Energy Detection of Unknown Deterministic Signals in the Presence of Jamming

Urkowitz [1]has discussed the detection of a deterministic signal of unknown structure in the presence of flat, band-limited, Gaussian noise of known power density. That analysis is extended here to the case where jamming or other conditions preclude knowledge of the noise power density. The chi-square statistic of Urkowitz is replaced with Fisher's variance-ratio statistic, using a separate set of noise samples to estimate the unknown noise power density. Curves are given to show the additional degradation of perform over that due to ignorance of the signal structure, caused by ignorance of the noise power density.     

Implementing digital terrain data in knowledge-aided space-time adaptive processing

Many practical problems arise when implementing digital terrain data in airborne knowledge-aided (KA) space-time adaptive processing (STAP). This paper addresses these issues and presents solutions with numerical implementations. In particular, using digital land classification data and digital elevation data, techniques are developed for registering these data with radar return signals, correcting for Doppler and spatial misalignments, adjusting for antenna gain, characterizing clutter patches for secondary data selection, and ensuring independent secondary data samples. These techniques are applied to select secondary data for a single-bin post-Doppler STAP algorithm using multi-channel airborne radar measurement (MCARM) program data. Results with the KA approach are compared with those obtained using the standard sliding window method for choosing secondary data. These results illustrate the benefits of using terrain information, a priori data about the radar, and the importance of statistical independence when selecting secondary data for improving STAP performance     

The Coma of Comet 9P/Tempel 1

As comet 9P/Tempel 1 approaches the Sun in 2004–2005, a temporary atmosphere, or “coma,” will form, composed of molecules and dust expelled from the nucleus as its component icy volatiles sublimate. Driven mainly by water ice sublimation at surface temperatures T > 200 K, this coma is a gravitationally unbound atmosphere in free adiabatic expansion. Near the nucleus (≤ 10² km), it is in collisional equilibrium, at larger distances (≥10⁴ km) it is in free molecular flow. Ultimately the coma components are swept into the comet’s plasma and dust tails or simply dissipate into interplanetary space. Clues to the nature of the cometary nucleus are contained in the chemistry and physics of the coma, as well as with its variability with time, orbital position, and heliocentric distance. The DI instrument payload includes CCD cameras with broadband filters covering the optical spectrum, allowing for sensitive measurement of dust in the comet’s coma, and a number of narrowband filters for studying the spatial distribution of several gas species. DI also carries the first near-infrared spectrometer to a comet flyby since the VEGA mission to Halley in 1986. This spectrograph will allow detection of gas emission lines from the coma in unprecedented detail. Here we discuss the current state of understanding of the 9P/Tempel 1 coma, our expectations for the measurements DI will obtain, and the predicted hazards that the coma presents for the spacecraft. An erratum to this article is available at .     

The History and Dynamics of Comet 9P/Tempel 1

Since its discovery in 1867, periodic comet 9P/Tempel 1 has been observed at 10 returns to perihelion, including all its returns since 1967. The observations for the seven apparitions beginning in 1967 have been fit with an orbit that includes only radial and transverse nongravitational accelerations that model the rocket-like thrusting introduced by the outgassing of the cometary nucleus. The successful nongravitational acceleration model did not assume any change in the comet’s ability to outgas from one apparition to the next and the outgassing was assumed to reach a maximum at perihelion. The success of this model over the 1967–2003 interval suggests that the comet’s spin axis is currently stable. Rough calculations suggest that the collision of the impactor released by the Deep Impact spacecraft will not provide a noticeable perturbation on the comet’s orbit nor will any new vent that is opened as a result of the impact provide a noticeable change in the comet’s nongravitational acceleration history. The observing geometries prior to, and during, the impact will allow extensive Earth based observations to complement the in situ observations from the impactor and flyby spacecraft.     

The GGS/POLAR magnetic fields investigation

The magnetometer on the POLAR Spacecraft is a high precision instrument designed to measure the magnetic fields at both high and low altitudes in the polar magnetosphere in 3 ranges of 700, 5700, and 47000 nT. This instrument will be used to investigate the behavior of fieldaligned current systems and the role they play in the acceleration of particles, and it will be used to study the dynamic fields in the polar cusp, magnetosphere, and magnetosheath. It will measure the coupling between the shocked magnetosheath plasma and the near polar cusp magnetosphere where much of the solar wind magnetosphere coupling is thought to take place. Moreover, it will provide measurements critical to the interpretation of data from other instruments. The instrument design has been influenced by the needs of the other investigations for immediately useable magnetic field data and high rate (100+vectors s^–1) data distributed on the spacecraft. Data to the ground includes measurements at 10 vectors per second over the entire orbit plus snapshots of 100 vectors per second data. The design provides a fully redundant instrument with enhanced measurement capabilities that can be used when available spacecraft power permits.     

