M. Rangaswamy

CSI Usage over Parallel Fading Channels under Jamming Attacks: A Game Theory Study

Consider a parallel channel with M independent flat-fading subchannels. There exists a smart jammer which has possession of a copy of perfect channel state information (CSI) measured and sent back by a receiver to its transmitter. Under this model, a class of two-person zero-sum games is investigated where either achievable mutual information rate or Chernoff bound is taken as the underlying pay-off function with the strategy space of each player determined by respective power control and hopping functions. More specifically, we have tackled and answered the following three fundamental questions. The first one is about whether the transmitter and jammer should hop or fully use all degrees of freedom over the entire parallel channels given the full CSI available to both of them, i.e. to hop or not to hop. The second question is about the impact of sending back CSI on system performance considering that the smart jammer can exploit CSI to further enhance its interference effects, i.e. to feedback or not to feedback. The last question is about whether the amount of feedback information can be reduced given the mutual restrictions between transmitter and jammer, i.e. when to feedback and when not to.

Cramér-Rao bounds and TX-RX selection in a multistatic radar scenario

Multistatic radars utilize multiple transmitter and receiver sites to provide several different monostatic and bistatic channels of observation. Multistatic passive and active systems can offer many advantages in terms of coverage and accuracy in the estimation of target signal parameters but unfortunately their performances are heavily sensitive to the position of receivers (RX) and transmitters (TX) with respect to the target trajectory. As known, geometry factors play an important role in the shape of the ambiguity function (AF) which is often used to measure the possible global resolution and large error properties of the target parameters estimates. Exploiting the relation between the ambiguity function and the Cramér-Rao lower bound (CRLB), in this work we propose an algorithm for choosing in a multistatic scenario, along the trajectory of the tracked target, the pair TX-RX with the best asymptotic performance calculated in terms of CRLB on estimation accuracy.

Detecting multiple slow-moving targets in SAR images

Ground moving target indication (GMTI) radars can detect slow-moving targets if their velocities are high enough to produce Doppler frequencies distinguishable from the surrounding stationary clutter. However, no reliable technique is currently available to detect targets that fall below the minimum detectable velocity (MDV) of GMTI radars. Detecting slow moving targets in synthetic aperture radar (SAR) images has also not ceded a reliable solution. Reflected energy from the target is spread over many pixels in the image due to its motion, degenerating the detection process. The addition of clutter from surrounding stationary objects or ground features further complicates detection. Several techniques for SAR imaging of moving targets have been attempted. These techniques require pre-detection, which, in turn, requires sufficient signal-to-stationary ground clutter ratio (SCR). Other attempts such as adaptive, model-based approaches face exponential combinatorial complexity. Exponential computational cost results from having to consider a large number of combinations between multiple target models and the data. The dynamic logic algorithm (DLA) presented below detects multiple slow-moving targets simultaneously in SAR images with low signal-to-clutter ratio, no minimum velocity requirement, and without combinatorial complexity. The mathematics underlying the algorithm is based on biologically inspired signal processing concepts.

Moving target localization with multistatic radar systems

In this paper we describe a method of processing data from a chosen area as surveyed by a multistatic system for the localization of a target. For this purpose data were acquired using the UCL netted radar and processed with two different incoherent approaches for localizing the target on a grid. The first is a centralized scheme and the second decentralized. Results are compared with two coherent approaches that for detection and coverage have been shown to provide the limits on the achievable performance. Numerical minimization of specific functions has to be applied when the estimated target location is used in a tracking algorithm, so we also report an easy and immediate method to localize one (or more) target which expands the domain of application.

Performance tradeoffs for multi-channel parametric adaptive radar algorithms

Airborne radar systems employing radar sensor arrays utilize multi-channel (MC) signal processing techniques for optimal detection and localization of targets. The detection and localization statistics have mathematical structures that typically require evaluating the inverse of an estimated covariance matrix. Due to the size of sensor arrays and the number of pulses in a coherent processing interval (CPI), the dimension of the covariance arrays is very large (1000s); the computational burden of estimating and inverting such large arrays has led to the development of parametric methodologies that significantly reduce both the computational requirements and the amount of measured data to create the estimated inverse covariance matrix. This paper compares the relative merits, by using performance tradeoff plots of six different parametric algorithms when compared to the conventional sample matrix inversion (SMI) approach.

