On The Positive Definiteness of Polarity Coincidence Correlation Coefficient Matrix

Polarity coincidence correlator (PCC), when used to estimate the covariance matrix on an element-by-element basis, may not yield a positive semi-definite (PSD) estimate. Devlin et al. [1], claimed that element-wise PCC is not guaranteed to be PSD in dimensions p>3 for real signals. However, no justification or proof was available on this issue. In this letter, it is proved that for real signals with p<=3 and for complex signals with p<=2, a PSD estimate is guaranteed. Counterexamples are presented for higher dimensions which yield invalid covariance estimates.Comment: IEEE Signal Processing Letters, Volume 15, pp. 73-76, 200

Multi-UAV Enabled Integrated Sensing and Wireless Powered Communication: A Robust Multi-Objective Approach

In this paper, we consider an integrated sensing and communication (ISAC) system with wireless power transfer (WPT) where multiple unmanned aerial vehicle (UAV)-based radars serve multiple clusters of energy-limited communication users in addition to their sensing functionality. In this architecture, the radars sense the environment in phase 1 (namely sensing phase) and meanwhile, the communications users (nodes) harvest and store the energy from the radar transmit signals. The stored energy is then used for information transmission from the nodes to UAVs in phase 2, i.e., uplink phase. Performance of the radar systems depends on the transmit signals as well as the receive filters; the energy of the transmit signals also affects the communication network because it serves as the source of uplink powers. Therefore, we cast a multi-objective design problem addressing performance of both radar and communication systems via optimizing UAV trajectories, radar transmit waveforms, radar receive filters, time scheduling and uplink powers. The design problem is further formulated as a robust non-convex optimization problem taking into account the the user location uncertainty. Hence, we devise a method based on alternating optimization followed by concepts of fractional programming, S-procedure, and tricky majorization-minimization (MM) technique to tackle it. Numerical examples illustrate the effectiveness of the proposed method for different scenarios

Direction-of-Arrival Estimation for Temporally Correlated Narrowband Signals

signal direction-of-arrival estimation using an array of sensors has been the subject of intensive research and development during the last two decades. Efforts have been directed to both, better solutions for the general data model and to develop more realistic models. So far, many authors have assumed the data to be iid samples of a multivariate statistical model. Although this assumption reduces the complexity of the model, it may not be true in certain situations where signals show temporal correlation. Some results are available on the temporally correlated signal model in the literature. The temporally correlated stochastic Cramer-Rao bound (CRB) has been calculated and an instrumental variable-based method called IV-SSF is introduced. Also, it has been shown that temporally correlated CRB is lower bounded by the deterministic CRB. In this paper, we show that temporally correlated CRB is also upper bounded by the stochastic iid CRB. We investigate the effect of temporal correlation of the signals on the best achievable performance. We also show that the IV-SSF method is not efficient and based on an analysis of the CRB, propose a variation in the method which boosts its performance. Simulation results show the improved performance of the proposed method in terms of lower bias and error variance.Comment: IEEE Transactions on Signal Processing, vol. 57, pp. 600-609, Feb. 200

Statistical Performance Analysis of MDL Source Enumeration in Array Processing

In this correspondence, we focus on the performance analysis of the widely-used minimum description length (MDL) source enumeration technique in array processing. Unfortunately, available theoretical analysis exhibit deviation from the simulation results. We present an accurate and insightful performance analysis for the probability of missed detection. We also show that the statistical performance of the MDL is approximately the same under both deterministic and stochastic signal models. Simulation results show the superiority of the proposed analysis over available results.Comment: Accepted for publication in IEEE Transactions on Signal Processing, April 200

CFAR adaptive threshold for ESM receiver with logarithmic ampliÿcation

Abstract An adaptive threshold with constant false alarm rate (CFAR) property is proposed to be used in a channelized electronic support measures (ESM) system with logarithmic video ampliÿcation. For this purpose, two CFAR processors are designed which are in fact modiÿed excision (MEx) and adaptive MEx (AMEx) processors, previously presented by authors, but modiÿed for the logarithmic ampliÿcation case. In the case of relatively small variations in the noise power, MEx-LOG/CFAR is proposed. This processor exhibits a good robustness against interfering pulses, which cause the major di culty in the estimation of noise statistics. In the case of relatively large variations in the noise power, AMEx-LOG/CFAR processor is proposed. Thanks to a feedback loop in its structure, this processor can easily adapt itself with any change in the background noise power to assure the CFAR property and false alarm rate regulation. Furthermore, in the steady state (constant noise power), its detection performance is independent of the noise power. Methods to determine the design parameters of the proposed processors are discussed, and their performance analysis is studied using Monte Carlo simulations.

Compressed-Domain Detection and Estimation for Colocated MIMO Radar

This article proposes a compressed-domain signal processing (CSP) multiple-input multiple-output (MIMO) radar, a MIMO radar approach that achieves substantial sample complexity reduction by exploiting the idea of CSP. CSP MIMO radar involves two levels of data compression followed by target detection at the compressed domain. First, compressive sensing is applied at the receive antennas, followed by a Capon beamformer, which is designed to suppress clutter. Exploiting the sparse nature of the beamformer output, a second compression is applied to the filtered data. Target detection is subsequently conducted by formulating and solving a hypothesis testing problem at each grid point of the discretized angle space. The proposed approach enables an eightfold reduction of the sample complexity in some settings as compared to a conventional compressed sensing (CS) MIMO radar, thus enabling faster target detection. Receiver operating characteristic curves of the proposed detector are provided. Simulation results show that the proposed approach outperforms recovery-based CS algorithms. </p

Sparse Antenna and Pulse Placement for Colocated MIMO Radar

Multiple-input multiple-output (MIMO) radar is known for its superiority over conventional radar due to its antenna and waveform diversity. Although higher angular resolution, improved parameter identifiability, and better target detection are achieved, the hardware costs (due to multiple transmitters and multiple receivers) and high-energy consumption (multiple pulses) limit the usage of MIMO radars in large scale networks. On one hand, higher angle and velocity estimation accuracy is required, but on the other hand, a lower number of antennas/pulses is desirable. To achieve such a compromise, in this paper, the Cramér-Rao lower bound (CRLB) for the angle and velocity estimator is employed as a performance metric to design the antenna and the pulse placement. It is shown that the CRLB derived for two targets is a more appropriate criterion in comparison with the single-target CRLB since the two-target CRLB takes into account both the mainlobe width and the sidelobe level of the ambiguity function. In this paper, several algorithms for antenna and pulse selection based on convex and submodular optimization are proposed. Numerical experiments are provided to illustrate the developed theory.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Circuits and System