Traditional millimeter-wave surface movement radar (SMR) has been designed and tested. A novel concept for the design of a new SMR is suggested based on synthetic aperture antenna and noise radar technology. It enables designing SMR without mechanical rotation of an antenna, but applying several nonmoving synthetic aperture antennas instead. Application of noise radar technology is also considered in more detail to improve the expected performance of a new SMR.

The capabilities of millimeter wave radars have been demonstrated for a long period of time for missile seeker applications and for automotive radars. The technological advantages of this type of radar can be adapted to security applications in air traffic management at short and medium range as well as on the ground. The application discussed in this paper focuses on inverse synthetic aperture radar (ISAR) imaging techniques for the derivation of high-resolution signatures of helicopters in the air and the determination of reference images using turntable measurements.

Detection in most surveillance radars is based on the condition of point targets against a more or less homogeneous background. Currently, the resolution of many new types of radar is increasing, at least in the range dimension. Therefore many objects can no longer be considered as points. Also as a consequence, the background is becoming more diverse, in statistical terms. The scene addressed in this paper concerns a ground clutter environment, and extended objects observed with a polarimetric radar with modestly high resolution (i.e. 6 m in range). A step-by-step approach is proposed for the detection and parameter assessment of extended objects and adding classification based on polarimetric features. The evaluation of this approach is based on recordings of real natural scenes and artificially inserted extended objects. It has been observed that in multi-stage detection object classification benefits from several features, including polarimetric ones. It is proposed that the quality of the contour circumscribing the object is the prime factor for quality of features next to polarimetric features. Clutter is affecting, however, the edges of the contours, and therefore may have a major impact on features that are dependent on the shape of these contours. The results also suggest that in the case of large targets with a basically simple shape, like ships, the eccentricity of the shape of the extended object is consistent from scan to scan and probably could support the target tracking.

Systems based on secondary surveillance radar (SSR) downlink signals, both with directional and with omni-directional antennae (such as in multilateration), are operational today and more and more installations are being planned. In this frame, high-density traffic leads to the reception of a mixture of several overlapping SSR replies. By nature, SSR sources are sparse, i.e. with amplitude equal to zero with significantly high probability. While in the literature several algorithms performing sources separation with an m-element antenna have been proposed, none has satisfactorily employed the full potential of sparsity for SSR signals. Most sparsity algorithms can separate only real-valued sources, although we present in this study two algorithms to separate the complex-valued SSR sources. Recorded signals in a live environment are used to demonstrate the effectiveness of the proposed techniques.

The aim of this study is to increase the capacity of the 1090 MHz secondary surveillance radar (SSR) channel by novel transmission and decoding techniques. In particular, multilateration stations have omni-directional antennae; hence considering aircraft traffic and including the extension of surveillance to cooperating vehicles, the reception of superimposed signals is more and more probable. We propose mitigating this problem by combining frequency agility and source separation techniques; we analyze the pertaining channel capacity improvement, and then evaluate the detection and timing estimation for frequency-shifted and separated signals.

Passive location techniques have always been considered an important topic and recently, thanks to digital signal processing (DSP) advances, new methods are being studied and experimented with. The possibility to passively locate radar emitters avoiding transmission is crucial in a variety of military applications, in particular when a flying platform (aircraft or helicopter) is entering an unknown and potentially hostile area. Elettronica SpA (ELT) gave start in 2004 to an experimental campaign in this field with the support and collaboration of the Italian Ministry of Defence (MoD). In this context the following activities were carried out:

• – theoretical study (with analytically derived and simulated results) of a passive location algorithm,

• – design and development of a passive location demonstrator (PLD) qualified for flight,

• – field tests (July 2006) performed in Sardegna (Salto di Quirra).

The subspace-based technique is used for the estimation of the time of arrival and Doppler shift of a signal of known waveform. The tool to find required subspaces is a special orthogonal decomposition of received data. It allows one to concentrate Fisher information on the desired parameter in just a few of the first terms of the decomposition. This approach offers a low-dimensional vector of sufficient statistics. It leads to computationally efficient Bayesian estimation. Besides, it results in expansion of the signal-to-noise ratio (SNR) range for effective maximum likelihood (ML) estimation. Finally, we can obtain independent time arrival and Doppler shift estimations based on generalized eigenvectors.

Multilateration (MLAT) systems and wide area MLAT (WAM) systems are particular cases of multisite (multistatic) radar systems (MSRSs): passive MSRSs (PMSRSs) with known expected signal waveforms. One of the most stringent requirements on an MLAT system is a very high accuracy of target (emitter) localization. In view of this, the potential accuracy of emitter localization (PAEL) based on Cramer–Rao inequality is important. Its dependence on system geometry and time of arrival (TOA) measurement accuracy allows choosing reasonable system geometry and requirements on TOA measurements. PAEL for MLAT and WAM systems with different geometry is considered, including systems proposed for the Marco Polo airport in Venice, Italy. The possibility of velocity determination using PAEL for landing and taking off aircrafts is also discussed. The concept of PAEL permits one to analyze joint measurements of different signal parameters and target coordinates. The effect of additional elevation angle measurements on PAEL in the WAM system for the Marco Polo airport is shown.

Two localization algorithms for multilateration systems are derived and analyzed. Instead of the classical time difference of arrival (TDOA), a direct use of the time of arrival (TOA) is made. The algorithms work for arbitrary spatial dimensions and overdetermined systems. These derivations are tested in a real-case implementation with simulated data (in particular, the multilateration (MLAT) system installed on the Malpensa Airport in Milan was considered for the MLAT simulation and its possible extension to wide area multilateration (WAM) system was considered for WAM trials). The results are also compared with the present-day algorithms performance, mostly based on TDOA.

This paper describes some key points of a new tool being currently developed by Eurocontrol for the assessment of air traffic control (ATC) multisensor trackers performance. It summarizes the algorithmic foundations of the high-accuracy trajectory reconstruction process used to obtain reference trajectories from recorded measures. These trajectories will serve as a reference for the evaluation of the accuracy of ATC data processing centers. The performance of the system is illustrated with some reconstruction experiments on synthetic and real data.