Introduction

Part I Homogeneous Partitioning of the Surveillance Volume discusses the

implementation of the first of three sequentially complementary approaches for

increasing the probability of target detection within at least some of the cells of

the surveillance volume for a spatially nonGaussian or Gaussian “noise”

environment that is temporally Gaussian. This approach, identified in the Preface

as Approach A, partitions the surveillance volume into homogeneous contiguous

subdivisions. A homogeneous subdivision is one that can be subdivided into

arbitrary subgroups, each of at least 100 contiguous cells, such that all the

subgroups contain stochastic spatio-temporal “noise” sharing the same

probability density function (PDF). At least one hundred cells per subgroup are

necessary for sufficient confidence levels (see Section 4.3). The constant false-

alarm rate (CFAR) method reduces to Approach A if the CFAR “reference” cells

are within the same homogeneous subdivision as the target cell. When the noise

environment is not known a priori, then it is necessary to sample the

environment, classify and index the homogeneous subdivisions, and exclude

samples that are not homogeneous within a subdivision. If this sampling is not

done in a statistically correct manner, then Approach A can yield disappointing

results because the estimated PDF is not the actual PDF. Part I addresses this

issue.