The problem of designing finite-pulse-train radar signals and receivers to maximize the detectability of targets in the presence of clutter has recently been solved. In practice, the performance of these optimum signal-receiver pairs is often degraded seriously by implementation errors. The purpose of this paper is to present an iterative procedure for designing signal-receiver pairs, which takes into account the effects of implementation errors. This method is compared with the error-free design technique by means of two examples.

In a recent paper on radar detection in clutter, the authors stated that the signal-to-interference ratio\rho_{cf} (u)obtained with the signaluand its optimum filter can have stationary points which are not stationary points of\rho_{mf} (u), the signal-to-interference ratio obtained withuand its matched filter, even when the clutter distribution in range and Doppler is symmetric. This letter strengthens this statement and exhibits an example to support it. The stronger statement is the following: Even for symmetric clutter distributions, the global maximum of\rho_{cf}can exceed the global maximum of\rho_{mf}.

The problem of designing radar signals and receivers that are optimum for detecting a point target masked by thermal noise and clutter returns is considered. In a previous paper, the authors described an iterative algorithm for designing such signals subject to an energy constraint. This paper describes an algorithm for the case where the energy constraint is replaced by a dynamic-range constraint, that is, the ratio of maximum to minimum signal amplitude is limited. The signal to which the algorithm converges satisfies the Kuhn-Tucker conditions, which are necessary for optimality. Examples of the application of both algorithms to radar signal design problems are given.

This paper considers the problem of detecting and estimating the unknown angular location of a radar target that is observed simultaneously by a number of antennas. The amplitude of the signal received by a particular antenna is assumed to depend on the angular location of the target, but the time of arrival of the signal is assumed to be the same at all of the antennas. The generalized likelihood ratio test is used to derive the detection and parameter-estimation strategy for the radar receiver. Explicit expressions for the detector and the angle estimates are derived in a number of important special cases, and the performance of the detector is evaluated. Accuracy formulas for the angle estimates, valid for high signal-to-noise ratios, are derived for the general problem and used to compare the performance of an optimum four-beam monopulse system with a type of monopulse system commonly in use.

The problem to be considered in this paper is that of designing radar signals and receivers that are optimum for detecting a point target masked by a background of clutter returns and thermal noise. The problem of choosing an optimum signal when no constraints are placed on the type of signals allowed is discussed briefly, but the remainder of the paper is restricted to signals and receiver impulse responses that are uniformly spaced, phase and amplitude-tapered pulse trains. Expressions for the signal-to-interference ratio obtained when a signal is used with its matched filter (pm/) and with the optimum filter or clutter filter(\rho_{cf})are then derived together with an explicit expression for the clutter filter. An iterative technique for maximizing\rho_{cf}is devised. This scheme has the useful property that it generates a sequence of signals whose\rho_{cf}'s form a monotone, nondecreasing sequence. This is followed by an application of the calculus of variations to derive the Euler equations for the stationary points of\rho_{cf}and\rho_{mf}. The form of the Euler equations suggests iterative techniques for their solution; in fact, the technique suggested for the solution of the Euler equation associated with\rho_{cf}is essentially the iterative technique that was described above.