1D optimum and adaptive radar processing space-time adaptive processing important factors affecting STAP performance reduced-rank and minimized sample support STAP other topics appendix.

Space-Time Adaptive Processing for Radar

Traditional analysis of space-time adaptive radar generally assumes the ideal condition of statistically independent and identically distributed (IID) secondary data. To the contrary, measured data suggests realistic clutter environments appear heterogeneous and so the secondary data is no longer IID. Heterogeneity leads to mismatch between actual and estimated covariance matrices, thereby magnifying the loss between the adaptive implementation and optimum condition. Concerns regarding the impact of clutter heterogeneity on space-time adaptive processing (STAP) warrant further study. To this end, we propose space-time models of amplitude and spectral clutter heterogeneity, with operational airborne radar in mind, and then characterize expected STAP performance loss under such heterogeneous scenarios. Simulation results reveal loss in signal-to-interference plus noise ratio (SINR) ranging between a few tenths of a decibel to greater than 16 dB for specific cases.

Space-time adaptive radar performance in heterogeneous clutter

Factored space-time processing has been proposed as a reasonable suboptimal solution to reduce ground clutter in an airborne radar system in order to lower the enormous computational complexity required in fully adaptive processing. An algorithm for mitigating loss in performance of the basic factored technique by extending the Doppler filter spatial weight set to include various degrees of adjacent Doppler coupling is described. The extended factored algorithm is developed, and performance results, vis-a-vis the optimal and basic factored approaches, are presented for both theoretical and measured airborne clutter scenarios. >

Extended factored space-time processing for airborne radar systems

A direct data domain (D/sup 3/) least-squares space-time adaptive processing (STAP) approach is presented for adaptively enhancing signals in a nonhomogeneous environment. The nonhomogeneous environment may consist of nonstationary clutter and could include blinking jammers. The D/sup 3/ approach is applied to data collected by an antenna array utilizing space and in time (Doppler) diversity. Conventional STAP generally utilizes statistical methodologies based on estimating a covariance matrix of the interference using data from secondary range cells. As the results are derived from ensemble averages, one filter (optimum in a probabilistic sense) is obtained for the operational environment, assumed to be wide sense stationary. However for highly transient and inhomogeneous environments the conventional statistical methodology is difficult to apply. Hence, the D/sup 3/ method is presented as it analyzes the data in space and time over each range cell separately. The D/sup 3/ method is deterministic in approach. From an operational standpoint, an optimum method could be a combination of these two diverse methodologies. This paper represents several new D/sup 3/ approaches. One is based on the computation of a generalized eigenvalue for the signal strength and the others are based on the solution of a set of block Hankel matrix equations. Since the matrix of the system of equations to be solved has a block Hankel structure, the conjugate gradient method and the fast Fourier transform (FFT) can be utilized for efficient solution of the adaptive problem. Illustrative examples presented in this paper use measured data from the multichannel airborne radar measurements (MCARM) database to detect a Sabreliner in the presence of urban, land, and sea clutter. An added advantage for the D/sup 3/ method in solving real-life problems is that simultaneously many realizations can be obtained for the same solution for the signal of interest (SOI). The degree of variability amongst the different results can provide a confidence level of the processed results. The D/sup 3/ method may also be used for mobile communications.

A deterministic least-squares approach to space-time adaptive processing (STAP)

To support the development of high-capacity air-to-ground links for range extension, measurements of the low-altitude air-to-ground channel were made at 915 MHz. Two transmit antennas were mounted on an unmanned aerial vehicle (UAV), which was flown in loops at an altitude of approximately 200 m above ground level. The received signals were recorded at each of eight antenna elements mounted on a van at locations outside and inside the flight loop. The analysis of the measurements shows that there are regions where the spatial diversity is significant, despite the sparse multipath environment, indicating spatial decorrelation at both the ground and air terminals. The variations in spatial correlation across the receiver array indicate the presence of nonplanar wavefronts produced by the signals' interaction with objects in the array near field, in particular the measurement vehicle. A similar effect is probable at the UAV, and it is expected that more significant near-field effects would arise on a more conventional air platform. These support significant reductions in outage probability at both receiver locations: With appropriate signaling strategies, an airborne platform could provide a viable relay or broadcast node for high-capacity communications using a multiple-input–multiple-output (MIMO) system.

Measurement and Characterization of Low-Altitude Air-to-Ground MIMO Channels

It is shown that internal clutter motion, aircraft crabbing, scattering from near-field obstacles, and channel mismatch can limit the effectiveness of space-time processing in eliminating airborne clutter. An analytical expression is developed to show how each of these effects produces a deterioration in the signal-to-clutter-plus-noise ratio achievable. By studying the spectral decomposition of the covariance matrix, it is found that the effects of both internal clutter motion and crabbing can either be compensated by artificially adding noise or by processing more pulses. A near-field obstacle produces a spread of the clutter into all of sine azimuth-Doppler space. It is shown that the space-time processor attempts to compensate for this effect by placing a near-field null on the obstacle. Thus, adding more elements is much more effective in eliminating this effect than is processing more pulses. Channel mismatch can be alleviated by controlling the dispersive errors more tightly and by increasing the number of receive elements. >

Some limitations on the effectiveness of airborne adaptive radar

Space-time processing has been proposed as an approach by which an airborne radar can adaptively detect small targets in the presence of ground clutter and jammers, provided the covariance matrix of the interference is available. One of the difficulties in estimating the covariance matrix is the need to obtain a sufficient number of independent samples, especially for high pulse-repetition-frequency (PRF) systems. It is shown here that this difficulty can be overcome by combining subaperture averaging, or spatial smoothing, of the received data with conventional range bin averaging. >

Clutter covariance smoothing by subaperture averaging

Advanced airborne radar may require adaptive space-time processing (STP) to detect small targets at long ranges. STP is a multidimensional adaptive filter that resolves received radar data into a spectrum of plane waves in angular and Doppler frequency coordinates. The platform of an airborne radar can scatter incident signals into the antenna, spreading the spectra of the clutter signals so that it overlaps the target signal and therefore increases the false alarm rate. To reduce the processing requirements of a full STP filter, a suboptimal architecture with fewer degrees of freedom is demonstrated and compared with the optimal architecture. >

Adaptive antenna space-time processing techniques to suppress platform scattered clutter for airborne radar

The authors study how internal clutter motion, channel mismatch, platform interaction and nonstationary jammer multipath limit the effectiveness of an airborne adaptive radar. Approaches to mitigate these effects are discussed. >

E.C. Barile

Papers

Some limitations on the effectiveness of airborne adaptive radar

Clutter covariance smoothing by subaperture averaging

Adaptive antenna space-time processing techniques to suppress platform scattered clutter for airborne radar

Performance of space-time adaptive airborne radar