A new airborne rain radar named CAMPR (CRL Airborne Multiparameter precipitation Radar) has been developed for the major purpose of calibrating PR (Precipitation Radar) onboard TRMM (Tropical Rainfall Measuring Mission; scheduled to be launched in 1997) in orbit by observing the same rain with both CAMPR and TRMM satellite. CAMPR operates as a coherent radar at 13.8 GHz, the same frequency as TRMM-PR, and has polarimetric and Doppler capabilities. It is installed on a relatively small aircraft and can scan the antenna over a wide angle range, from the nadir to the near-horizon. These functions have been verified to work well and it is shown that the radar system is accurately calibrated. Examples of measurement data show CAMPR's high capability to extract various quantities relating to precipitation and cloud physics. Before the TRMM launch, CAMPR is being used to obtain TRMM-PR simulation data to help its algorithm development as well as to obtain data concerning precipitation and cloud physics.

For IF direct sampling phase detection method (IFSM) which realizes the arithmetical operations with digital filters by direct A/D (Analog to Digital) conversion of IF (Intermediate Frequency) signal, the method to eliminate DC offset is proposed and developed by using the gate array. A principle of the proposed method and the results of the measurement are shown.

This paper describes a DBF (Digital Beamforming) technique as a spatial filtering in the radar systems. DBF for a beamformer and an adaptive processor are discussed. An architecture for the beamformer is proposed. The beamformer discussed consists of systolic arrays that can form beams arbitrarily. Antenna radiation patterns measured in an open site are shown. For the adaptive processor, Gram-Schmidt transformation method is attained by using systolic arrays. Proposed is a means to prevent target signals from being suppressed in cells of the systolic arrays and to achieve the convergent characteristics independent of the magnitude of undesired signal power. In order to demonstrate the performance of the proposed processor, a test model of the adaptive processor was developed and tested in multiple undesired signal environment. Test results are indicated.

In the ISAR (Inverse Synthetic Aperture Radar), when a target is to be recognized by use of the radar image produced from the radar echoes, it is important first to estimate the scale of the target. To estimate the scale, the rotating motion of the target must be estimated. This paper describes a method for estimating the scale of the target from the information on the radar image by converting the target figure into a simple model and estimating the rotating motion of the target.