracking scheme, a tight bound for robust performance and prove the overall convergence of the adaptive algorithm. The adaptive scheme proposed in this paper has good robust stability and asymptotically optimal robust performance
We analyse the stability of the Kalman filter with time varying stochastic system parameters-a problem which has been open for a long time. A natural form of stochastic stability is established under conditions that a...
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We analyse the stability of the Kalman filter with time varying stochastic system parameters-a problem which has been open for a long time. A natural form of stochastic stability is established under conditions that are analogues of well known deterministic criteria. Our results are applied to obtain new and weaker conditions for stability of some adaptive algorithms.
Recent work has shown that minimum mean squared error (MMSE) based adaptive interference suppression schemes have the potential of providing large performance and capacity gains over conventional reception for direct ...
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Recent work has shown that minimum mean squared error (MMSE) based adaptive interference suppression schemes have the potential of providing large performance and capacity gains over conventional reception for direct sequence (DS) CDMA systems. However, the applicability of such schemes to future cellular and PCS systems will depend on their ability to cope with the severe time variations characteristic of a wireless channel. We address this issue in the context of Rayleigh faded DS-CDMA signals. Our main results are as follows. (a) Standard decision directed (DD) MMSE adaptation following some initial training is unable to track a typical fading channel. (b) A modified DD (MDD) MMSE adaptation that exploits differential encoding and decoding to simplify the task of tracking is robust against fading and the near-far problem. (c) MDD-MMSE adaptation survives the arrival of new interfering transmissions even in the presence of a severe near-far problem. (d) The performance of the MDD-MMSE algorithm shows some deterioration when there are several rapidly fading independent multipath components, so that further investigation is needed for devising adaptive algorithms for this setting.
Methods of performing sum-of-squares signal power estimation which may be implemented in an extremely simple manner are presented. Two sum-of-square signal power estimators are presented. One of these is to be used wi...
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Methods of performing sum-of-squares signal power estimation which may be implemented in an extremely simple manner are presented. Two sum-of-square signal power estimators are presented. One of these is to be used with a power-of-two quantizer, and the other without. Both improve the implementation complexity of their respective systems with little or no degradation in overall algorithm performance. Comparison, and example designs in a CMOS process illustrate the advantages of the new methods. These methods can be applied to a variety of algorithms, such as normalized adaptive algorithms.< >
We design and evaluate novel adaptive load balancing algorithms for processes in an MIMD architecture. We introduce a gradient descent paradigm to compute on-line load balancing decisions and implement it on an nCube ...
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We design and evaluate novel adaptive load balancing algorithms for processes in an MIMD architecture. We introduce a gradient descent paradigm to compute on-line load balancing decisions and implement it on an nCube target architecture. Our measurements show that such algorithms will substantially improve distributed system performance.< >
Three systolic arrays suitable for implementation of order-recursive least-squares (ORLS) adaptive algorithms are considered. It is shown that they can be constructed using two types of elementary cells. A classificat...
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Three systolic arrays suitable for implementation of order-recursive least-squares (ORLS) adaptive algorithms are considered. It is shown that they can be constructed using two types of elementary cells. A classification of systolic implementations of the ORLS adaptive algorithms is given by exploiting the possible variations of the elementary cells. The investigation of the array structures and variations of the elementary cells leads to a systematic approach to designing reconfigurable systolic arrays for implementation of ORLS algorithms. As an application of this approach, a novel least-squares (LS) lattice algorithm based on Givens rotations is derived.< >
The definitions of instantaneous frequency are reviewed in the context of signal theory, communication theory and discrete time implementations. The spread of a signal about its instantaneous frequency, or instantaneo...
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The definitions of instantaneous frequency are reviewed in the context of signal theory, communication theory and discrete time implementations. The spread of a signal about its instantaneous frequency, or instantaneous bandwidth, is investigated for several common time-frequency distributions by simulations. The instantaneous frequency of a multicomponent signal is examined. Further investigation of the time-frequency representation of a multicomponent signal leads to an adaptive algorithm which may improve time-frequency resolution of multicomponent signals.< >
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