Soft-decision cognitive radio power control based on intelligent spectrum sensing

We formulate an expression for the channel capacity of a soft-decision cognitive network in which cognitive radio transmitters can share spectrum usage with primary users depending on adaptive interference tolerance limits. We consider the problem of capacity maximization in this domain and provide an efficient polynomial time algorithm for cognitive radio power control. Results obtained using this algorithm will be useful in soft-decision spectrum allocation for cognitive radio (CR) transmitters as well as for developing the general analytic enabling waveform for soft-decision CR.

Mimo Radar, Theory and Experiments

In this paper the data acquired with the UCL radar network are analyzed and the properties of the received multistatic signals are investigated. Under a specific design of the experiment geometry, the statistical properties of the received signals are also studied.

MIMO clutter discrete probing for cognitive radar

A new airborne radar mode is introduced that addresses the problem of high false alarm rates due to strong clutter discretes in the radar field of regard. The new mode takes advantage of emerging cognitive and fully adaptive radar (CoFAR) architectures that support rapid adaptation of the radar space-time transmit waveform. The new mode exploits this flexibility to both rapidly characterize strong clutter discretes and minimize their impact on target detection performance, while minimizing impact to radar timeline. The new mode leverages a MIMO probing approach that rapidly characterizes the clutter discretes in the scene and uses the received signals to form an appropriate space-time waveform response that minimizes their radar return and impact on radar performance during the processing of subsequent radar pulses. The paper provides details about the processing algorithms and presents a performance assessment based on a simulation of an airborne GMTI radar system.

A fully polynomial approximation algorithm for collaborative relaying in sensor networks under finite rate constraints

We take an algorithmic approach to a well-known communication channel problem and develop several algorithms for solving it. Specifically, we develop power control algorithms for sensor networks with collaborative relaying under bandwidth constraints, via quantization of finite rate (bandwidth limited) feedback channels. We first consider the power allocation problem under collaborative relaying where the tradeoff between minimizing ones own energy expenditure and the energy for relaying is considered under the constraints of packet outage probability and bandwidth constrained (finite rate) feedback. Then we develop bandwidth constrained quantization algorithms (due to the finite rate feedback) that seek the optimal way of quantizing channel quality and power values in order to minimize the total average transmission power and satisfy the given probability of outage. We develop two kinds of quantization protocols and associated quantization algorithms. For separate source-relay quantization, we reduce the problem to the well-known k-median problem [1] on line graphs and show a a simple O((KJ)2N) polynomial time algorithm, where log2 KJ is the quantization bandwidth and N is the size of the discretized parameter space. For joint quantization, we first develop a simple 2-factor approximation of complexity O(KJN + N logN). Then, for Ɛ > 0, we develop a fully polynomial approximation scheme (FPAS) that approximates the optimal quantization cost to within an 1+Ɛ-factor. The running time of the FPAS is polynomial in 1/Ɛ, size of the input N and also ln F, where F is the maximum available transmit power.

Waveform diversity and advanced signaling strategies for the Hybrid MIMO Phased Array Radar

The Hybrid MIMO Phased Array Radar, or HMPAR, is a notional concept for a multisensor radar architecture that combines elements of traditional phased-array radar with the emerging technology of Multiple-Input Multiple Output (MIMO) radar. A HMPAR comprises a large number, MP, of T/R elements, organized into M subarrays of P elements each. Within each subarray, passive elementlevel phase shifting is used to steer transmit and receive beams in some desired fashion. Each of the M subarrays are in turn driven by independently amplified phase-coded signals. This paper proposes new transmit signal selection strategies based on the observation that some MIMO signal sets, such as those proposed by us previously, cause a very rapid sequential or raster scan across some field of view. Exploiting this property allows one to create and process multiple beams simultaneously. Furthermore, there exists a range-angle coupling in the transmit and receive signals that may lead to high-resolution target localization.