APIS

Array Passive ISAR Adaptive Processing

Detection and classification of small slow moving surface targets in presence of sophisticated jamming from airborne platforms is currently one of the most stringent needs for new European Defence systems. Advanced radar systems with a high level of flexibility, reconfigurability and modularity need high performance adaptive signal processing to fully exploit the radar potentiality.

A possible solution to meet these requirements is to make use of passive radar in antenna array configuration. This new system concept is of great interest for operative military scenarios for the following reasons:

  1. The absence of electromagnetic emission provides a Low Probability of Intercept (LPI).
  2. The system is intrinsically coherent because it directly uses the signal transmitted by the illuminator of opportunity as the reference signal.
  3. Friendly radar emissions, typically present in the area under surveillance, can be exploited as illuminators of opportunity. Radar waveforms are more efficient than communication transmitted signals (better ambiguity function and spatial resolution).

Moreover, the use of a receiving array antenna allows:

  1. forming multiple beams for separating the source reference channel from the surveillance channel
  2. reducing the direct signal interference by creating suitable nulls on the beam pattern in the direction of the transmitter
  3. using beamforming and radar imaging capability for improving target detection, recognition and classification. Beam Electronic steering also allows tracking functionality to be implemented.

The goal of the Project is to study new adaptive signal processing algorithms for Array passive ISAR (APIS) systems.

The main idea is to exploit the antenna array for:

  1. improving target detection and tracking;
  2. enable passive ISAR imaging.

Both airborne and ground-based receiver configurations will be considered. Detection, tracking and imaging of surface targets (both sea and ground targets) will be considered as reference scenarios.

The MAIN STEPS of the SAP-ISAR (Space Adaptive Processing- ISAR) algorithm to be studied are:

  1. SAP is used to remove spatially correlated interference like jammer and clutter.
  2. Targets are selected in the spatial-Doppler frequency domain after SAP filtering. A Range-Doppler data-set is produced for those directions of arrival where targets are detected.
  3. Conversion to range-time format via Inverse Discrete Fourier Transform (IDFT).
  4. ISAR image formation of each target in the scene.

The main BENEFITS of such techniques and system concept are:

  1. Improvement of the Signal to Noise/clutter/Interference, thanks to the use of antenna beam-forming.
  2. Implementation of the ISAR imaging functionality for passive radar, which is an innovative issue in the radar scientific field.
  3. Allowing target tracking by exploiting the electronic beam steering.
  4. Jamming signals are strongly attenuated since they are mainly directed toward the transmitter and the array receiver position is not detectable because of its passive nature.
  5. ISAR jammer can be distinguished by exploiting the jammer DoA in ISAR image sequences.

Contributions of the DEVA Laboratory

We have proposed a Multi-frame Marked Point Process model for automatic target detection and tracking in Inverse Synthetic Aperture Radar (ISAR) image sequences. For purposes of dealing with high ISAR noise, we obtain the optimal target sequence by an energy minimization process, which simultaneously considers the observed image data and prior geometric interaction constraints between the target appearances in the consecutive frames. Finally, a robust permanent scatterer detetection step is introduced to support the target identification process. Evaluation is performed on real ISAR image sequences of ship targets.

Figure: Sample frames from the SHIP2-SHIP7 data sets, and the corresponding detection results of the FmMPP approach obtained by the optimization of the proposed ISAR sequence based model

Technical project leader: Csaba Benedek

Head of the DEVA laboratory: Tamás Szirányi

See our demo

References

[1] Cs. Benedek and M. Martorella, ”Moving Target Analysis in ISAR Image Sequences with a Multiframe Marked Point Process Model,” IEEE Trans. on Geoscience and Remote Sensing, vol. 52, no. 4, pp. 2234 - 2246, 2014

[2] Cs. Benedek and M. Martorella: ”ISAR Image Sequence based Automatic Target Recognition by using a Multi-frame Marked Point Process Model,” IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Vancouver, Canada, July 24-29, 2011

[3] Cs. Benedek and M. Martorella ”Ship Structure Extraction in ISAR Image Sequences by a Markovian Approach,” IET International Conference on Radar Systems, Glasgow, UK, Oct. 22-25, 2012

[4] J. Alvarez, J. Gaitán, F. Berizzi, A. Capria, M. Conti, E. Giusti, M. Martorella, C. Moscardini, D. Olivadese, D. Petri, J. L. Bárcena, D. De La Mata, P. Jarabo, M. Rosa, A. Podda, A. Sulis, Cs. Benedek, T. Szirányi, G. Georgiou, A. Papanastasiou, C. Topping: ”Array Passive ISAR adaptive processing (APIS) project: an overview,” NATO SET 187 Specialists Meeting on "Passive radar, challenges concerning theory and practice in military applications", Szczecin, Poland, May 13-14 2013