A coarse/fine search PN code acquisition scheme

A parallel two-stage acquisition technique is described for direct sequence spread spectrum (DS/SS) range finding applications. The technique offers hardware complexity that scales better with code length than matched filter correlators while providing better performance than sequential detection using comparable hardware     

Adaptive polarimetric target detection with coherent radar. II.Detection against non-Gaussian background

For pt. I see ibid., vol. 37, no. 4, pp. 1194-1206 (2001).This paper presents the derivation of a polarimetric coherent adaptive scheme to detect a radar target against a non-Gaussian background. This completes the results presented in Part I for the Gaussian background. A Texture Free-Generalized Likelihood Ratio Test (TF-GLRT) detector is derived that exploits the polarimetric characteristics of the received radar echoes to improve the detection performance. The proposed polarimetric detector is shown to have Constant False Alarm Rate (CFAR) when operating against compound-Gaussian clutter with unknown parameters. Its performance is fully characterized by both theoretical analysis and simulation. Moreover, the application to recorded radar data demonstrates the performance improvement achievable in practice     

Resonant inverters for photovoltaic array to utility interface

A number of high-frequency link power converter schemes suitable for interconnecting a photovoltaic (PV) array to the utility line using resonant inverters are presented. Use of high-frequency resonant inverters (HFRI) results in reduced size, weight and cost. Scheme 1 uses the HFRI-cycloconverter, scheme 2 uses the HFRI-rectifier pulsewidth-modulated voltage source inverter, scheme 3 uses the HFRI-rectifier line commutated inverter working with a fixed maximum possible inverting fringe angle, and scheme 4 uses the HFRI-rectifier line-connected inverter (with line current modulation). These schemes are compared. Based on the comparison, scheme 3 was selected for an initial study. To overcome various problems associated with scheme 3, the line current is modulated sinusoidally in scheme 4. In this scheme, the HFRI is controlled appropriately to obtain a rectified sine wave of 120 Hz in the DC link and the function of the line-connected inverter is to unfold this waveform on alternate half cycles to obtain a sinusoidal line current with the line voltage. Methods of commutation of the line connected inverter are explained. Experimental results obtained with scheme 4 are presented     

The atmospheric composition,extinction and luminosity of the LBV R71

ESO 3.6m Caspec spectra of the LMC luminous blue variable (LBV) taken at minimum have been analysed using NLTE model atmospheres and line formation calculations to derive atmospheric parameters and chemical composition. Using the silicon ionization balance and the hydrogen Balmer lines we deriveT _eff =17250, log g=1.80 and a microturbulent velocity of 15–20 km/s. The analysis yields abundance ratios by number of approximately 0.43 for He/H, 0.03 for C/N and 0.14 for O/N, implying that enrichment of the atmosphere by processed material has taken place. We have re-evaluated the reddening of R71 using IUE low resolution data and published UBVRIJHKL photometry and derive a value for A _V of 0.63. We also construct an extinction curve using archive IUE data for mid-B LMC supergiants and show that the extinction is anomalous; the 2175A bump being almost absent and the far UV rise very pronounced. A comparison of our model flux in theV-band with the observed (dereddened)V magnitude and the D.M. of the LMC (18.45), implies that the bolometric magnitude or R71 is –9.9. This is significantly higher than the value of –9.0 usually adopted for R71 and suggests that this object may not in fact be a subluminous LBV.     

Spatio-temporal pattern recognition using hidden Markov models

A spatio-temporal method for identifying objects contained in an image sequence is presented. The Hidden Markov Model (HMM) technique is used as the classification algorithm, making classification decisions based on a spatio-temporal sequence of observed object features. A five class problem is considered. Classification accuracies of 100% and 99.7%, are obtained for sequences of images generated over two separate regions of viewing positions. HMMs trained on image sequences of the objects moving in opposite directions showed a 98.1% successful classification rate by class and direction of movement. The HMM technique proved robust to image corruption with additive correlated noise and had a higher accuracy than a single-look nearest neighbor method. A real image sequence of one of the objects used was successfully recognized with the HMMs trained on synthetic data. This study shows the temporal changes that observed feature vectors undergo due to object motion hold information that can yield superior classification accuracy when compared with single-frame techniques