Pietro Stinco

Impact of Sea Clutter Nonstationarity on Disturbance Covariance Matrix Estimation and CFAR Detector Performance

Adaptive detection of signals embedded in non-Gaussian clutter is an important challenge for radar engineers. We present an analysis of sea clutter nonstationarity with respect to clutter covariance matrix estimation and its impact on the constant false alarm rate (CFAR) property of the normalized adaptive matched filter (NAMF). Three covariance matrix estimators, e.g., the sample covariance matrix (SCM), the normalized sample covariance matrix (NSCM), and the approximate maximum likelihood (AML) estimators, have been investigated. The impact of nonstationarity, which emerges in the statistical analysis of the clutter data, is measured in terms of probability of false alarm and probability of detection. Performance analysis is presented using both simulated data and measured sea clutter data recorded by two different X-band radars, namely, the Fynmeet radar and the IPIX radar.

Posterior Cramér–Rao lower bounds for passive bistatic radar tracking with uncertain target measurements

Abstract In the context of target tracking, the Posterior Cramer–Rao Lower Bound (PCRLB) provides a powerful tool to assess the optimal achievable accuracy of target state estimation. In the bistatic configuration both geometry factors and transmitted waveform play an important role in the estimation accuracy. In this paper, we derive the PCRLB on sequential target state estimation accuracy in a bistatic radar tracking scenario, in the most general case of uncertain target measurements, i.e. when the probability of detection is less than one and the probability of false alarm is greater than zero. Then, we propose a PCRLB-based algorithm for selecting the best transmitter of opportunity for the tracking of a radar target in a multisensor Passive Coherent Location (PCL) system.

Design of a cognitive radar for operation in spectrally dense environments

This paper presents a new idea for cognitive radar operating in spectrally dense environments. In particular, the case is addressed when the instantaneous frequency of the radar, assumed to be a wideband or ultra wideband radar, spans several channels, which are used at the same time by other users for communication services. This work proposes a decentralized frequency sharing protocol, which optimizes the performance of the radar and, at the same time, limits the interference received by the other users.

A fast spectrum sensing for CP-OFDM cognitive radio based on adaptive thresholding

Recently, cyclostationarity (CS) based detection methods exploiting the autocorrelation periodicity property of the orthogonal frequency division multiplexing (OFDM) signals attracted a lot of attention. These detection methods are more complex than energy detection but they have better detection performance in low-SNR regimes. The drawback, however, is their extensive computational complexity. In this paper, we propose a computationally efficient spectrum sensing method for detecting unsynchronized OFDM signals in additive white Gaussian noise (AWGN). The proposed method exploits the second-order CS property of OFDM signals to set an adaptive threshold, which achieves the desired constant false alarm rate (CFAR) property. The complexity of the proposed method is significantly reduced compared with the scheme proposed in 22. Monte-Carlo simulations illustrate that the performance of the proposed detector outperforms the classical energy detector (ED), the sliding window detector (SW) and Axells detector in addition to guaranteeing a low sensing time. A spectrum sensing (SS) method for detecting unsynchronized OFDM signals in additive white Gaussian noise (AWGN) is proposed.An adaptive CFAR spectrum sensing algorithm is considered based on the generalized likelihood ratio test (GLRT).The SS detector has a capability of adaption to noise fluctuations by maintaining a desired probability of false alarm constant.The proposed detector can be considered as a good candidate for practical implementation of SS for OFDM signals.

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.

Statistical analysis of bistatic and monostatic sea clutter

In this work, we analyze the sea clutter data collected simultaneously by the bistatic and monostatic nodes of an S-band netted radar system under different out-of-plane geometries. The empirical distribution of sea clutter data are fitted to some known heavy-tailed distributions, and the sea spikes statistics are examined. Our analyses show that spikiness is higher for small bistatic angles and that bistatic data are sometimes less spiky than monostatic ones only for horizontal polarization.

Cramér-Rao bounds and their application to sensor selection

This work deals with the analysis of a multisensor radar system in the context of maritime border control scenario. The system is composed by a receiver that exploits the signal emitted by two non co-operative transmitters of opportunity: a UMTS base station and a FM radio station. An algorithm for selecting the transmitter for the tracking of a radar target is proposed. This algorithm can provide a significant aid to harbour protection and can reduce the computational load of surveillance operations.

Channel parameters estimation for cognitive radar systems

This paper deals with the problem of a cognitive radar system that shares the same frequency band with a communication system, supposed to be the primary user of channel. A cognitive algorithm is proposed to estimate the channel parameters that describe the behaviour of the primary user and how to exploit these estimates to minimize the interference between the radar and the communication system. The performance of the proposed algorithm are assessed in terms of probability of collision, that is the probability that the radar transmits when the primary user already occupies the channel, and probability to lose a spectrum opportunity, that is the probability that the radar does not transmit when the channel is free.

Multistatic target recognition in real operational scenarios

The ability to recognize quickly and reliably non cooperative targets is a primary issue in modern radar systems. The use of a multistatic radar has already been demonstrated to improve sensibly the recognition capacity of a radar system, through the exploitation of its inherent spatial diversity, given by the presence of multiple observation channels. In this paper, we evaluate the performance of a multistatic radar, which uses a correlation based classification algorithm for each channel of the multistatic system and a suitable fusion rule that combines the decisions coming from different channels. This fusion rule, referred as SELX (SELection of tX and rX), takes into account that each channel decision is influenced by a number of parameters, including the relative positions between target, transmitter and receiver. As a consequence, a suitable selection is made to favour the channels which show better performance with respect to the other ones. The performance evaluation of the SELX rule is carried out and compared with a straight method that takes into account only the SNR. In both the cases the performance are carried out by considering complex targets, each of them modelled as a set of independent scatterers, according to type, form and structure of the target. Four different types of targets are modelled, which emulate real targets. The evaluation demonstrates the ability to classify the targets by means of our methods and algorithms, with a very high probability of correct classification.

White space Passive Coherent Location system based on IEEE 802.22

In this work we describe a Passive Coherent Location (PCL) system that exploits the signals emitted by IEEE 802.22 devices, operating in the white spaces of the VHF/UHF TV bands. The analysed system is called White Space PCL (WS-PCL). To cope with the very low transmitted EIRP of the IEEE 802.22 devices, we focus on the design of a WS-PCL system that exploits all the useful signals received in each frame, and therefore the signals emitted from the Base Station (BS) and the portable Customer Premise Equipment (CPE) devices. In this work we derive the Receiver Operating Characteristic (ROC) of the WS-PCL as a function of the target range from the receiver.